Fast egg collection method greatly improves randomness of egg sampling in Drosophila melanogaster

DEFF Research Database (Denmark)

Schou, Mads Fristrup

2013-01-01

When obtaining samples for population genetic studies, it is essential that the sampling is random. For Drosophila, one of the crucial steps in sampling experimental flies is the collection of eggs. Here an egg collection method is presented, which randomizes the eggs in a water column...... and diminishes environmental variance. This method was compared with a traditional egg collection method where eggs are collected directly from the medium. Within each method the observed and expected standard deviations of egg-to-adult viability were compared, whereby the difference in the randomness...... and to obtain a representative collection of genotypes, the method presented here is strongly recommended when collecting eggs from Drosophila....

Randomized branch sampling to estimatefruit production in Pecan trees cv. ‘Barton’

Directory of Open Access Journals (Sweden)

Filemom Manoel Mokochinski

Full Text Available ABSTRACT: Sampling techniques to quantify the production of fruits are still very scarce and create a gap in crop development research. This study was conducted in a rural property in the county of Cachoeira do Sul - RS to estimate the efficiency of randomized branch sampling (RBS in quantifying the production of pecan fruit at three different ages (5,7 and 10 years. Two selection techniques were tested: the probability proportional to the diameter (PPD and the uniform probability (UP techniques, which were performed on nine trees, three from each age and randomly chosen. The RBS underestimated fruit production for all ages, and its main drawback was the high sampling error (125.17% - PPD and 111.04% - UP. The UP was regarded as more efficient than the PPD, though both techniques estimated similar production and similar experimental errors. In conclusion, we reported that branch sampling was inaccurate for this case study, requiring new studies to produce estimates with smaller sampling error.

Misrepresenting random sampling? A systematic review of research papers in the Journal of Advanced Nursing.

Science.gov (United States)

Williamson, Graham R

2003-11-01

This paper discusses the theoretical limitations of the use of random sampling and probability theory in the production of a significance level (or P-value) in nursing research. Potential alternatives, in the form of randomization tests, are proposed. Research papers in nursing, medicine and psychology frequently misrepresent their statistical findings, as the P-values reported assume random sampling. In this systematic review of studies published between January 1995 and June 2002 in the Journal of Advanced Nursing, 89 (68%) studies broke this assumption because they used convenience samples or entire populations. As a result, some of the findings may be questionable. The key ideas of random sampling and probability theory for statistical testing (for generating a P-value) are outlined. The result of a systematic review of research papers published in the Journal of Advanced Nursing is then presented, showing how frequently random sampling appears to have been misrepresented. Useful alternative techniques that might overcome these limitations are then discussed. REVIEW LIMITATIONS: This review is limited in scope because it is applied to one journal, and so the findings cannot be generalized to other nursing journals or to nursing research in general. However, it is possible that other nursing journals are also publishing research articles based on the misrepresentation of random sampling. The review is also limited because in several of the articles the sampling method was not completely clearly stated, and in this circumstance a judgment has been made as to the sampling method employed, based on the indications given by author(s). Quantitative researchers in nursing should be very careful that the statistical techniques they use are appropriate for the design and sampling methods of their studies. If the techniques they employ are not appropriate, they run the risk of misinterpreting findings by using inappropriate, unrepresentative and biased samples.

SOME SYSTEMATIC SAMPLING STRATEGIES USING MULTIPLE RANDOM STARTS

OpenAIRE

Sampath Sundaram; Ammani Sivaraman

2010-01-01

In this paper an attempt is made to extend linear systematic sampling using multiple random starts due to Gautschi(1957)for various types of systematic sampling schemes available in literature, namely(i)  Balanced Systematic Sampling (BSS) of  Sethi (1965) and (ii) Modified Systematic Sampling (MSS) of Singh, Jindal, and Garg  (1968). Further, the proposed methods were compared with Yates corrected estimator developed with reference to Gautschi’s Linear systematic samplin...

LOD score exclusion analyses for candidate genes using random population samples.

Science.gov (United States)

Deng, H W; Li, J; Recker, R R

2001-05-01

While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes with random population samples. We develop a LOD score approach for exclusion analyses of candidate genes with random population samples. Under this approach, specific genetic effects and inheritance models at candidate genes can be analysed and if a LOD score is < or = - 2.0, the locus can be excluded from having an effect larger than that specified. Computer simulations show that, with sample sizes often employed in association studies, this approach has high power to exclude a gene from having moderate genetic effects. In contrast to regular association analyses, population admixture will not affect the robustness of our analyses; in fact, it renders our analyses more conservative and thus any significant exclusion result is robust. Our exclusion analysis complements association analysis for candidate genes in random population samples and is parallel to the exclusion mapping analyses that may be conducted in linkage analyses with pedigrees or relative pairs. The usefulness of the approach is demonstrated by an application to test the importance of vitamin D receptor and estrogen receptor genes underlying the differential risk to osteoporotic fractures.

Assessment of fracture risk: value of random population-based samples--the Geelong Osteoporosis Study.

Science.gov (United States)

Henry, M J; Pasco, J A; Seeman, E; Nicholson, G C; Sanders, K M; Kotowicz, M A

2001-01-01

Fracture risk is determined by bone mineral density (BMD). The T-score, a measure of fracture risk, is the position of an individual's BMD in relation to a reference range. The aim of this study was to determine the magnitude of change in the T-score when different sampling techniques were used to produce the reference range. Reference ranges were derived from three samples, drawn from the same region: (1) an age-stratified population-based random sample, (2) unselected volunteers, and (3) a selected healthy subset of the population-based sample with no diseases or drugs known to affect bone. T-scores were calculated using the three reference ranges for a cohort of women who had sustained a fracture and as a group had a low mean BMD (ages 35-72 yr; n = 484). For most comparisons, the T-scores for the fracture cohort were more negative using the population reference range. The difference in T-scores reached 1.0 SD. The proportion of the fracture cohort classified as having osteoporosis at the spine was 26, 14, and 23% when the population, volunteer, and healthy reference ranges were applied, respectively. The use of inappropriate reference ranges results in substantial changes to T-scores and may lead to inappropriate management.

Monitoring oil persistence on beaches : SCAT versus stratified random sampling designs

International Nuclear Information System (INIS)

Short, J.W.; Lindeberg, M.R.; Harris, P.M.; Maselko, J.M.; Pella, J.J.; Rice, S.D.

2003-01-01

In the event of a coastal oil spill, shoreline clean-up assessment teams (SCAT) commonly rely on visual inspection of the entire affected area to monitor the persistence of the oil on beaches. Occasionally, pits are excavated to evaluate the persistence of subsurface oil. This approach is practical for directing clean-up efforts directly following a spill. However, sampling of the 1989 Exxon Valdez oil spill in Prince William Sound 12 years later has shown that visual inspection combined with pit excavation does not offer estimates of contaminated beach area of stranded oil volumes. This information is needed to statistically evaluate the significance of change with time. Assumptions regarding the correlation of visually-evident surface oil and cryptic subsurface oil are usually not evaluated as part of the SCAT mandate. Stratified random sampling can avoid such problems and could produce precise estimates of oiled area and volume that allow for statistical assessment of major temporal trends and the extent of the impact. The 2001 sampling of the shoreline of Prince William Sound showed that 15 per cent of surface oil occurrences were associated with subsurface oil. This study demonstrates the usefulness of the stratified random sampling method and shows how sampling design parameters impact statistical outcome. Power analysis based on the study results, indicate that optimum power is derived when unnecessary stratification is avoided. It was emphasized that sampling effort should be balanced between choosing sufficient beaches for sampling and the intensity of sampling

Estimates of Inequality Indices Based on Simple Random, Ranked Set, and Systematic Sampling

OpenAIRE

Bansal, Pooja; Arora, Sangeeta; Mahajan, Kalpana K.

2013-01-01

Gini index, Bonferroni index, and Absolute Lorenz index are some popular indices of inequality showing different features of inequality measurement. In general simple random sampling procedure is commonly used to estimate the inequality indices and their related inference. The key condition that the samples must be drawn via simple random sampling procedure though makes calculations much simpler but this assumption is often violated in practice as the data does not always yield simple random ...

Systematic random sampling of the comet assay.

Science.gov (United States)

McArt, Darragh G; Wasson, Gillian R; McKerr, George; Saetzler, Kurt; Reed, Matt; Howard, C Vyvyan

2009-07-01

The comet assay is a technique used to quantify DNA damage and repair at a cellular level. In the assay, cells are embedded in agarose and the cellular content is stripped away leaving only the DNA trapped in an agarose cavity which can then be electrophoresed. The damaged DNA can enter the agarose and migrate while the undamaged DNA cannot and is retained. DNA damage is measured as the proportion of the migratory 'tail' DNA compared to the total DNA in the cell. The fundamental basis of these arbitrary values is obtained in the comet acquisition phase using fluorescence microscopy with a stoichiometric stain in tandem with image analysis software. Current methods deployed in such an acquisition are expected to be both objectively and randomly obtained. In this paper we examine the 'randomness' of the acquisition phase and suggest an alternative method that offers both objective and unbiased comet selection. In order to achieve this, we have adopted a survey sampling approach widely used in stereology, which offers a method of systematic random sampling (SRS). This is desirable as it offers an impartial and reproducible method of comet analysis that can be used both manually or automated. By making use of an unbiased sampling frame and using microscope verniers, we are able to increase the precision of estimates of DNA damage. Results obtained from a multiple-user pooled variation experiment showed that the SRS technique attained a lower variability than that of the traditional approach. The analysis of a single user with repetition experiment showed greater individual variances while not being detrimental to overall averages. This would suggest that the SRS method offers a better reflection of DNA damage for a given slide and also offers better user reproducibility.

Correlated random sampling for multivariate normal and log-normal distributions

International Nuclear Information System (INIS)

Žerovnik, Gašper; Trkov, Andrej; Kodeli, Ivan A.

2012-01-01

A method for correlated random sampling is presented. Representative samples for multivariate normal or log-normal distribution can be produced. Furthermore, any combination of normally and log-normally distributed correlated variables may be sampled to any requested accuracy. Possible applications of the method include sampling of resonance parameters which are used for reactor calculations.

Occupational position and its relation to mental distress in a random sample of Danish residents

DEFF Research Database (Denmark)

Rugulies, Reiner Ernst; Madsen, Ida E H; Nielsen, Maj Britt D

2010-01-01

PURPOSE: To analyze the distribution of depressive, anxiety, and somatization symptoms across different occupational positions in a random sample of Danish residents. METHODS: The study sample consisted of 591 Danish residents (50% women), aged 20-65, drawn from an age- and gender-stratified random...... sample of the Danish population. Participants filled out a survey that included the 92 item version of the Hopkins Symptom Checklist (SCL-92). We categorized occupational position into seven groups: high- and low-grade non-manual workers, skilled and unskilled manual workers, high- and low-grade self...

Are most samples of animals systematically biased? Consistent individual trait differences bias samples despite random sampling.

Science.gov (United States)

Biro, Peter A

2013-02-01

Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.

Random sampling of evolution time space and Fourier transform processing

International Nuclear Information System (INIS)

Kazimierczuk, Krzysztof; Zawadzka, Anna; Kozminski, Wiktor; Zhukov, Igor

2006-01-01

Application of Fourier Transform for processing 3D NMR spectra with random sampling of evolution time space is presented. The 2D FT is calculated for pairs of frequencies, instead of conventional sequence of one-dimensional transforms. Signal to noise ratios and linewidths for different random distributions were investigated by simulations and experiments. The experimental examples include 3D HNCA, HNCACB and 15 N-edited NOESY-HSQC spectra of 13 C 15 N labeled ubiquitin sample. Obtained results revealed general applicability of proposed method and the significant improvement of resolution in comparison with conventional spectra recorded in the same time

A random sampling procedure for anisotropic distributions

International Nuclear Information System (INIS)

Nagrajan, P.S.; Sethulakshmi, P.; Raghavendran, C.P.; Bhatia, D.P.

1975-01-01

A procedure is described for sampling the scattering angle of neutrons as per specified angular distribution data. The cosine of the scattering angle is written as a double Legendre expansion in the incident neutron energy and a random number. The coefficients of the expansion are given for C, N, O, Si, Ca, Fe and Pb and these elements are of interest in dosimetry and shielding. (author)

A random sampling approach for robust estimation of tissue-to-plasma ratio from extremely sparse data.

Science.gov (United States)

Chu, Hui-May; Ette, Ene I

2005-09-02

his study was performed to develop a new nonparametric approach for the estimation of robust tissue-to-plasma ratio from extremely sparsely sampled paired data (ie, one sample each from plasma and tissue per subject). Tissue-to-plasma ratio was estimated from paired/unpaired experimental data using independent time points approach, area under the curve (AUC) values calculated with the naïve data averaging approach, and AUC values calculated using sampling based approaches (eg, the pseudoprofile-based bootstrap [PpbB] approach and the random sampling approach [our proposed approach]). The random sampling approach involves the use of a 2-phase algorithm. The convergence of the sampling/resampling approaches was investigated, as well as the robustness of the estimates produced by different approaches. To evaluate the latter, new data sets were generated by introducing outlier(s) into the real data set. One to 2 concentration values were inflated by 10% to 40% from their original values to produce the outliers. Tissue-to-plasma ratios computed using the independent time points approach varied between 0 and 50 across time points. The ratio obtained from AUC values acquired using the naive data averaging approach was not associated with any measure of uncertainty or variability. Calculating the ratio without regard to pairing yielded poorer estimates. The random sampling and pseudoprofile-based bootstrap approaches yielded tissue-to-plasma ratios with uncertainty and variability. However, the random sampling approach, because of the 2-phase nature of its algorithm, yielded more robust estimates and required fewer replications. Therefore, a 2-phase random sampling approach is proposed for the robust estimation of tissue-to-plasma ratio from extremely sparsely sampled data.

Influence of population versus convenience sampling on sample characteristics in studies of cognitive aging.

Science.gov (United States)

Brodaty, Henry; Mothakunnel, Annu; de Vel-Palumbo, Melissa; Ames, David; Ellis, Kathryn A; Reppermund, Simone; Kochan, Nicole A; Savage, Greg; Trollor, Julian N; Crawford, John; Sachdev, Perminder S

2014-01-01

We examined whether differences in findings of studies examining mild cognitive impairment (MCI) were associated with recruitment methods by comparing sample characteristics in two contemporaneous Australian studies, using population-based and convenience sampling. The Sydney Memory and Aging Study invited participants randomly from the electoral roll in defined geographic areas in Sydney. The Australian Imaging, Biomarkers and Lifestyle Study of Ageing recruited cognitively normal (CN) individuals via media appeals and MCI participants via referrals from clinicians in Melbourne and Perth. Demographic and cognitive variables were harmonized, and similar diagnostic criteria were applied to both samples retrospectively. CN participants recruited via convenience sampling were younger, better educated, more likely to be married and have a family history of dementia, and performed better cognitively than those recruited via population-based sampling. MCI participants recruited via population-based sampling had better memory performance and were less likely to carry the apolipoprotein E ε4 allele than clinically referred participants but did not differ on other demographic variables. A convenience sample of normal controls is likely to be younger and better functioning and that of an MCI group likely to perform worse than a purportedly random sample. Sampling bias should be considered when interpreting findings. Copyright © 2014 Elsevier Inc. All rights reserved.

Random sampling of elementary flux modes in large-scale metabolic networks.

Science.gov (United States)

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

Accounting for randomness in measurement and sampling in studying cancer cell population dynamics.

Science.gov (United States)

Ghavami, Siavash; Wolkenhauer, Olaf; Lahouti, Farshad; Ullah, Mukhtar; Linnebacher, Michael

2014-10-01

Knowing the expected temporal evolution of the proportion of different cell types in sample tissues gives an indication about the progression of the disease and its possible response to drugs. Such systems have been modelled using Markov processes. We here consider an experimentally realistic scenario in which transition probabilities are estimated from noisy cell population size measurements. Using aggregated data of FACS measurements, we develop MMSE and ML estimators and formulate two problems to find the minimum number of required samples and measurements to guarantee the accuracy of predicted population sizes. Our numerical results show that the convergence mechanism of transition probabilities and steady states differ widely from the real values if one uses the standard deterministic approach for noisy measurements. This provides support for our argument that for the analysis of FACS data one should consider the observed state as a random variable. The second problem we address is about the consequences of estimating the probability of a cell being in a particular state from measurements of small population of cells. We show how the uncertainty arising from small sample sizes can be captured by a distribution for the state probability.

STATISTICAL LANDMARKS AND PRACTICAL ISSUES REGARDING THE USE OF SIMPLE RANDOM SAMPLING IN MARKET RESEARCHES

Directory of Open Access Journals (Sweden)

CODRUŢA DURA

2010-01-01

Full Text Available The sample represents a particular segment of the statistical populationchosen to represent it as a whole. The representativeness of the sample determines the accuracyfor estimations made on the basis of calculating the research indicators and the inferentialstatistics. The method of random sampling is part of probabilistic methods which can be usedwithin marketing research and it is characterized by the fact that it imposes the requirementthat each unit belonging to the statistical population should have an equal chance of beingselected for the sampling process. When the simple random sampling is meant to be rigorouslyput into practice, it is recommended to use the technique of random number tables in order toconfigure the sample which will provide information that the marketer needs. The paper alsodetails the practical procedure implemented in order to create a sample for a marketingresearch by generating random numbers using the facilities offered by Microsoft Excel.

CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS.

Science.gov (United States)

Shalizi, Cosma Rohilla; Rinaldo, Alessandro

2013-04-01

The growing availability of network data and of scientific interest in distributed systems has led to the rapid development of statistical models of network structure. Typically, however, these are models for the entire network, while the data consists only of a sampled sub-network. Parameters for the whole network, which is what is of interest, are estimated by applying the model to the sub-network. This assumes that the model is consistent under sampling , or, in terms of the theory of stochastic processes, that it defines a projective family. Focusing on the popular class of exponential random graph models (ERGMs), we show that this apparently trivial condition is in fact violated by many popular and scientifically appealing models, and that satisfying it drastically limits ERGM's expressive power. These results are actually special cases of more general results about exponential families of dependent random variables, which we also prove. Using such results, we offer easily checked conditions for the consistency of maximum likelihood estimation in ERGMs, and discuss some possible constructive responses.

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects.

Science.gov (United States)

Dreyhaupt, Jens; Mayer, Benjamin; Keis, Oliver; Öchsner, Wolfgang; Muche, Rainer

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called "cluster randomization"). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

Sample size of the reference sample in a case-augmented study.

Science.gov (United States)

Ghosh, Palash; Dewanji, Anup

2017-05-01

The case-augmented study, in which a case sample is augmented with a reference (random) sample from the source population with only covariates information known, is becoming popular in different areas of applied science such as pharmacovigilance, ecology, and econometrics. In general, the case sample is available from some source (for example, hospital database, case registry, etc.); however, the reference sample is required to be drawn from the corresponding source population. The required minimum size of the reference sample is an important issue in this regard. In this work, we address the minimum sample size calculation and discuss related issues. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Investigating causal associations between use of nicotine, alcohol, caffeine and cannabis: a two-sample bidirectional Mendelian randomization study.

Science.gov (United States)

Verweij, Karin J H; Treur, Jorien L; Vink, Jacqueline M

2018-07-01

Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use. Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy. Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing. Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use. © 2018 Society for the Study of Addiction.

Characterization of electron microscopes with binary pseudo-random multilayer test samples

Science.gov (United States)

Yashchuk, Valeriy V.; Conley, Raymond; Anderson, Erik H.; Barber, Samuel K.; Bouet, Nathalie; McKinney, Wayne R.; Takacs, Peter Z.; Voronov, Dmitriy L.

2011-09-01

Verification of the reliability of metrology data from high quality X-ray optics requires that adequate methods for test and calibration of the instruments be developed. For such verification for optical surface profilometers in the spatial frequency domain, a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) gratings and arrays has been suggested [1,2] and proven to be an effective calibration method for a number of interferometric microscopes, a phase shifting Fizeau interferometer, and a scatterometer [5]. Here we describe the details of development of binary pseudo-random multilayer (BPRML) test samples suitable for characterization of scanning (SEM) and transmission (TEM) electron microscopes. We discuss the results of TEM measurements with the BPRML test samples fabricated from a WiSi 2/Si multilayer coating with pseudo-randomly distributed layers. In particular, we demonstrate that significant information about the metrological reliability of the TEM measurements can be extracted even when the fundamental frequency of the BPRML sample is smaller than the Nyquist frequency of the measurements. The measurements demonstrate a number of problems related to the interpretation of the SEM and TEM data. Note that similar BPRML test samples can be used to characterize X-ray microscopes. Corresponding work with X-ray microscopes is in progress.

Characterization of electron microscopes with binary pseudo-random multilayer test samples

International Nuclear Information System (INIS)

Yashchuk, Valeriy V.; Conley, Raymond; Anderson, Erik H.; Barber, Samuel K.; Bouet, Nathalie; McKinney, Wayne R.; Takacs, Peter Z.; Voronov, Dmitriy L.

2011-01-01

Verification of the reliability of metrology data from high quality X-ray optics requires that adequate methods for test and calibration of the instruments be developed. For such verification for optical surface profilometers in the spatial frequency domain, a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) gratings and arrays has been suggested and proven to be an effective calibration method for a number of interferometric microscopes, a phase shifting Fizeau interferometer, and a scatterometer [5]. Here we describe the details of development of binary pseudo-random multilayer (BPRML) test samples suitable for characterization of scanning (SEM) and transmission (TEM) electron microscopes. We discuss the results of TEM measurements with the BPRML test samples fabricated from a WiSi 2 /Si multilayer coating with pseudo-randomly distributed layers. In particular, we demonstrate that significant information about the metrological reliability of the TEM measurements can be extracted even when the fundamental frequency of the BPRML sample is smaller than the Nyquist frequency of the measurements. The measurements demonstrate a number of problems related to the interpretation of the SEM and TEM data. Note that similar BPRML test samples can be used to characterize X-ray microscopes. Corresponding work with X-ray microscopes is in progress.

Path integral methods for primordial density perturbations - sampling of constrained Gaussian random fields

International Nuclear Information System (INIS)

Bertschinger, E.

1987-01-01

Path integrals may be used to describe the statistical properties of a random field such as the primordial density perturbation field. In this framework the probability distribution is given for a Gaussian random field subjected to constraints such as the presence of a protovoid or supercluster at a specific location in the initial conditions. An algorithm has been constructed for generating samples of a constrained Gaussian random field on a lattice using Monte Carlo techniques. The method makes possible a systematic study of the density field around peaks or other constrained regions in the biased galaxy formation scenario, and it is effective for generating initial conditions for N-body simulations with rare objects in the computational volume. 21 references

Generating Random Samples of a Given Size Using Social Security Numbers.

Science.gov (United States)

Erickson, Richard C.; Brauchle, Paul E.

1984-01-01

The purposes of this article are (1) to present a method by which social security numbers may be used to draw cluster samples of a predetermined size and (2) to describe procedures used to validate this method of drawing random samples. (JOW)

Cluster-randomized Studies in Educational Research: Principles and Methodological Aspects

Directory of Open Access Journals (Sweden)

Dreyhaupt, Jens

2017-05-01

Full Text Available An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called “cluster randomization”. Compared with studies with individual randomization, studies with cluster randomization normally require (significantly larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies.Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies.

Random On-Board Pixel Sampling (ROPS) X-Ray Camera

Energy Technology Data Exchange (ETDEWEB)

Wang, Zhehui [Los Alamos; Iaroshenko, O. [Los Alamos; Li, S. [Los Alamos; Liu, T. [Fermilab; Parab, N. [Argonne (main); Chen, W. W. [Purdue U.; Chu, P. [Los Alamos; Kenyon, G. [Los Alamos; Lipton, R. [Fermilab; Sun, K.-X. [Nevada U., Las Vegas

2017-09-25

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.

Sample size estimation and sampling techniques for selecting a representative sample

Directory of Open Access Journals (Sweden)

Aamir Omair

2014-01-01

Full Text Available Introduction: The purpose of this article is to provide a general understanding of the concepts of sampling as applied to health-related research. Sample Size Estimation: It is important to select a representative sample in quantitative research in order to be able to generalize the results to the target population. The sample should be of the required sample size and must be selected using an appropriate probability sampling technique. There are many hidden biases which can adversely affect the outcome of the study. Important factors to consider for estimating the sample size include the size of the study population, confidence level, expected proportion of the outcome variable (for categorical variables/standard deviation of the outcome variable (for numerical variables, and the required precision (margin of accuracy from the study. The more the precision required, the greater is the required sample size. Sampling Techniques: The probability sampling techniques applied for health related research include simple random sampling, systematic random sampling, stratified random sampling, cluster sampling, and multistage sampling. These are more recommended than the nonprobability sampling techniques, because the results of the study can be generalized to the target population.

Precision of systematic and random sampling in clustered populations: habitat patches and aggregating organisms.

Science.gov (United States)

McGarvey, Richard; Burch, Paul; Matthews, Janet M

2016-01-01

Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν₈ and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν₂ and ν₃) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with

Developing Sampling Frame for Case Study: Challenges and Conditions

Science.gov (United States)

Ishak, Noriah Mohd; Abu Bakar, Abu Yazid

2014-01-01

Due to statistical analysis, the issue of random sampling is pertinent to any quantitative study. Unlike quantitative study, the elimination of inferential statistical analysis, allows qualitative researchers to be more creative in dealing with sampling issue. Since results from qualitative study cannot be generalized to the bigger population,…

Smoothing the redshift distributions of random samples for the baryon acoustic oscillations: applications to the SDSS-III BOSS DR12 and QPM mock samples

Science.gov (United States)

Wang, Shao-Jiang; Guo, Qi; Cai, Rong-Gen

2017-12-01

We investigate the impact of different redshift distributions of random samples on the baryon acoustic oscillations (BAO) measurements of D_V(z)r_d^fid/r_d from the two-point correlation functions of galaxies in the Data Release 12 of the Baryon Oscillation Spectroscopic Survey (BOSS). Big surveys, such as BOSS, usually assign redshifts to the random samples by randomly drawing values from the measured redshift distributions of the data, which would necessarily introduce fiducial signals of fluctuations into the random samples, weakening the signals of BAO, if the cosmic variance cannot be ignored. We propose a smooth function of redshift distribution that fits the data well to populate the random galaxy samples. The resulting cosmological parameters match the input parameters of the mock catalogue very well. The significance of BAO signals has been improved by 0.33σ for a low-redshift sample and by 0.03σ for a constant-stellar-mass sample, though the absolute values do not change significantly. Given the precision of the measurements of current cosmological parameters, it would be appreciated for the future improvements on the measurements of galaxy clustering.

Comparison of Address-based Sampling and Random-digit Dialing Methods for Recruiting Young Men as Controls in a Case-Control Study of Testicular Cancer Susceptibility

OpenAIRE

Clagett, Bartholt; Nathanson, Katherine L.; Ciosek, Stephanie L.; McDermoth, Monique; Vaughn, David J.; Mitra, Nandita; Weiss, Andrew; Martonik, Rachel; Kanetsky, Peter A.

2013-01-01

Random-digit dialing (RDD) using landline telephone numbers is the historical gold standard for control recruitment in population-based epidemiologic research. However, increasing cell-phone usage and diminishing response rates suggest that the effectiveness of RDD in recruiting a random sample of the general population, particularly for younger target populations, is decreasing. In this study, we compared landline RDD with alternative methods of control recruitment, including RDD using cell-...

Sampling pig farms at the abattoir in a cross-sectional study - Evaluation of a sampling method.

Science.gov (United States)

Birkegård, Anna Camilla; Halasa, Tariq; Toft, Nils

2017-09-15

A cross-sectional study design is relatively inexpensive, fast and easy to conduct when compared to other study designs. Careful planning is essential to obtaining a representative sample of the population, and the recommended approach is to use simple random sampling from an exhaustive list of units in the target population. This approach is rarely feasible in practice, and other sampling procedures must often be adopted. For example, when slaughter pigs are the target population, sampling the pigs on the slaughter line may be an alternative to on-site sampling at a list of farms. However, it is difficult to sample a large number of farms from an exact predefined list, due to the logistics and workflow of an abattoir. Therefore, it is necessary to have a systematic sampling procedure and to evaluate the obtained sample with respect to the study objective. We propose a method for 1) planning, 2) conducting, and 3) evaluating the representativeness and reproducibility of a cross-sectional study when simple random sampling is not possible. We used an example of a cross-sectional study with the aim of quantifying the association of antimicrobial resistance and antimicrobial consumption in Danish slaughter pigs. It was not possible to visit farms within the designated timeframe. Therefore, it was decided to use convenience sampling at the abattoir. Our approach was carried out in three steps: 1) planning: using data from meat inspection to plan at which abattoirs and how many farms to sample; 2) conducting: sampling was carried out at five abattoirs; 3) evaluation: representativeness was evaluated by comparing sampled and non-sampled farms, and the reproducibility of the study was assessed through simulated sampling based on meat inspection data from the period where the actual data collection was carried out. In the cross-sectional study samples were taken from 681 Danish pig farms, during five weeks from February to March 2015. The evaluation showed that the sampling

40 CFR 761.308 - Sample selection by random number generation on any two-dimensional square grid.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sample selection by random number... § 761.79(b)(3) § 761.308 Sample selection by random number generation on any two-dimensional square... area created in accordance with paragraph (a) of this section, select two random numbers: one each for...

Random-Number Generator Validity in Simulation Studies: An Investigation of Normality.

Science.gov (United States)

Bang, Jung W.; Schumacker, Randall E.; Schlieve, Paul L.

1998-01-01

The normality of number distributions generated by various random-number generators were studied, focusing on when the random-number generator reached a normal distribution and at what sample size. Findings suggest the steps that should be followed when using a random-number generator in a Monte Carlo simulation. (SLD)

A simple and efficient alternative to implementing systematic random sampling in stereological designs without a motorized microscope stage.

Science.gov (United States)

Melvin, Neal R; Poda, Daniel; Sutherland, Robert J

2007-10-01

When properly applied, stereology is a very robust and efficient method to quantify a variety of parameters from biological material. A common sampling strategy in stereology is systematic random sampling, which involves choosing a random sampling [corrected] start point outside the structure of interest, and sampling relevant objects at [corrected] sites that are placed at pre-determined, equidistant intervals. This has proven to be a very efficient sampling strategy, and is used widely in stereological designs. At the microscopic level, this is most often achieved through the use of a motorized stage that facilitates the systematic random stepping across the structure of interest. Here, we report a simple, precise and cost-effective software-based alternative to accomplishing systematic random sampling under the microscope. We believe that this approach will facilitate the use of stereological designs that employ systematic random sampling in laboratories that lack the resources to acquire costly, fully automated systems.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

Science.gov (United States)

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

Random Sampling of Correlated Parameters – a Consistent Solution for Unfavourable Conditions

Energy Technology Data Exchange (ETDEWEB)

Žerovnik, G., E-mail: gasper.zerovnik@ijs.si [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Trkov, A. [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); International Atomic Energy Agency, PO Box 100, A-1400 Vienna (Austria); Kodeli, I.A. [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Capote, R. [International Atomic Energy Agency, PO Box 100, A-1400 Vienna (Austria); Smith, D.L. [Argonne National Laboratory, 1710 Avenida del Mundo, Coronado, CA 92118-3073 (United States)

2015-01-15

Two methods for random sampling according to a multivariate lognormal distribution – the correlated sampling method and the method of transformation of correlation coefficients – are briefly presented. The methods are mathematically exact and enable consistent sampling of correlated inherently positive parameters with given information on the first two distribution moments. Furthermore, a weighted sampling method to accelerate the convergence of parameters with extremely large relative uncertainties is described. However, the method is efficient only for a limited number of correlated parameters.

The Bootstrap, the Jackknife, and the Randomization Test: A Sampling Taxonomy.

Science.gov (United States)

Rodgers, J L

1999-10-01

A simple sampling taxonomy is defined that shows the differences between and relationships among the bootstrap, the jackknife, and the randomization test. Each method has as its goal the creation of an empirical sampling distribution that can be used to test statistical hypotheses, estimate standard errors, and/or create confidence intervals. Distinctions between the methods can be made based on the sampling approach (with replacement versus without replacement) and the sample size (replacing the whole original sample versus replacing a subset of the original sample). The taxonomy is useful for teaching the goals and purposes of resampling schemes. An extension of the taxonomy implies other possible resampling approaches that have not previously been considered. Univariate and multivariate examples are presented.

Survey research with a random digit dial national mobile phone sample in Ghana: Methods and sample quality

Science.gov (United States)

Sefa, Eunice; Adimazoya, Edward Akolgo; Yartey, Emmanuel; Lenzi, Rachel; Tarpo, Cindy; Heward-Mills, Nii Lante; Lew, Katherine; Ampeh, Yvonne

2018-01-01

Introduction Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample. Materials and methods The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census. Results The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample. Conclusions The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in

Survey research with a random digit dial national mobile phone sample in Ghana: Methods and sample quality.

Science.gov (United States)

L'Engle, Kelly; Sefa, Eunice; Adimazoya, Edward Akolgo; Yartey, Emmanuel; Lenzi, Rachel; Tarpo, Cindy; Heward-Mills, Nii Lante; Lew, Katherine; Ampeh, Yvonne

2018-01-01

Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample. The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census. The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample. The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in comparison to household surveys. Random digit dialing of mobile

Survey research with a random digit dial national mobile phone sample in Ghana: Methods and sample quality.

Directory of Open Access Journals (Sweden)

Kelly L'Engle

Full Text Available Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample.The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census.The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample.The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in comparison to household surveys. Random digit

Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

Energy Technology Data Exchange (ETDEWEB)

Romero, Vicente [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bonney, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Schroeder, Benjamin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weirs, V. Gregory [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-11-01

When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a class of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10^-4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.

Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets

International Nuclear Information System (INIS)

Stanek, Jan; Kozminski, Wiktor

2010-01-01

Spectra obtained by application of multidimensional Fourier Transformation (MFT) to sparsely sampled nD NMR signals are usually corrupted due to missing data. In the present paper this phenomenon is investigated on simulations and experiments. An effective iterative algorithm for artifact suppression for sparse on-grid NMR data sets is discussed in detail. It includes automated peak recognition based on statistical methods. The results enable one to study NMR spectra of high dynamic range of peak intensities preserving benefits of random sampling, namely the superior resolution in indirectly measured dimensions. Experimental examples include 3D 15 N- and 13 C-edited NOESY-HSQC spectra of human ubiquitin.

Effects of psychological therapies in randomized trials and practice-based studies.

Science.gov (United States)

Barkham, Michael; Stiles, William B; Connell, Janice; Twigg, Elspeth; Leach, Chris; Lucock, Mike; Mellor-Clark, John; Bower, Peter; King, Michael; Shapiro, David A; Hardy, Gillian E; Greenberg, Leslie; Angus, Lynne

2008-11-01

Randomized trials of the effects of psychological therapies seek internal validity via homogeneous samples and standardized treatment protocols. In contrast, practice-based studies aim for clinical realism and external validity via heterogeneous samples of clients treated under routine practice conditions. We compared indices of treatment effects in these two types of studies. Using published transformation formulas, the Beck Depression Inventory (BDI) scores from five randomized trials of depression (N = 477 clients) were transformed into Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) scores and compared with CORE-OM data collected in four practice-based studies (N = 4,196 clients). Conversely, the practice-based studies' CORE-OM scores were transformed into BDI scores and compared with randomized trial data. Randomized trials showed a modest advantage over practice-based studies in amount of pre-post improvement. This difference was compressed or exaggerated depending on the direction of the transformation but averaged about 12%. There was a similarly sized advantage to randomized trials in rates of reliable and clinically significant improvement (RCSI). The largest difference was yielded by comparisons of effect sizes which suggested an advantage more than twice as large, reflecting narrower pre-treatment distributions in the randomized trials. Outcomes of completed treatments for depression in randomized trials appeared to be modestly greater than those in routine care settings. The size of the difference may be distorted depending on the method for calculating degree of change. Transforming BDI scores into CORE-OM scores and vice versa may be a preferable alternative to effect sizes for comparisons of studies using these measures.

Estimation of Sensitive Proportion by Randomized Response Data in Successive Sampling

Directory of Open Access Journals (Sweden)

Bo Yu

2015-01-01

Full Text Available This paper considers the problem of estimation for binomial proportions of sensitive or stigmatizing attributes in the population of interest. Randomized response techniques are suggested for protecting the privacy of respondents and reducing the response bias while eliciting information on sensitive attributes. In many sensitive question surveys, the same population is often sampled repeatedly on each occasion. In this paper, we apply successive sampling scheme to improve the estimation of the sensitive proportion on current occasion.

Adaptive importance sampling of random walks on continuous state spaces

International Nuclear Information System (INIS)

Baggerly, K.; Cox, D.; Picard, R.

1998-01-01

The authors consider adaptive importance sampling for a random walk with scoring in a general state space. Conditions under which exponential convergence occurs to the zero-variance solution are reviewed. These results generalize previous work for finite, discrete state spaces in Kollman (1993) and in Kollman, Baggerly, Cox, and Picard (1996). This paper is intended for nonstatisticians and includes considerable explanatory material

Random-effects linear modeling and sample size tables for two special crossover designs of average bioequivalence studies: the four-period, two-sequence, two-formulation and six-period, three-sequence, three-formulation designs.

Science.gov (United States)

Diaz, Francisco J; Berg, Michel J; Krebill, Ron; Welty, Timothy; Gidal, Barry E; Alloway, Rita; Privitera, Michael

2013-12-01

Due to concern and debate in the epilepsy medical community and to the current interest of the US Food and Drug Administration (FDA) in revising approaches to the approval of generic drugs, the FDA is currently supporting ongoing bioequivalence studies of antiepileptic drugs, the EQUIGEN studies. During the design of these crossover studies, the researchers could not find commercial or non-commercial statistical software that quickly allowed computation of sample sizes for their designs, particularly software implementing the FDA requirement of using random-effects linear models for the analyses of bioequivalence studies. This article presents tables for sample-size evaluations of average bioequivalence studies based on the two crossover designs used in the EQUIGEN studies: the four-period, two-sequence, two-formulation design, and the six-period, three-sequence, three-formulation design. Sample-size computations assume that random-effects linear models are used in bioequivalence analyses with crossover designs. Random-effects linear models have been traditionally viewed by many pharmacologists and clinical researchers as just mathematical devices to analyze repeated-measures data. In contrast, a modern view of these models attributes an important mathematical role in theoretical formulations in personalized medicine to them, because these models not only have parameters that represent average patients, but also have parameters that represent individual patients. Moreover, the notation and language of random-effects linear models have evolved over the years. Thus, another goal of this article is to provide a presentation of the statistical modeling of data from bioequivalence studies that highlights the modern view of these models, with special emphasis on power analyses and sample-size computations.

Comparison of address-based sampling and random-digit dialing methods for recruiting young men as controls in a case-control study of testicular cancer susceptibility.

Science.gov (United States)

Clagett, Bartholt; Nathanson, Katherine L; Ciosek, Stephanie L; McDermoth, Monique; Vaughn, David J; Mitra, Nandita; Weiss, Andrew; Martonik, Rachel; Kanetsky, Peter A

2013-12-01

Random-digit dialing (RDD) using landline telephone numbers is the historical gold standard for control recruitment in population-based epidemiologic research. However, increasing cell-phone usage and diminishing response rates suggest that the effectiveness of RDD in recruiting a random sample of the general population, particularly for younger target populations, is decreasing. In this study, we compared landline RDD with alternative methods of control recruitment, including RDD using cell-phone numbers and address-based sampling (ABS), to recruit primarily white men aged 18-55 years into a study of testicular cancer susceptibility conducted in the Philadelphia, Pennsylvania, metropolitan area between 2009 and 2012. With few exceptions, eligible and enrolled controls recruited by means of RDD and ABS were similar with regard to characteristics for which data were collected on the screening survey. While we find ABS to be a comparably effective method of recruiting young males compared with landline RDD, we acknowledge the potential impact that selection bias may have had on our results because of poor overall response rates, which ranged from 11.4% for landline RDD to 1.7% for ABS.

Generalizability of causal inference in observational studies under retrospective convenience sampling.

Science.gov (United States)

Hu, Zonghui; Qin, Jing

2018-05-20

Many observational studies adopt what we call retrospective convenience sampling (RCS). With the sample size in each arm prespecified, RCS randomly selects subjects from the treatment-inclined subpopulation into the treatment arm and those from the control-inclined into the control arm. Samples in each arm are representative of the respective subpopulation, but the proportion of the 2 subpopulations is usually not preserved in the sample data. We show in this work that, under RCS, existing causal effect estimators actually estimate the treatment effect over the sample population instead of the underlying study population. We investigate how to correct existing methods for consistent estimation of the treatment effect over the underlying population. Although RCS is adopted in medical studies for ethical and cost-effective purposes, it also has a big advantage for statistical inference: When the tendency to receive treatment is low in a study population, treatment effect estimators under RCS, with proper correction, are more efficient than their parallels under random sampling. These properties are investigated both theoretically and through numerical demonstration. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

A Table-Based Random Sampling Simulation for Bioluminescence Tomography

Directory of Open Access Journals (Sweden)

Xiaomeng Zhang

2006-01-01

Full Text Available As a popular simulation of photon propagation in turbid media, the main problem of Monte Carlo (MC method is its cumbersome computation. In this work a table-based random sampling simulation (TBRS is proposed. The key idea of TBRS is to simplify multisteps of scattering to a single-step process, through randomly table querying, thus greatly reducing the computing complexity of the conventional MC algorithm and expediting the computation. The TBRS simulation is a fast algorithm of the conventional MC simulation of photon propagation. It retained the merits of flexibility and accuracy of conventional MC method and adapted well to complex geometric media and various source shapes. Both MC simulations were conducted in a homogeneous medium in our work. Also, we present a reconstructing approach to estimate the position of the fluorescent source based on the trial-and-error theory as a validation of the TBRS algorithm. Good agreement is found between the conventional MC simulation and the TBRS simulation.

A Systematic Review of Surgical Randomized Controlled Trials: Part 2. Funding Source, Conflict of Interest, and Sample Size in Plastic Surgery.

Science.gov (United States)

Voineskos, Sophocles H; Coroneos, Christopher J; Ziolkowski, Natalia I; Kaur, Manraj N; Banfield, Laura; Meade, Maureen O; Chung, Kevin C; Thoma, Achilleas; Bhandari, Mohit

2016-02-01

The authors examined industry support, conflict of interest, and sample size in plastic surgery randomized controlled trials that compared surgical interventions. They hypothesized that industry-funded trials demonstrate statistically significant outcomes more often, and randomized controlled trials with small sample sizes report statistically significant results more frequently. An electronic search identified randomized controlled trials published between 2000 and 2013. Independent reviewers assessed manuscripts and performed data extraction. Funding source, conflict of interest, primary outcome direction, and sample size were examined. Chi-squared and independent-samples t tests were used in the analysis. The search identified 173 randomized controlled trials, of which 100 (58 percent) did not acknowledge funding status. A relationship between funding source and trial outcome direction was not observed. Both funding status and conflict of interest reporting improved over time. Only 24 percent (six of 25) of industry-funded randomized controlled trials reported authors to have independent control of data and manuscript contents. The mean number of patients randomized was 73 per trial (median, 43, minimum, 3, maximum, 936). Small trials were not found to be positive more often than large trials (p = 0.87). Randomized controlled trials with small sample size were common; however, this provides great opportunity for the field to engage in further collaboration and produce larger, more definitive trials. Reporting of trial funding and conflict of interest is historically poor, but it greatly improved over the study period. Underreporting at author and journal levels remains a limitation when assessing the relationship between funding source and trial outcomes. Improved reporting and manuscript control should be goals that both authors and journals can actively achieve.

40 CFR 761.306 - Sampling 1 meter square surfaces by random selection of halves.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Sampling 1 meter square surfaces by...(b)(3) § 761.306 Sampling 1 meter square surfaces by random selection of halves. (a) Divide each 1 meter square portion where it is necessary to collect a surface wipe test sample into two equal (or as...

A Nationwide Random Sampling Survey of Potential Complicated Grief in Japan

Science.gov (United States)

Mizuno, Yasunao; Kishimoto, Junji; Asukai, Nozomu

2012-01-01

To investigate the prevalence of significant loss, potential complicated grief (CG), and its contributing factors, we conducted a nationwide random sampling survey of Japanese adults aged 18 or older (N = 1,343) using a self-rating Japanese-language version of the Complicated Grief Brief Screen. Among them, 37.0% experienced their most significant…

Reinforcing Sampling Distributions through a Randomization-Based Activity for Introducing ANOVA

Science.gov (United States)

Taylor, Laura; Doehler, Kirsten

2015-01-01

This paper examines the use of a randomization-based activity to introduce the ANOVA F-test to students. The two main goals of this activity are to successfully teach students to comprehend ANOVA F-tests and to increase student comprehension of sampling distributions. Four sections of students in an advanced introductory statistics course…

Randomization tests

CERN Document Server

Edgington, Eugene

2007-01-01

Statistical Tests That Do Not Require Random Sampling Randomization Tests Numerical Examples Randomization Tests and Nonrandom Samples The Prevalence of Nonrandom Samples in Experiments The Irrelevance of Random Samples for the Typical Experiment Generalizing from Nonrandom Samples Intelligibility Respect for the Validity of Randomization Tests Versatility Practicality Precursors of Randomization Tests Other Applications of Permutation Tests Questions and Exercises Notes References Randomized Experiments Unique Benefits of Experiments Experimentation without Mani

Work Sampling Study of an Engineering Professor during a Regular Contract Period

Science.gov (United States)

Brink, Jan; McDonald, Dale B.

2015-01-01

Work sampling is a technique that has been employed in industry and fields such as healthcare for some time. It is a powerful technique, and an alternative to conventional stop watch time studies, used by industrial engineers to focus upon random work sampling observations. This study applies work sampling to the duties performed by an individual…

LOD score exclusion analyses for candidate QTLs using random population samples.

Science.gov (United States)

Deng, Hong-Wen

2003-11-01

While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes as putative QTLs using random population samples. Previously, we developed an LOD score exclusion mapping approach for candidate genes for complex diseases. Here, we extend this LOD score approach for exclusion analyses of candidate genes for quantitative traits. Under this approach, specific genetic effects (as reflected by heritability) and inheritance models at candidate QTLs can be analyzed and if an LOD score is < or = -2.0, the locus can be excluded from having a heritability larger than that specified. Simulations show that this approach has high power to exclude a candidate gene from having moderate genetic effects if it is not a QTL and is robust to population admixture. Our exclusion analysis complements association analysis for candidate genes as putative QTLs in random population samples. The approach is applied to test the importance of Vitamin D receptor (VDR) gene as a potential QTL underlying the variation of bone mass, an important determinant of osteoporosis.

The Dirichet-Multinomial model for multivariate randomized response data and small samples

NARCIS (Netherlands)

Avetisyan, Marianna; Fox, Gerardus J.A.

2012-01-01

In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The

Prevalence and correlates of problematic smartphone use in a large random sample of Chinese undergraduates.

Science.gov (United States)

Long, Jiang; Liu, Tie-Qiao; Liao, Yan-Hui; Qi, Chang; He, Hao-Yu; Chen, Shu-Bao; Billieux, Joël

2016-11-17

Smartphones are becoming a daily necessity for most undergraduates in Mainland China. Because the present scenario of problematic smartphone use (PSU) is largely unexplored, in the current study we aimed to estimate the prevalence of PSU and to screen suitable predictors for PSU among Chinese undergraduates in the framework of the stress-coping theory. A sample of 1062 undergraduate smartphone users was recruited by means of the stratified cluster random sampling strategy between April and May 2015. The Problematic Cellular Phone Use Questionnaire was used to identify PSU. We evaluated five candidate risk factors for PSU by using logistic regression analysis while controlling for demographic characteristics and specific features of smartphone use. The prevalence of PSU among Chinese undergraduates was estimated to be 21.3%. The risk factors for PSU were majoring in the humanities, high monthly income from the family (≥1500 RMB), serious emotional symptoms, high perceived stress, and perfectionism-related factors (high doubts about actions, high parental expectations). PSU among undergraduates appears to be ubiquitous and thus constitutes a public health issue in Mainland China. Although further longitudinal studies are required to test whether PSU is a transient phenomenon or a chronic and progressive condition, our study successfully identified socio-demographic and psychological risk factors for PSU. These results, obtained from a random and thus representative sample of undergraduates, opens up new avenues in terms of prevention and regulation policies.

Tobacco smoking surveillance: is quota sampling an efficient tool for monitoring national trends? A comparison with a random cross-sectional survey.

Directory of Open Access Journals (Sweden)

Romain Guignard

Full Text Available OBJECTIVES: It is crucial for policy makers to monitor the evolution of tobacco smoking prevalence. In France, this monitoring is based on a series of cross-sectional general population surveys, the Health Barometers, conducted every five years and based on random samples. A methodological study has been carried out to assess the reliability of a monitoring system based on regular quota sampling surveys for smoking prevalence. DESIGN / OUTCOME MEASURES: In 2010, current and daily tobacco smoking prevalences obtained in a quota survey on 8,018 people were compared with those of the 2010 Health Barometer carried out on 27,653 people. Prevalences were assessed separately according to the telephone equipment of the interviewee (landline phone owner vs "mobile-only", and logistic regressions were conducted in the pooled database to assess the impact of the telephone equipment and of the survey mode on the prevalences found. Finally, logistic regressions adjusted for sociodemographic characteristics were conducted in the random sample in order to determine the impact of the needed number of calls to interwiew "hard-to-reach" people on the prevalence found. RESULTS: Current and daily prevalences were higher in the random sample (respectively 33.9% and 27.5% in 15-75 years-old than in the quota sample (respectively 30.2% and 25.3%. In both surveys, current and daily prevalences were lower among landline phone owners (respectively 31.8% and 25.5% in the random sample and 28.9% and 24.0% in the quota survey. The required number of calls was slightly related to the smoking status after adjustment for sociodemographic characteristics. CONCLUSION: Random sampling appears to be more effective than quota sampling, mainly by making it possible to interview hard-to-reach populations.

Application of random effects to the study of resource selection by animals.

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Gillies, Cameron S; Hebblewhite, Mark; Nielsen, Scott E; Krawchuk, Meg A; Aldridge, Cameron L; Frair, Jacqueline L; Saher, D Joanne; Stevens, Cameron E; Jerde, Christopher L

2006-07-01

1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions

Revisiting random walk based sampling in networks: evasion of burn-in period and frequent regenerations.

Science.gov (United States)

Avrachenkov, Konstantin; Borkar, Vivek S; Kadavankandy, Arun; Sreedharan, Jithin K

2018-01-01

In the framework of network sampling, random walk (RW) based estimation techniques provide many pragmatic solutions while uncovering the unknown network as little as possible. Despite several theoretical advances in this area, RW based sampling techniques usually make a strong assumption that the samples are in stationary regime, and hence are impelled to leave out the samples collected during the burn-in period. This work proposes two sampling schemes without burn-in time constraint to estimate the average of an arbitrary function defined on the network nodes, for example, the average age of users in a social network. The central idea of the algorithms lies in exploiting regeneration of RWs at revisits to an aggregated super-node or to a set of nodes, and in strategies to enhance the frequency of such regenerations either by contracting the graph or by making the hitting set larger. Our first algorithm, which is based on reinforcement learning (RL), uses stochastic approximation to derive an estimator. This method can be seen as intermediate between purely stochastic Markov chain Monte Carlo iterations and deterministic relative value iterations. The second algorithm, which we call the Ratio with Tours (RT)-estimator, is a modified form of respondent-driven sampling (RDS) that accommodates the idea of regeneration. We study the methods via simulations on real networks. We observe that the trajectories of RL-estimator are much more stable than those of standard random walk based estimation procedures, and its error performance is comparable to that of respondent-driven sampling (RDS) which has a smaller asymptotic variance than many other estimators. Simulation studies also show that the mean squared error of RT-estimator decays much faster than that of RDS with time. The newly developed RW based estimators (RL- and RT-estimators) allow to avoid burn-in period, provide better control of stability along the sample path, and overall reduce the estimation time. Our

Additive non-uniform random sampling in superimposed fiber Bragg grating strain gauge

Science.gov (United States)

Ma, Y. C.; Liu, H. Y.; Yan, S. B.; Yang, Y. H.; Yang, M. W.; Li, J. M.; Tang, J.

2013-05-01

This paper demonstrates an additive non-uniform random sampling and interrogation method for dynamic and/or static strain gauge using a reflection spectrum from two superimposed fiber Bragg gratings (FBGs). The superimposed FBGs are designed to generate non-equidistant space of a sensing pulse train in the time domain during dynamic strain gauge. By combining centroid finding with smooth filtering methods, both the interrogation speed and accuracy are improved. A 1.9 kHz dynamic strain is measured by generating an additive non-uniform randomly distributed 2 kHz optical sensing pulse train from a mean 500 Hz triangular periodically changing scanning frequency.

An efficient method of randomly sampling the coherent angular scatter distribution

International Nuclear Information System (INIS)

Williamson, J.F.; Morin, R.L.

1983-01-01

Monte Carlo simulations of photon transport phenomena require random selection of an interaction process at each collision site along the photon track. Possible choices are usually limited to photoelectric absorption and incoherent scatter as approximated by the Klein-Nishina distribution. A technique is described for sampling the coherent angular scatter distribution, for the benefit of workers in medical physics. (U.K.)

Random vs. systematic sampling from administrative databases involving human subjects.

Science.gov (United States)

Hagino, C; Lo, R J

1998-09-01

Two sampling techniques, simple random sampling (SRS) and systematic sampling (SS), were compared to determine whether they yield similar and accurate distributions for the following four factors: age, gender, geographic location and years in practice. Any point estimate within 7 yr or 7 percentage points of its reference standard (SRS or the entire data set, i.e., the target population) was considered "acceptably similar" to the reference standard. The sampling frame was from the entire membership database of the Canadian Chiropractic Association. The two sampling methods were tested using eight different sample sizes of n (50, 100, 150, 200, 250, 300, 500, 800). From the profile/characteristics, summaries of four known factors [gender, average age, number (%) of chiropractors in each province and years in practice], between- and within-methods chi 2 tests and unpaired t tests were performed to determine whether any of the differences [descriptively greater than 7% or 7 yr] were also statistically significant. The strengths of the agreements between the provincial distributions were quantified by calculating the percent agreements for each (provincial pairwise-comparison methods). Any percent agreement less than 70% was judged to be unacceptable. Our assessments of the two sampling methods (SRS and SS) for the different sample sizes tested suggest that SRS and SS yielded acceptably similar results. Both methods started to yield "correct" sample profiles at approximately the same sample size (n > 200). SS is not only convenient, it can be recommended for sampling from large databases in which the data are listed without any inherent order biases other than alphabetical listing by surname.

Biological Sampling Variability Study

Energy Technology Data Exchange (ETDEWEB)

Amidan, Brett G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hutchison, Janine R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2016-11-08

There are many sources of variability that exist in the sample collection and analysis process. This paper addresses many, but not all, sources of variability. The main focus of this paper was to better understand and estimate variability due to differences between samplers. Variability between days was also studied, as well as random variability within each sampler. Experiments were performed using multiple surface materials (ceramic and stainless steel), multiple contaminant concentrations (10 spores and 100 spores), and with and without the presence of interfering material. All testing was done with sponge sticks using 10-inch by 10-inch coupons. Bacillus atrophaeus was used as the BA surrogate. Spores were deposited using wet deposition. Grime was coated on the coupons which were planned to include the interfering material (Section 3.3). Samples were prepared and analyzed at PNNL using CDC protocol (Section 3.4) and then cultured and counted. Five samplers were trained so that samples were taken using the same protocol. Each sampler randomly sampled eight coupons each day, four coupons with 10 spores deposited and four coupons with 100 spores deposited. Each day consisted of one material being tested. The clean samples (no interfering materials) were run first, followed by the dirty samples (coated with interfering material). There was a significant difference in recovery efficiency between the coupons with 10 spores deposited (mean of 48.9%) and those with 100 spores deposited (mean of 59.8%). There was no general significant difference between the clean and dirty (containing interfering material) coupons or between the two surface materials; however, there was a significant interaction between concentration amount and presence of interfering material. The recovery efficiency was close to the same for coupons with 10 spores deposited, but for the coupons with 100 spores deposited, the recovery efficiency for the dirty samples was significantly larger (65

Methodology Series Module 5: Sampling Strategies.

Science.gov (United States)

Setia, Maninder Singh

2016-01-01

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ' Sampling Method'. There are essentially two types of sampling methods: 1) probability sampling - based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling - based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term ' random sample' when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the ' generalizability' of these results. In such a scenario, the researcher may want to use ' purposive sampling' for the study.

Methodology series module 5: Sampling strategies

Directory of Open Access Journals (Sweden)

Maninder Singh Setia

2016-01-01

Full Text Available Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the 'Sampling Method'. There are essentially two types of sampling methods: 1 probability sampling – based on chance events (such as random numbers, flipping a coin etc.; and 2 non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term 'random sample' when the researcher has used convenience sample. The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the 'generalizability' of these results. In such a scenario, the researcher may want to use 'purposive sampling' for the study.

Fixed-location hydroacoustic monitoring designs for estimating fish passage using stratified random and systematic sampling

International Nuclear Information System (INIS)

Skalski, J.R.; Hoffman, A.; Ransom, B.H.; Steig, T.W.

1993-01-01

Five alternate sampling designs are compared using 15 d of 24-h continuous hydroacoustic data to identify the most favorable approach to fixed-location hydroacoustic monitoring of salmonid outmigrants. Four alternative aproaches to systematic sampling are compared among themselves and with stratified random sampling (STRS). Stratifying systematic sampling (STSYS) on a daily basis is found to reduce sampling error in multiday monitoring studies. Although sampling precision was predictable with varying levels of effort in STRS, neither magnitude nor direction of change in precision was predictable when effort was varied in systematic sampling (SYS). Furthermore, modifying systematic sampling to include replicated (e.g., nested) sampling (RSYS) is further shown to provide unbiased point and variance estimates as does STRS. Numerous short sampling intervals (e.g., 12 samples of 1-min duration per hour) must be monitored hourly using RSYS to provide efficient, unbiased point and interval estimates. For equal levels of effort, STRS outperformed all variations of SYS examined. Parametric approaches to confidence interval estimates are found to be superior to nonparametric interval estimates (i.e., bootstrap and jackknife) in estimating total fish passage. 10 refs., 1 fig., 8 tabs

Methodology Series Module 5: Sampling Strategies

Science.gov (United States)

Setia, Maninder Singh

2016-01-01

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ‘ Sampling Method’. There are essentially two types of sampling methods: 1) probability sampling – based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling – based on researcher's choice, population that accessible & available. Some of the non-probability sampling methods are: purposive sampling, convenience sampling, or quota sampling. Random sampling method (such as simple random sample or stratified random sample) is a form of probability sampling. It is important to understand the different sampling methods used in clinical studies and mention this method clearly in the manuscript. The researcher should not misrepresent the sampling method in the manuscript (such as using the term ‘ random sample’ when the researcher has used convenience sample). The sampling method will depend on the research question. For instance, the researcher may want to understand an issue in greater detail for one particular population rather than worry about the ‘ generalizability’ of these results. In such a scenario, the researcher may want to use ‘ purposive sampling’ for the study. PMID:27688438

Additive non-uniform random sampling in superimposed fiber Bragg grating strain gauge

International Nuclear Information System (INIS)

Ma, Y C; Liu, H Y; Yan, S B; Li, J M; Tang, J; Yang, Y H; Yang, M W

2013-01-01

This paper demonstrates an additive non-uniform random sampling and interrogation method for dynamic and/or static strain gauge using a reflection spectrum from two superimposed fiber Bragg gratings (FBGs). The superimposed FBGs are designed to generate non-equidistant space of a sensing pulse train in the time domain during dynamic strain gauge. By combining centroid finding with smooth filtering methods, both the interrogation speed and accuracy are improved. A 1.9 kHz dynamic strain is measured by generating an additive non-uniform randomly distributed 2 kHz optical sensing pulse train from a mean 500 Hz triangular periodically changing scanning frequency. (paper)

The Dirichlet-Multinomial Model for Multivariate Randomized Response Data and Small Samples

Science.gov (United States)

Avetisyan, Marianna; Fox, Jean-Paul

2012-01-01

In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized…

Sampling pig farms at the abattoir in a cross-sectional study − Evaluation of a sampling method

DEFF Research Database (Denmark)

Birkegård, Anna Camilla; Hisham Beshara Halasa, Tariq; Toft, Nils

2017-01-01

slaughter pigs. It was not possible to visit farms within the designated timeframe. Therefore, it was decided to use convenience sampling at the abattoir. Our approach was carried out in three steps: 1) planning: using data from meat inspection to plan at which abattoirs and how many farms to sample; 2......A cross-sectional study design is relatively inexpensive, fast and easy to conduct when compared to other study designs. Careful planning is essential to obtaining a representative sample of the population, and the recommended approach is to use simple random sampling from an exhaustive list...... of units in the target population. This approach is rarely feasible in practice, and other sampling procedures must often be adopted. For example, when slaughter pigs are the target population, sampling the pigs on the slaughter line may be an alternative to on-site sampling at a list of farms. However...

At convenience and systematic random sampling: effects on the prognostic value of nuclear area assessments in breast cancer patients.

Science.gov (United States)

Jannink, I; Bennen, J N; Blaauw, J; van Diest, P J; Baak, J P

1995-01-01

This study compares the influence of two different nuclear sampling methods on the prognostic value of assessments of mean and standard deviation of nuclear area (MNA, SDNA) in 191 consecutive invasive breast cancer patients with long term follow up. The first sampling method used was 'at convenience' sampling (ACS); the second, systematic random sampling (SRS). Both sampling methods were tested with a sample size of 50 nuclei (ACS-50 and SRS-50). To determine whether, besides the sampling methods, sample size had impact on prognostic value as well, the SRS method was also tested using a sample size of 100 nuclei (SRS-100). SDNA values were systematically lower for ACS, obviously due to (unconsciously) not including small and large nuclei. Testing prognostic value of a series of cut off points, MNA and SDNA values assessed by the SRS method were prognostically significantly stronger than the values obtained by the ACS method. This was confirmed in Cox regression analysis. For the MNA, the Mantel-Cox p-values from SRS-50 and SRS-100 measurements were not significantly different. However, for the SDNA, SRS-100 yielded significantly lower p-values than SRS-50. In conclusion, compared with the 'at convenience' nuclear sampling method, systematic random sampling of nuclei is not only superior with respect to reproducibility of results, but also provides a better prognostic value in patients with invasive breast cancer.

Location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling

Directory of Open Access Journals (Sweden)

Alireza Goli

2015-09-01

Full Text Available Distribution and optimum allocation of emergency resources are the most important tasks, which need to be accomplished during crisis. When a natural disaster such as earthquake, flood, etc. takes place, it is necessary to deliver rescue efforts as quickly as possible. Therefore, it is important to find optimum location and distribution of emergency relief resources. When a natural disaster occurs, it is not possible to reach some damaged areas. In this paper, location and multi-depot vehicle routing for emergency vehicles using tour coverage and random sampling is investigated. In this study, there is no need to visit all the places and some demand points receive their needs from the nearest possible location. The proposed study is implemented for some randomly generated numbers in different sizes. The preliminary results indicate that the proposed method was capable of reaching desirable solutions in reasonable amount of time.

Acute stress symptoms during the second Lebanon war in a random sample of Israeli citizens.

Science.gov (United States)

Cohen, Miri; Yahav, Rivka

2008-02-01

The aims of this study were to assess prevalence of acute stress disorder (ASD) and acute stress symptoms (ASS) in Israel during the second Lebanon war. A telephone survey was conducted in July 2006 of a random sample of 235 residents of northern Israel, who were subjected to missile attacks, and of central Israel, who were not subjected to missile attacks. Results indicate that ASS scores were higher in the northern respondents; 6.8% of the northern sample and 3.9% of the central sample met ASD criteria. Appearance of each symptom ranged from 15.4% for dissociative to 88.4% for reexperiencing, with significant differences between northern and central respondents only for reexperiencing and arousal. A low ASD rate and a moderate difference between areas subjected and not subjected to attack were found.

Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling

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Hyun-Joo Oh

2017-01-01

Full Text Available This paper assesses the performance of the landslide susceptibility analysis using frequency ratio (FR with an iterative random sampling. A pair of before-and-after digital aerial photographs with 50 cm spatial resolution was used to detect landslide occurrences in Yongin area, Korea. Iterative random sampling was run ten times in total and each time it was applied to the training and validation datasets. Thirteen landslide causative factors were derived from the topographic, soil, forest, and geological maps. The FR scores were calculated from the causative factors and training occurrences repeatedly ten times. The ten landslide susceptibility maps were obtained from the integration of causative factors that assigned FR scores. The landslide susceptibility maps were validated by using each validation dataset. The FR method achieved susceptibility accuracies from 89.48% to 93.21%. And the landslide susceptibility accuracy of the FR method is higher than 89%. Moreover, the ten times iterative FR modeling may contribute to a better understanding of a regularized relationship between the causative factors and landslide susceptibility. This makes it possible to incorporate knowledge-driven considerations of the causative factors into the landslide susceptibility analysis and also be extensively used to other areas.

Determination of Initial Conditions for the Safety Analysis by Random Sampling of Operating Parameters

International Nuclear Information System (INIS)

Jeong, Hae-Yong; Park, Moon-Ghu

2015-01-01

In most existing evaluation methodologies, which follow a conservative approach, the most conservative initial conditions are searched for each transient scenario through tremendous assessment for wide operating windows or limiting conditions for operation (LCO) allowed by the operating guidelines. In this procedure, a user effect could be involved and a remarkable time and human resources are consumed. In the present study, we investigated a more effective statistical method for the selection of the most conservative initial condition by the use of random sampling of operating parameters affecting the initial conditions. A method for the determination of initial conditions based on random sampling of plant design parameters is proposed. This method is expected to be applied for the selection of the most conservative initial plant conditions in the safety analysis using a conservative evaluation methodology. In the method, it is suggested that the initial conditions of reactor coolant flow rate, pressurizer level, pressurizer pressure, and SG level are adjusted by controlling the pump rated flow, setpoints of PLCS, PPCS, and FWCS, respectively. The proposed technique is expected to contribute to eliminate the human factors introduced in the conventional safety analysis procedure and also to reduce the human resources invested in the safety evaluation of nuclear power plants

A simple sample size formula for analysis of covariance in cluster randomized trials.

NARCIS (Netherlands)

Teerenstra, S.; Eldridge, S.; Graff, M.J.; Hoop, E. de; Borm, G.F.

2012-01-01

For cluster randomized trials with a continuous outcome, the sample size is often calculated as if an analysis of the outcomes at the end of the treatment period (follow-up scores) would be performed. However, often a baseline measurement of the outcome is available or feasible to obtain. An

Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

Science.gov (United States)

Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

2017-09-14

While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

Application of a stratified random sampling technique to the estimation and minimization of respirable quartz exposure to underground miners

International Nuclear Information System (INIS)

Makepeace, C.E.; Horvath, F.J.; Stocker, H.

1981-11-01

The aim of a stratified random sampling plan is to provide the best estimate (in the absence of full-shift personal gravimetric sampling) of personal exposure to respirable quartz among underground miners. One also gains information of the exposure distribution of all the miners at the same time. Three variables (or strata) are considered in the present scheme: locations, occupations and times of sampling. Random sampling within each stratum ensures that each location, occupation and time of sampling has equal opportunity of being selected without bias. Following implementation of the plan and analysis of collected data, one can determine the individual exposures and the mean. This information can then be used to identify those groups whose exposure contributes significantly to the collective exposure. In turn, this identification, along with other considerations, allows the mine operator to carry out a cost-benefit optimization and eventual implementation of engineering controls for these groups. This optimization and engineering control procedure, together with the random sampling plan, can then be used in an iterative manner to minimize the mean value of the distribution and collective exposures

Event-triggered synchronization for reaction-diffusion complex networks via random sampling

Science.gov (United States)

Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

2018-04-01

In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

Randomized comparison of vaginal self-sampling by standard vs. dry swabs for Human papillomavirus testing

International Nuclear Information System (INIS)

Eperon, Isabelle; Vassilakos, Pierre; Navarria, Isabelle; Menoud, Pierre-Alain; Gauthier, Aude; Pache, Jean-Claude; Boulvain, Michel; Untiet, Sarah; Petignat, Patrick

2013-01-01

To evaluate if human papillomavirus (HPV) self-sampling (Self-HPV) using a dry vaginal swab is a valid alternative for HPV testing. Women attending colposcopy clinic were recruited to collect two consecutive Self-HPV samples: a Self-HPV using a dry swab (S-DRY) and a Self-HPV using a standard wet transport medium (S-WET). These samples were analyzed for HPV using real time PCR (Roche Cobas). Participants were randomized to determine the order of the tests. Questionnaires assessing preferences and acceptability for both tests were conducted. Subsequently, women were invited for colposcopic examination; a physician collected a cervical sample (physician-sampling) with a broom-type device and placed it into a liquid-based cytology medium. Specimens were then processed for the production of cytology slides and a Hybrid Capture HPV DNA test (Qiagen) was performed from the residual liquid. Biopsies were performed if indicated. Unweighted kappa statistics (κ) and McNemar tests were used to measure the agreement among the sampling methods. A total of 120 women were randomized. Overall HPV prevalence was 68.7% (95% Confidence Interval (CI) 59.3–77.2) by S-WET, 54.4% (95% CI 44.8–63.9) by S-DRY and 53.8% (95% CI 43.8–63.7) by HC. Among paired samples (S-WET and S-DRY), the overall agreement was good (85.7%; 95% CI 77.8–91.6) and the κ was substantial (0.70; 95% CI 0.57-0.70). The proportion of positive type-specific HPV agreement was also good (77.3%; 95% CI 68.2-84.9). No differences in sensitivity for cervical intraepithelial neoplasia grade one (CIN1) or worse between the two Self-HPV tests were observed. Women reported the two Self-HPV tests as highly acceptable. Self-HPV using dry swab transfer does not appear to compromise specimen integrity. Further study in a large screening population is needed. ClinicalTrials.gov: http://clinicaltrials.gov/show/NCT01316120

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies

Science.gov (United States)

Theis, Fabian J.

2017-01-01

Epidemiological studies often utilize stratified data in which rare outcomes or exposures are artificially enriched. This design can increase precision in association tests but distorts predictions when applying classifiers on nonstratified data. Several methods correct for this so-called sample selection bias, but their performance remains unclear especially for machine learning classifiers. With an emphasis on two-phase case-control studies, we aim to assess which corrections to perform in which setting and to obtain methods suitable for machine learning techniques, especially the random forest. We propose two new resampling-based methods to resemble the original data and covariance structure: stochastic inverse-probability oversampling and parametric inverse-probability bagging. We compare all techniques for the random forest and other classifiers, both theoretically and on simulated and real data. Empirical results show that the random forest profits from only the parametric inverse-probability bagging proposed by us. For other classifiers, correction is mostly advantageous, and methods perform uniformly. We discuss consequences of inappropriate distribution assumptions and reason for different behaviors between the random forest and other classifiers. In conclusion, we provide guidance for choosing correction methods when training classifiers on biased samples. For random forests, our method outperforms state-of-the-art procedures if distribution assumptions are roughly fulfilled. We provide our implementation in the R package sambia. PMID:29312464

Rationale, design, methodology and sample characteristics for the Vietnam pre-conceptual micronutrient supplementation trial (PRECONCEPT: a randomized controlled study

Directory of Open Access Journals (Sweden)

Nguyen Phuong H

2012-10-01

Full Text Available Abstract Background Low birth weight and maternal anemia remain intractable problems in many developing countries. The adequacy of the current strategy of providing iron-folic acid (IFA supplements only during pregnancy has been questioned given many women enter pregnancy with poor iron stores, the substantial micronutrient demand by maternal and fetal tissues, and programmatic issues related to timing and coverage of prenatal care. Weekly IFA supplementation for women of reproductive age (WRA improves iron status and reduces the burden of anemia in the short term, but few studies have evaluated subsequent pregnancy and birth outcomes. The Preconcept trial aims to determine whether pre-pregnancy weekly IFA or multiple micronutrient (MM supplementation will improve birth outcomes and maternal and infant iron status compared to the current practice of prenatal IFA supplementation only. This paper provides an overview of study design, methodology and sample characteristics from baseline survey data and key lessons learned. Methods/design We have recruited 5011 WRA in a double-blind stratified randomized controlled trial in rural Vietnam and randomly assigned them to receive weekly supplements containing either: 1 2800 μg folic acid 2 60 mg iron and 2800 μg folic acid or 3 MM. Women who become pregnant receive daily IFA, and are being followed through pregnancy, delivery, and up to three months post-partum. Study outcomes include birth outcomes and maternal and infant iron status. Data are being collected on household characteristics, maternal diet and mental health, anthropometry, infant feeding practices, morbidity and compliance. Discussion The study is timely and responds to the WHO Global Expert Consultation which identified the need to evaluate the long term benefits of weekly IFA and MM supplementation in WRA. Findings will generate new information to help guide policy and programs designed to reduce the burden of anemia in women and

A topological analysis of large-scale structure, studied using the CMASS sample of SDSS-III

International Nuclear Information System (INIS)

Parihar, Prachi; Gott, J. Richard III; Vogeley, Michael S.; Choi, Yun-Young; Kim, Juhan; Kim, Sungsoo S.; Speare, Robert; Brownstein, Joel R.; Brinkmann, J.

2014-01-01

We study the three-dimensional genus topology of large-scale structure using the northern region of the CMASS Data Release 10 (DR10) sample of the SDSS-III Baryon Oscillation Spectroscopic Survey. We select galaxies with redshift 0.452 < z < 0.625 and with a stellar mass M stellar > 10 11.56 M ☉ . We study the topology at two smoothing lengths: R G = 21 h –1 Mpc and R G = 34 h –1 Mpc. The genus topology studied at the R G = 21 h –1 Mpc scale results in the highest genus amplitude observed to date. The CMASS sample yields a genus curve that is characteristic of one produced by Gaussian random phase initial conditions. The data thus support the standard model of inflation where random quantum fluctuations in the early universe produced Gaussian random phase initial conditions. Modest deviations in the observed genus from random phase are as expected from shot noise effects and the nonlinear evolution of structure. We suggest the use of a fitting formula motivated by perturbation theory to characterize the shift and asymmetries in the observed genus curve with a single parameter. We construct 54 mock SDSS CMASS surveys along the past light cone from the Horizon Run 3 (HR3) N-body simulations, where gravitationally bound dark matter subhalos are identified as the sites of galaxy formation. We study the genus topology of the HR3 mock surveys with the same geometry and sampling density as the observational sample and find the observed genus topology to be consistent with ΛCDM as simulated by the HR3 mock samples. We conclude that the topology of the large-scale structure in the SDSS CMASS sample is consistent with cosmological models having primordial Gaussian density fluctuations growing in accordance with general relativity to form galaxies in massive dark matter halos.

Randomization of grab-sampling strategies for estimating the annual exposure of U miners to Rn daughters.

Science.gov (United States)

Borak, T B

1986-04-01

Periodic grab sampling in combination with time-of-occupancy surveys has been the accepted procedure for estimating the annual exposure of underground U miners to Rn daughters. Temporal variations in the concentration of potential alpha energy in the mine generate uncertainties in this process. A system to randomize the selection of locations for measurement is described which can reduce uncertainties and eliminate systematic biases in the data. In general, a sample frequency of 50 measurements per year is sufficient to satisfy the criteria that the annual exposure be determined in working level months to within +/- 50% of the true value with a 95% level of confidence. Suggestions for implementing this randomization scheme are presented.

A systematic examination of a random sampling strategy for source apportionment calculations.

Science.gov (United States)

Andersson, August

2011-12-15

Estimating the relative contributions from multiple potential sources of a specific component in a mixed environmental matrix is a general challenge in diverse fields such as atmospheric, environmental and earth sciences. Perhaps the most common strategy for tackling such problems is by setting up a system of linear equations for the fractional influence of different sources. Even though an algebraic solution of this approach is possible for the common situation with N+1 sources and N source markers, such methodology introduces a bias, since it is implicitly assumed that the calculated fractions and the corresponding uncertainties are independent of the variability of the source distributions. Here, a random sampling (RS) strategy for accounting for such statistical bias is examined by investigating rationally designed synthetic data sets. This random sampling methodology is found to be robust and accurate with respect to reproducibility and predictability. This method is also compared to a numerical integration solution for a two-source situation where source variability also is included. A general observation from this examination is that the variability of the source profiles not only affects the calculated precision but also the mean/median source contributions. Copyright © 2011 Elsevier B.V. All rights reserved.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States.

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Andreas Steimer

Full Text Available Oscillations between high and low values of the membrane potential (UP and DOWN states respectively are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon's implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs of the exponential integrate and fire (EIF model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike's preceding ISI. As we show, the EIF's exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron's ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States.

Science.gov (United States)

Steimer, Andreas; Schindler, Kaspar

2015-01-01

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon's implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike's preceding ISI. As we show, the EIF's exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron's ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational

MUP, CEC-DES, STRADE. Codes for uncertainty propagation, experimental design and stratified random sampling techniques

International Nuclear Information System (INIS)

Amendola, A.; Astolfi, M.; Lisanti, B.

1983-01-01

The report describes the how-to-use of the codes: MUP (Monte Carlo Uncertainty Propagation) for uncertainty analysis by Monte Carlo simulation, including correlation analysis, extreme value identification and study of selected ranges of the variable space; CEC-DES (Central Composite Design) for building experimental matrices according to the requirements of Central Composite and Factorial Experimental Designs; and, STRADE (Stratified Random Design) for experimental designs based on the Latin Hypercube Sampling Techniques. Application fields, of the codes are probabilistic risk assessment, experimental design, sensitivity analysis and system identification problems

Distributed fiber sparse-wideband vibration sensing by sub-Nyquist additive random sampling

Science.gov (United States)

Zhang, Jingdong; Zheng, Hua; Zhu, Tao; Yin, Guolu; Liu, Min; Bai, Yongzhong; Qu, Dingrong; Qiu, Feng; Huang, Xianbing

2018-05-01

The round trip time of the light pulse limits the maximum detectable vibration frequency response range of phase-sensitive optical time domain reflectometry ({\\phi}-OTDR). Unlike the uniform laser pulse interval in conventional {\\phi}-OTDR, we randomly modulate the pulse interval, so that an equivalent sub-Nyquist additive random sampling (sNARS) is realized for every sensing point of the long interrogation fiber. For an {\\phi}-OTDR system with 10 km sensing length, the sNARS method is optimized by theoretical analysis and Monte Carlo simulation, and the experimental results verify that a wide-band spars signal can be identified and reconstructed. Such a method can broaden the vibration frequency response range of {\\phi}-OTDR, which is of great significance in sparse-wideband-frequency vibration signal detection, such as rail track monitoring and metal defect detection.

Assessing differences in groups randomized by recruitment chain in a respondent-driven sample of Seattle-area injection drug users.

Science.gov (United States)

Burt, Richard D; Thiede, Hanne

2014-11-01

Respondent-driven sampling (RDS) is a form of peer-based study recruitment and analysis that incorporates features designed to limit and adjust for biases in traditional snowball sampling. It is being widely used in studies of hidden populations. We report an empirical evaluation of RDS's consistency and variability, comparing groups recruited contemporaneously, by identical methods and using identical survey instruments. We randomized recruitment chains from the RDS-based 2012 National HIV Behavioral Surveillance survey of injection drug users in the Seattle area into two groups and compared them in terms of sociodemographic characteristics, drug-associated risk behaviors, sexual risk behaviors, human immunodeficiency virus (HIV) status and HIV testing frequency. The two groups differed in five of the 18 variables examined (P ≤ .001): race (e.g., 60% white vs. 47%), gender (52% male vs. 67%), area of residence (32% downtown Seattle vs. 44%), an HIV test in the previous 12 months (51% vs. 38%). The difference in serologic HIV status was particularly pronounced (4% positive vs. 18%). In four further randomizations, differences in one to five variables attained this level of significance, although the specific variables involved differed. We found some material differences between the randomized groups. Although the variability of the present study was less than has been reported in serial RDS surveys, these findings indicate caution in the interpretation of RDS results. Copyright © 2014 Elsevier Inc. All rights reserved.

Sample Size and Saturation in PhD Studies Using Qualitative Interviews

Directory of Open Access Journals (Sweden)

Mark Mason

2010-08-01

Full Text Available A number of issues can affect sample size in qualitative research; however, the guiding principle should be the concept of saturation. This has been explored in detail by a number of authors but is still hotly debated, and some say little understood. A sample of PhD studies using qualitative approaches, and qualitative interviews as the method of data collection was taken from theses.com and contents analysed for their sample sizes. Five hundred and sixty studies were identified that fitted the inclusion criteria. Results showed that the mean sample size was 31; however, the distribution was non-random, with a statistically significant proportion of studies, presenting sample sizes that were multiples of ten. These results are discussed in relation to saturation. They suggest a pre-meditated approach that is not wholly congruent with the principles of qualitative research. URN: urn:nbn:de:0114-fqs100387

Studies in astronomical time series analysis: Modeling random processes in the time domain

Science.gov (United States)

Scargle, J. D.

1979-01-01

Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

The quality of the reported sample size calculations in randomized controlled trials indexed in PubMed.

Science.gov (United States)

Lee, Paul H; Tse, Andy C Y

2017-05-01

There are limited data on the quality of reporting of information essential for replication of the calculation as well as the accuracy of the sample size calculation. We examine the current quality of reporting of the sample size calculation in randomized controlled trials (RCTs) published in PubMed and to examine the variation in reporting across study design, study characteristics, and journal impact factor. We also reviewed the targeted sample size reported in trial registries. We reviewed and analyzed all RCTs published in December 2014 with journals indexed in PubMed. The 2014 Impact Factors for the journals were used as proxies for their quality. Of the 451 analyzed papers, 58.1% reported an a priori sample size calculation. Nearly all papers provided the level of significance (97.7%) and desired power (96.6%), and most of the papers reported the minimum clinically important effect size (73.3%). The median (inter-quartile range) of the percentage difference of the reported and calculated sample size calculation was 0.0% (IQR -4.6%;3.0%). The accuracy of the reported sample size was better for studies published in journals that endorsed the CONSORT statement and journals with an impact factor. A total of 98 papers had provided targeted sample size on trial registries and about two-third of these papers (n=62) reported sample size calculation, but only 25 (40.3%) had no discrepancy with the reported number in the trial registries. The reporting of the sample size calculation in RCTs published in PubMed-indexed journals and trial registries were poor. The CONSORT statement should be more widely endorsed. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Computer code ENDSAM for random sampling and validation of the resonance parameters covariance matrices of some major nuclear data libraries

International Nuclear Information System (INIS)

Plevnik, Lucijan; Žerovnik, Gašper

2016-01-01

Highlights: • Methods for random sampling of correlated parameters. • Link to open-source code for sampling of resonance parameters in ENDF-6 format. • Validation of the code on realistic and artificial data. • Validation of covariances in three major contemporary nuclear data libraries. - Abstract: Methods for random sampling of correlated parameters are presented. The methods are implemented for sampling of resonance parameters in ENDF-6 format and a link to the open-source code ENDSAM is given. The code has been validated on realistic data. Additionally, consistency of covariances of resonance parameters of three major contemporary nuclear data libraries (JEFF-3.2, ENDF/B-VII.1 and JENDL-4.0u2) has been checked.

Random sampling of quantum states: a survey of methods and some issues regarding the Overparametrized Method

International Nuclear Information System (INIS)

Maziero, Jonas

2015-01-01

The numerical generation of random quantum states (RQS) is an important procedure for investigations in quantum information science. Here, we review some methods that may be used for performing that task. We start by presenting a simple procedure for generating random state vectors, for which the main tool is the random sampling of unbiased discrete probability distributions (DPD). Afterwards, the creation of random density matrices is addressed. In this context, we first present the standard method, which consists in using the spectral decomposition of a quantum state for getting RQS from random DPDs and random unitary matrices. In the sequence, the Bloch vector parametrization method is described. This approach, despite being useful in several instances, is not in general convenient for RQS generation. In the last part of the article, we regard the overparametrized method (OPM) and the related Ginibre and Bures techniques. The OPM can be used to create random positive semidefinite matrices with unit trace from randomly produced general complex matrices in a simple way that is friendly for numerical implementations. We consider a physically relevant issue related to the possible domains that may be used for the real and imaginary parts of the elements of such general complex matrices. Subsequently, a too fast concentration of measure in the quantum state space that appears in this parametrization is noticed. (author)

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

Science.gov (United States)

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure

New complete sample of identified radio sources. Part 2. Statistical study

International Nuclear Information System (INIS)

Soltan, A.

1978-01-01

Complete sample of radio sources with known redshifts selected in Paper I is studied. Source counts in the sample and the luminosity - volume test show that both quasars and galaxies are subject to the evolution. Luminosity functions for different ranges of redshifts are obtained. Due to many uncertainties only simplified models of the evolution are tested. Exponential decline of the liminosity with time of all the bright sources is in a good agreement both with the luminosity- volume test and N(S) realtion in the entire range of observed flux densities. It is shown that sources in the sample are randomly distributed in scales greater than about 17 Mpc. (author)

[A comparison of convenience sampling and purposive sampling].

Science.gov (United States)

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

2014-06-01

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

Sample Size Calculation: Inaccurate A Priori Assumptions for Nuisance Parameters Can Greatly Affect the Power of a Randomized Controlled Trial.

Directory of Open Access Journals (Sweden)

Elsa Tavernier

Full Text Available We aimed to examine the extent to which inaccurate assumptions for nuisance parameters used to calculate sample size can affect the power of a randomized controlled trial (RCT. In a simulation study, we separately considered an RCT with continuous, dichotomous or time-to-event outcomes, with associated nuisance parameters of standard deviation, success rate in the control group and survival rate in the control group at some time point, respectively. For each type of outcome, we calculated a required sample size N for a hypothesized treatment effect, an assumed nuisance parameter and a nominal power of 80%. We then assumed a nuisance parameter associated with a relative error at the design stage. For each type of outcome, we randomly drew 10,000 relative errors of the associated nuisance parameter (from empirical distributions derived from a previously published review. Then, retro-fitting the sample size formula, we derived, for the pre-calculated sample size N, the real power of the RCT, taking into account the relative error for the nuisance parameter. In total, 23%, 0% and 18% of RCTs with continuous, binary and time-to-event outcomes, respectively, were underpowered (i.e., the real power was 90%. Even with proper calculation of sample size, a substantial number of trials are underpowered or overpowered because of imprecise knowledge of nuisance parameters. Such findings raise questions about how sample size for RCTs should be determined.

Distribution of peak expiratory flow variability by age, gender and smoking habits in a random population sample aged 20-70 yrs

NARCIS (Netherlands)

Boezen, H M; Schouten, J. P.; Postma, D S; Rijcken, B

1994-01-01

Peak expiratory flow (PEF) variability can be considered as an index of bronchial lability. Population studies on PEF variability are few. The purpose of the current paper is to describe the distribution of PEF variability in a random population sample of adults with a wide age range (20-70 yrs),

Modern survey sampling

CERN Document Server

Chaudhuri, Arijit

2014-01-01

Exposure to SamplingAbstract Introduction Concepts of Population, Sample, and SamplingInitial RamificationsAbstract Introduction Sampling Design, Sampling SchemeRandom Numbers and Their Uses in Simple RandomSampling (SRS)Drawing Simple Random Samples with and withoutReplacementEstimation of Mean, Total, Ratio of Totals/Means:Variance and Variance EstimationDetermination of Sample SizesA.2 Appendix to Chapter 2 A.More on Equal Probability Sampling A.Horvitz-Thompson EstimatorA.SufficiencyA.LikelihoodA.Non-Existence Theorem More Intricacies Abstract Introduction Unequal Probability Sampling StrategiesPPS Sampling Exploring Improved WaysAbstract Introduction Stratified Sampling Cluster SamplingMulti-Stage SamplingMulti-Phase Sampling: Ratio and RegressionEstimationviiviii ContentsControlled SamplingModeling Introduction Super-Population ModelingPrediction Approach Model-Assisted Approach Bayesian Methods Spatial SmoothingSampling on Successive Occasions: Panel Rotation Non-Response and Not-at-Homes Weighting Adj...

Blocked Randomization with Randomly Selected Block Sizes

Directory of Open Access Journals (Sweden)

Jimmy Efird

2010-12-01

Full Text Available When planning a randomized clinical trial, careful consideration must be given to how participants are selected for various arms of a study. Selection and accidental bias may occur when participants are not assigned to study groups with equal probability. A simple random allocation scheme is a process by which each participant has equal likelihood of being assigned to treatment versus referent groups. However, by chance an unequal number of individuals may be assigned to each arm of the study and thus decrease the power to detect statistically significant differences between groups. Block randomization is a commonly used technique in clinical trial design to reduce bias and achieve balance in the allocation of participants to treatment arms, especially when the sample size is small. This method increases the probability that each arm will contain an equal number of individuals by sequencing participant assignments by block. Yet still, the allocation process may be predictable, for example, when the investigator is not blind and the block size is fixed. This paper provides an overview of blocked randomization and illustrates how to avoid selection bias by using random block sizes.

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

Science.gov (United States)

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

A random cluster survey and a convenience sample give comparable estimates of immunity to vaccine preventable diseases in children of school age in Victoria, Australia.

Science.gov (United States)

Kelly, Heath; Riddell, Michaela A; Gidding, Heather F; Nolan, Terry; Gilbert, Gwendolyn L

2002-08-19

We compared estimates of the age-specific population immunity to measles, mumps, rubella, hepatitis B and varicella zoster viruses in Victorian school children obtained by a national sero-survey, using a convenience sample of residual sera from diagnostic laboratories throughout Australia, with those from a three-stage random cluster survey. When grouped according to school age (primary or secondary school) there was no significant difference in the estimates of immunity to measles, mumps, hepatitis B or varicella. Compared with the convenience sample, the random cluster survey estimated higher immunity to rubella in samples from both primary (98.7% versus 93.6%, P = 0.002) and secondary school students (98.4% versus 93.2%, P = 0.03). Despite some limitations, this study suggests that the collection of a convenience sample of sera from diagnostic laboratories is an appropriate sampling strategy to provide population immunity data that will inform Australia's current and future immunisation policies. Copyright 2002 Elsevier Science Ltd.

Random selection of items. Selection of n1 samples among N items composing a stratum

International Nuclear Information System (INIS)

Jaech, J.L.; Lemaire, R.J.

1987-02-01

STR-224 provides generalized procedures to determine required sample sizes, for instance in the course of a Physical Inventory Verification at Bulk Handling Facilities. The present report describes procedures to generate random numbers and select groups of items to be verified in a given stratum through each of the measurement methods involved in the verification. (author). 3 refs

Sampling Studies at an Air Force Live-Fire Bombing Range Impact Area

National Research Council Canada - National Science Library

Jenkins, Thomas F; Hewitt, Alan D; Ramsey, Charles A; Bjella, Kevin L; Bigl, Susan R; Lambert, Dennis J

2006-01-01

.... The main objective was to assess the effectiveness of using a systematic-random, multi-increment sampling strategy for the collection of representative surface soil samples in areas where bombing...

A Combined Weighting Method Based on Hybrid of Interval Evidence Fusion and Random Sampling

Directory of Open Access Journals (Sweden)

Ying Yan

2017-01-01

Full Text Available Due to the complexity of system and lack of expertise, epistemic uncertainties may present in the experts’ judgment on the importance of certain indices during group decision-making. A novel combination weighting method is proposed to solve the index weighting problem when various uncertainties are present in expert comments. Based on the idea of evidence theory, various types of uncertain evaluation information are uniformly expressed through interval evidence structures. Similarity matrix between interval evidences is constructed, and expert’s information is fused. Comment grades are quantified using the interval number, and cumulative probability function for evaluating the importance of indices is constructed based on the fused information. Finally, index weights are obtained by Monte Carlo random sampling. The method can process expert’s information with varying degrees of uncertainties, which possesses good compatibility. Difficulty in effectively fusing high-conflict group decision-making information and large information loss after fusion is avertible. Original expert judgments are retained rather objectively throughout the processing procedure. Cumulative probability function constructing and random sampling processes do not require any human intervention or judgment. It can be implemented by computer programs easily, thus having an apparent advantage in evaluation practices of fairly huge index systems.

The Study on Mental Health at Work: Design and sampling.

Science.gov (United States)

Rose, Uwe; Schiel, Stefan; Schröder, Helmut; Kleudgen, Martin; Tophoven, Silke; Rauch, Angela; Freude, Gabriele; Müller, Grit

2017-08-01

The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. S-MGA is a representative study of German employees aged 31-60 years subject to social security contributions. The sample was drawn from the employment register based on a two-stage cluster sampling procedure. Firstly, 206 municipalities were randomly selected from a pool of 12,227 municipalities in Germany. Secondly, 13,590 addresses were drawn from the selected municipalities for the purpose of conducting 4500 face-to-face interviews. The questionnaire covers psychosocial working and employment conditions, measures of mental health, work ability and functioning. Data from personal interviews were combined with employment histories from register data. Descriptive statistics of socio-demographic characteristics and logistic regressions analyses were used for comparing population, gross sample and respondents. In total, 4511 face-to-face interviews were conducted. A test for sampling bias revealed that individuals in older cohorts participated more often, while individuals with an unknown educational level, residing in major cities or with a non-German ethnic background were slightly underrepresented. There is no indication of major deviations in characteristics between the basic population and the sample of respondents. Hence, S-MGA provides representative data for research on work and health, designed as a cohort study with plans to rerun the survey 5 years after the first assessment.

The Study on Mental Health at Work: Design and sampling

Science.gov (United States)

Rose, Uwe; Schiel, Stefan; Schröder, Helmut; Kleudgen, Martin; Tophoven, Silke; Rauch, Angela; Freude, Gabriele; Müller, Grit

2017-01-01

Aims: The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. Methods: S-MGA is a representative study of German employees aged 31–60 years subject to social security contributions. The sample was drawn from the employment register based on a two-stage cluster sampling procedure. Firstly, 206 municipalities were randomly selected from a pool of 12,227 municipalities in Germany. Secondly, 13,590 addresses were drawn from the selected municipalities for the purpose of conducting 4500 face-to-face interviews. The questionnaire covers psychosocial working and employment conditions, measures of mental health, work ability and functioning. Data from personal interviews were combined with employment histories from register data. Descriptive statistics of socio-demographic characteristics and logistic regressions analyses were used for comparing population, gross sample and respondents. Results: In total, 4511 face-to-face interviews were conducted. A test for sampling bias revealed that individuals in older cohorts participated more often, while individuals with an unknown educational level, residing in major cities or with a non-German ethnic background were slightly underrepresented. Conclusions: There is no indication of major deviations in characteristics between the basic population and the sample of respondents. Hence, S-MGA provides representative data for research on work and health, designed as a cohort study with plans to rerun the survey 5 years after the first assessment. PMID:28673202

Self-reference and random sampling approach for label-free identification of DNA composition using plasmonic nanomaterials.

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Freeman, Lindsay M; Pang, Lin; Fainman, Yeshaiahu

2018-05-09

The analysis of DNA has led to revolutionary advancements in the fields of medical diagnostics, genomics, prenatal screening, and forensic science, with the global DNA testing market expected to reach revenues of USD 10.04 billion per year by 2020. However, the current methods for DNA analysis remain dependent on the necessity for fluorophores or conjugated proteins, leading to high costs associated with consumable materials and manual labor. Here, we demonstrate a potential label-free DNA composition detection method using surface-enhanced Raman spectroscopy (SERS) in which we identify the composition of cytosine and adenine within single strands of DNA. This approach depends on the fact that there is one phosphate backbone per nucleotide, which we use as a reference to compensate for systematic measurement variations. We utilize plasmonic nanomaterials with random Raman sampling to perform label-free detection of the nucleotide composition within DNA strands, generating a calibration curve from standard samples of DNA and demonstrating the capability of resolving the nucleotide composition. The work represents an innovative way for detection of the DNA composition within DNA strands without the necessity of attached labels, offering a highly sensitive and reproducible method that factors in random sampling to minimize error.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

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NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Sampling Strategies and Processing of Biobank Tissue Samples from Porcine Biomedical Models.

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Blutke, Andreas; Wanke, Rüdiger

2018-03-06

In translational medical research, porcine models have steadily become more popular. Considering the high value of individual animals, particularly of genetically modified pig models, and the often-limited number of available animals of these models, establishment of (biobank) collections of adequately processed tissue samples suited for a broad spectrum of subsequent analyses methods, including analyses not specified at the time point of sampling, represent meaningful approaches to take full advantage of the translational value of the model. With respect to the peculiarities of porcine anatomy, comprehensive guidelines have recently been established for standardized generation of representative, high-quality samples from different porcine organs and tissues. These guidelines are essential prerequisites for the reproducibility of results and their comparability between different studies and investigators. The recording of basic data, such as organ weights and volumes, the determination of the sampling locations and of the numbers of tissue samples to be generated, as well as their orientation, size, processing and trimming directions, are relevant factors determining the generalizability and usability of the specimen for molecular, qualitative, and quantitative morphological analyses. Here, an illustrative, practical, step-by-step demonstration of the most important techniques for generation of representative, multi-purpose biobank specimen from porcine tissues is presented. The methods described here include determination of organ/tissue volumes and densities, the application of a volume-weighted systematic random sampling procedure for parenchymal organs by point-counting, determination of the extent of tissue shrinkage related to histological embedding of samples, and generation of randomly oriented samples for quantitative stereological analyses, such as isotropic uniform random (IUR) sections generated by the "Orientator" and "Isector" methods, and vertical

Gray bootstrap method for estimating frequency-varying random vibration signals with small samples

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Wang Yanqing

2014-04-01

Full Text Available During environment testing, the estimation of random vibration signals (RVS is an important technique for the airborne platform safety and reliability. However, the available methods including extreme value envelope method (EVEM, statistical tolerances method (STM and improved statistical tolerance method (ISTM require large samples and typical probability distribution. Moreover, the frequency-varying characteristic of RVS is usually not taken into account. Gray bootstrap method (GBM is proposed to solve the problem of estimating frequency-varying RVS with small samples. Firstly, the estimated indexes are obtained including the estimated interval, the estimated uncertainty, the estimated value, the estimated error and estimated reliability. In addition, GBM is applied to estimating the single flight testing of certain aircraft. At last, in order to evaluate the estimated performance, GBM is compared with bootstrap method (BM and gray method (GM in testing analysis. The result shows that GBM has superiority for estimating dynamic signals with small samples and estimated reliability is proved to be 100% at the given confidence level.

Childhood adiposity and risk of type 1 diabetes: A Mendelian randomization study.

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J C Censin

2017-08-01

Full Text Available The incidence of type 1 diabetes (T1D is increasing globally. One hypothesis is that increasing childhood obesity rates may explain part of this increase, but, as T1D is rare, intervention studies are challenging to perform. The aim of this study was to assess this hypothesis with a Mendelian randomization approach that uses genetic variants as instrumental variables to test for causal associations.We created a genetic instrument of 23 single nucleotide polymorphisms (SNPs associated with childhood adiposity in children aged 2-10 years. Summary-level association results for these 23 SNPs with childhood-onset (<17 years T1D were extracted from a meta-analysis of genome-wide association study with 5,913 T1D cases and 8,828 reference samples. Using inverse-variance weighted Mendelian randomization analysis, we found support for an effect of childhood adiposity on T1D risk (odds ratio 1.32, 95% CI 1.06-1.64 per standard deviation score in body mass index [SDS-BMI]. A sensitivity analysis provided evidence of horizontal pleiotropy bias (p = 0.04 diluting the estimates towards the null. We therefore applied Egger regression and multivariable Mendelian randomization methods to control for this type of bias and found evidence in support of a role of childhood adiposity in T1D (odds ratio in Egger regression, 2.76, 95% CI 1.40-5.44. Limitations of our study include that underlying genes and their mechanisms for most of the genetic variants included in the score are not known. Mendelian randomization requires large sample sizes, and power was limited to provide precise estimates. This research has been conducted using data from the Early Growth Genetics (EGG Consortium, the Genetic Investigation of Anthropometric Traits (GIANT Consortium, the Tobacco and Genetics (TAG Consortium, and the Social Science Genetic Association Consortium (SSGAC, as well as meta-analysis results from a T1D genome-wide association study.This study provides genetic support for a

A study on the representative sampling survey for the inspection of the clearance level for the radioisotope waste

International Nuclear Information System (INIS)

Hong Joo Ahn; Se Chul Sohn; Kwang Yong Jee; Ju Youl Kim; In Koo Lee

2007-01-01

Utilization facilities for radioisotope (RI) are increasing annually in South Korea, and the total number was 2,723, as of December 31, 2005. The inspection of a clearance level is a very important problem in order to ensure a social reliance for releasing radioactive materials to the environment. Korean regulations for such a clearance are described in Notice No. 2001-30 of the Ministry of Science and Technology (MOST) and Notice No. 2002-67 of the Ministry of Commerce, Industry and Energy (MOCIE). Most unsealed sources in RI waste drums at a storage facility are low-level beta-emitters with short half-lives, so it is impossible to measure their inventories by a nondestructive analysis. Furthermore, RI wastes generated from hospital, educational and research institutes and industry have a heterogeneous, multiple, irregular, and a small quantity of a waste stream. This study addresses a representative (master) sampling survey and analysis plan for RI wastes because a complete enumeration of waste drums is impossible and not desirable in terms of a cost and efficiency. The existing approaches to a representative sampling include a judgmental, simple random, stratified random, systematic grid, systematic random, composite, and adaptive sampling. A representative sampling plan may combine two or more of the above sampling approaches depending on the type and distribution of a waste stream. Stratified random sampling (constrained randomization) is proven to be adequate for a sampling design of a RI waste regarding a half-life, surface dose, undertaking time to a storage facility, and type of waste. The developed sampling protocol includes estimating the number of drums within a waste stream, estimating the number of samples, and a confirmation of the required number of samples. The statistical process control for a quality assurance plan includes control charts and an upper control limit (UCL) of 95% to determine whether a clearance level is met or not. (authors)

Randomized Comparison of Two Vaginal Self-Sampling Methods for Human Papillomavirus Detection: Dry Swab versus FTA Cartridge

OpenAIRE

Catarino, Rosa; Vassilakos, Pierre; Bilancioni, Aline; Vanden Eynde, Mathieu; Meyer-Hamme, Ulrike; Menoud, Pierre-Alain; Guerry, Fr?d?ric; Petignat, Patrick

2015-01-01

Background Human papillomavirus (HPV) self-sampling (self-HPV) is valuable in cervical cancer screening. HPV testing is usually performed on physician-collected cervical smears stored in liquid-based medium. Dry filters and swabs are an alternative. We evaluated the adequacy of self-HPV using two dry storage and transport devices, the FTA cartridge and swab. Methods A total of 130 women performed two consecutive self-HPV samples. Randomization determined which of the two tests was performed f...

Discriminative motif discovery via simulated evolution and random under-sampling.

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Tao Song

Full Text Available Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

Discriminative motif discovery via simulated evolution and random under-sampling.

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Song, Tao; Gu, Hong

2014-01-01

Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs) training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

RANdom SAmple Consensus (RANSAC) algorithm for material-informatics: application to photovoltaic solar cells.

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Kaspi, Omer; Yosipof, Abraham; Senderowitz, Hanoch

2017-06-06

An important aspect of chemoinformatics and material-informatics is the usage of machine learning algorithms to build Quantitative Structure Activity Relationship (QSAR) models. The RANdom SAmple Consensus (RANSAC) algorithm is a predictive modeling tool widely used in the image processing field for cleaning datasets from noise. RANSAC could be used as a "one stop shop" algorithm for developing and validating QSAR models, performing outlier removal, descriptors selection, model development and predictions for test set samples using applicability domain. For "future" predictions (i.e., for samples not included in the original test set) RANSAC provides a statistical estimate for the probability of obtaining reliable predictions, i.e., predictions within a pre-defined number of standard deviations from the true values. In this work we describe the first application of RNASAC in material informatics, focusing on the analysis of solar cells. We demonstrate that for three datasets representing different metal oxide (MO) based solar cell libraries RANSAC-derived models select descriptors previously shown to correlate with key photovoltaic properties and lead to good predictive statistics for these properties. These models were subsequently used to predict the properties of virtual solar cells libraries highlighting interesting dependencies of PV properties on MO compositions.

Relationship between accuracy and number of samples on statistical quantity and contour map of environmental gamma-ray dose rate. Example of random sampling

International Nuclear Information System (INIS)

Matsuda, Hideharu; Minato, Susumu

2002-01-01

The accuracy of statistical quantity like the mean value and contour map obtained by measurement of the environmental gamma-ray dose rate was evaluated by random sampling of 5 different model distribution maps made by the mean slope, -1.3, of power spectra calculated from the actually measured values. The values were derived from 58 natural gamma dose rate data reported worldwide ranging in the means of 10-100 Gy/h rates and 10 -3 -10 7 km 2 areas. The accuracy of the mean value was found around ±7% even for 60 or 80 samplings (the most frequent number) and the standard deviation had the accuracy less than 1/4-1/3 of the means. The correlation coefficient of the frequency distribution was found 0.860 or more for 200-400 samplings (the most frequent number) but of the contour map, 0.502-0.770. (K.H.)

Simultaneous escaping of explicit and hidden free energy barriers: application of the orthogonal space random walk strategy in generalized ensemble based conformational sampling.

Science.gov (United States)

Zheng, Lianqing; Chen, Mengen; Yang, Wei

2009-06-21

To overcome the pseudoergodicity problem, conformational sampling can be accelerated via generalized ensemble methods, e.g., through the realization of random walks along prechosen collective variables, such as spatial order parameters, energy scaling parameters, or even system temperatures or pressures, etc. As usually observed, in generalized ensemble simulations, hidden barriers are likely to exist in the space perpendicular to the collective variable direction and these residual free energy barriers could greatly abolish the sampling efficiency. This sampling issue is particularly severe when the collective variable is defined in a low-dimension subset of the target system; then the "Hamiltonian lagging" problem, which reveals the fact that necessary structural relaxation falls behind the move of the collective variable, may be likely to occur. To overcome this problem in equilibrium conformational sampling, we adopted the orthogonal space random walk (OSRW) strategy, which was originally developed in the context of free energy simulation [L. Zheng, M. Chen, and W. Yang, Proc. Natl. Acad. Sci. U.S.A. 105, 20227 (2008)]. Thereby, generalized ensemble simulations can simultaneously escape both the explicit barriers along the collective variable direction and the hidden barriers that are strongly coupled with the collective variable move. As demonstrated in our model studies, the present OSRW based generalized ensemble treatments show improved sampling capability over the corresponding classical generalized ensemble treatments.

Choosing a suitable sample size in descriptive sampling

International Nuclear Information System (INIS)

Lee, Yong Kyun; Choi, Dong Hoon; Cha, Kyung Joon

2010-01-01

Descriptive sampling (DS) is an alternative to crude Monte Carlo sampling (CMCS) in finding solutions to structural reliability problems. It is known to be an effective sampling method in approximating the distribution of a random variable because it uses the deterministic selection of sample values and their random permutation,. However, because this method is difficult to apply to complex simulations, the sample size is occasionally determined without thorough consideration. Input sample variability may cause the sample size to change between runs, leading to poor simulation results. This paper proposes a numerical method for choosing a suitable sample size for use in DS. Using this method, one can estimate a more accurate probability of failure in a reliability problem while running a minimal number of simulations. The method is then applied to several examples and compared with CMCS and conventional DS to validate its usefulness and efficiency

A Randomized Control Study of Responsive Teaching with Young Turkish Children and Their Mothers

Science.gov (United States)

Karaaslan, Ozcan; Diken, Ibrahim H.; Mahoney, Gerald

2013-01-01

A randomized control study was conducted to evaluate the effectiveness of responsive teaching (RT) with a sample of 19 Turkish preschool-age children with disabilities and their mothers over a 6-months period. RT is an early intervention curriculum that attempts to promote children's development by encouraging parents to engage in highly…

Nutritional status and falls in community-dwelling older people: a longitudinal study of a population-based random sample.

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Ming-Hung Chien

Full Text Available Falls are common in older people and may lead to functional decline, disability, and death. Many risk factors have been identified, but studies evaluating effects of nutritional status are limited. To determine whether nutritional status is a predictor of falls in older people living in the community, we analyzed data collected through the Survey of Health and Living Status of the Elderly in Taiwan (SHLSET.SHLSET include a series of interview surveys conducted by the government on a random sample of people living in community dwellings in the nation. We included participants who received nutritional status assessment using the Mini Nutritional Assessment Taiwan Version 2 (MNA-T2 in the 1999 survey when they were 53 years or older and followed up on the cumulative incidence of falls in the one-year period before the interview in the 2003 survey.At the beginning of follow-up, the 4440 participants had a mean age of 69.5 (standard deviation= 9.1 years, and 467 participants were "not well-nourished," which was defined as having an MNA-T2 score of 23 or less. In the one-year study period, 659 participants reported having at least one fall. After adjusting for other risk factors, we found the associated odds ratio for falls was 1.73 (95% confidence interval, 1.23, 2.42 for "not well-nourished," 1.57 (1.30, 1.90 for female gender, 1.03 (1.02, 1.04 for one-year older, 1.55 (1.22, 1.98 for history of falls, 1.34 (1.05, 1.72 for hospital stay during the past 12 months, 1.66 (1.07, 2.58 for difficulties in activities of daily living, and 1.53 (1.23, 1.91 for difficulties in instrumental activities of daily living.Nutritional status is an independent predictor of falls in older people living in the community. Further studies are warranted to identify nutritional interventions that can help prevent falls in the elderly.

Sampling designs and methods for estimating fish-impingement losses at cooling-water intakes

International Nuclear Information System (INIS)

Murarka, I.P.; Bodeau, D.J.

1977-01-01

Several systems for estimating fish impingement at power plant cooling-water intakes are compared to determine the most statistically efficient sampling designs and methods. Compared to a simple random sampling scheme the stratified systematic random sampling scheme, the systematic random sampling scheme, and the stratified random sampling scheme yield higher efficiencies and better estimators for the parameters in two models of fish impingement as a time-series process. Mathematical results and illustrative examples of the applications of the sampling schemes to simulated and real data are given. Some sampling designs applicable to fish-impingement studies are presented in appendixes

Cluster designs to assess the prevalence of acute malnutrition by lot quality assurance sampling: a validation study by computer simulation.

Science.gov (United States)

Olives, Casey; Pagano, Marcello; Deitchler, Megan; Hedt, Bethany L; Egge, Kari; Valadez, Joseph J

2009-04-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67x3 (67 clusters of three observations) and a 33x6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67x3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis.

Sampling Large Graphs for Anticipatory Analytics

Science.gov (United States)

2015-05-15

low. C. Random Area Sampling Random area sampling [8] is a “ snowball ” sampling method in which a set of random seed vertices are selected and areas... Sampling Large Graphs for Anticipatory Analytics Lauren Edwards, Luke Johnson, Maja Milosavljevic, Vijay Gadepally, Benjamin A. Miller Lincoln...systems, greater human-in-the-loop involvement, or through complex algorithms. We are investigating the use of sampling to mitigate these challenges

Manual and Electroacupuncture for Labour Pain: Study Design of a Longitudinal Randomized Controlled Trial

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Linda Vixner

2012-01-01

Full Text Available Introduction. Results from previous studies on acupuncture for labour pain are contradictory and lack important information on methodology. However, studies indicate that acupuncture has a positive effect on women’s experiences of labour pain. The aim of the present study was to evaluate the efficacy of two different acupuncture stimulations, manual or electrical stimulation, compared with standard care in the relief of labour pain as the primary outcome. This paper will present in-depth information on the design of the study, following the CONSORT and STRICTA recommendations. Methods. The study was designed as a randomized controlled trial based on western medical theories. Nulliparous women with normal pregnancies admitted to the delivery ward after a spontaneous onset of labour were randomly allocated into one of three groups: manual acupuncture, electroacupuncture, or standard care. Sample size calculation gave 101 women in each group, including a total of 303 women. A Visual Analogue Scale was used for assessing pain every 30 minutes for five hours and thereafter every hour until birth. Questionnaires were distributed before treatment, directly after the birth, and at one day and two months postpartum. Blood samples were collected before and after the first treatment. This trial is registered at ClinicalTrials.gov: NCT01197950.

Parameters, test criteria and fault assessment in random sampling of waste barrels from non-qualified processes

International Nuclear Information System (INIS)

Martens, B.R.

1989-01-01

In the context of random sampling tests, parameters are checked on the waste barrels and criteria are given on which these tests are based. Also, it is shown how faulty data on the properties of the waste or faulty waste barrels should be treated. To decide the extent of testing, the properties of the waste relevant to final storage are determined based on the conditioning process used. (DG) [de

Experimental phase diagram for random laser spectra

International Nuclear Information System (INIS)

El-Dardiry, Ramy G S; Mooiweer, Ronald; Lagendijk, Ad

2012-01-01

We systematically study the presence of narrow spectral features in a wide variety of random laser samples. Less gain or stronger scattering are shown to lead to a crossover from spiky to smooth spectra. A decomposition of random laser spectra into a set of Lorentzians provides unprecedented detail in the analysis of random laser spectra. We suggest an interpretation in terms of mode competition that enables an understanding of the observed experimental trends. In this interpretation, smooth random laser spectra are a consequence of competing modes for which the loss and gain are proportional. Spectral spikes are associated with modes that are uncoupled from the mode competition in the bulk of the sample. (paper)

Sampling strategies for tropical forest nutrient cycling studies: a case study in São Paulo, Brazil

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G. Sparovek

1997-12-01

Full Text Available The precise sampling of soil, biological or micro climatic attributes in tropical forests, which are characterized by a high diversity of species and complex spatial variability, is a difficult task. We found few basic studies to guide sampling procedures. The objective of this study was to define a sampling strategy and data analysis for some parameters frequently used in nutrient cycling studies, i. e., litter amount, total nutrient amounts in litter and its composition (Ca, Mg, Κ, Ν and P, and soil attributes at three depths (organic matter, Ρ content, cation exchange capacity and base saturation. A natural remnant forest in the West of São Paulo State (Brazil was selected as study area and samples were collected in July, 1989. The total amount of litter and its total nutrient amounts had a high spatial independent variance. Conversely, the variance of litter composition was lower and the spatial dependency was peculiar to each nutrient. The sampling strategy for the estimation of litter amounts and the amount of nutrient in litter should be different than the sampling strategy for nutrient composition. For the estimation of litter amounts and the amount of nutrients in litter (related to quantity a large number of randomly distributed determinations are needed. Otherwise, for the estimation of litter nutrient composition (related to quality a smaller amount of spatially located samples should be analyzed. The determination of sampling for soil attributes differed according to the depth. Overall, surface samples (0-5 cm showed high short distance spatial dependent variance, whereas, subsurface samples exhibited spatial dependency in longer distances. Short transects with sampling interval of 5-10 m are recommended for surface sampling. Subsurface samples must also be spatially located, but with transects or grids with longer distances between sampling points over the entire area. Composite soil samples would not provide a complete

Coordination of Conditional Poisson Samples

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Grafström Anton

2015-12-01

Full Text Available Sample coordination seeks to maximize or to minimize the overlap of two or more samples. The former is known as positive coordination, and the latter as negative coordination. Positive coordination is mainly used for estimation purposes and to reduce data collection costs. Negative coordination is mainly performed to diminish the response burden of the sampled units. Poisson sampling design with permanent random numbers provides an optimum coordination degree of two or more samples. The size of a Poisson sample is, however, random. Conditional Poisson (CP sampling is a modification of the classical Poisson sampling that produces a fixed-size πps sample. We introduce two methods to coordinate Conditional Poisson samples over time or simultaneously. The first one uses permanent random numbers and the list-sequential implementation of CP sampling. The second method uses a CP sample in the first selection and provides an approximate one in the second selection because the prescribed inclusion probabilities are not respected exactly. The methods are evaluated using the size of the expected sample overlap, and are compared with their competitors using Monte Carlo simulation. The new methods provide a good coordination degree of two samples, close to the performance of Poisson sampling with permanent random numbers.

Random sequential adsorption of cubes

Science.gov (United States)

Cieśla, Michał; Kubala, Piotr

2018-01-01

Random packings built of cubes are studied numerically using a random sequential adsorption algorithm. To compare the obtained results with previous reports, three different models of cube orientation sampling were used. Also, three different cube-cube intersection algorithms were tested to find the most efficient one. The study focuses on the mean saturated packing fraction as well as kinetics of packing growth. Microstructural properties of packings were analyzed using density autocorrelation function.

Randomized Comparison of Two Vaginal Self-Sampling Methods for Human Papillomavirus Detection: Dry Swab versus FTA Cartridge.

Science.gov (United States)

Catarino, Rosa; Vassilakos, Pierre; Bilancioni, Aline; Vanden Eynde, Mathieu; Meyer-Hamme, Ulrike; Menoud, Pierre-Alain; Guerry, Frédéric; Petignat, Patrick

2015-01-01

Human papillomavirus (HPV) self-sampling (self-HPV) is valuable in cervical cancer screening. HPV testing is usually performed on physician-collected cervical smears stored in liquid-based medium. Dry filters and swabs are an alternative. We evaluated the adequacy of self-HPV using two dry storage and transport devices, the FTA cartridge and swab. A total of 130 women performed two consecutive self-HPV samples. Randomization determined which of the two tests was performed first: self-HPV using dry swabs (s-DRY) or vaginal specimen collection using a cytobrush applied to an FTA cartridge (s-FTA). After self-HPV, a physician collected a cervical sample using liquid-based medium (Dr-WET). HPV types were identified by real-time PCR. Agreement between collection methods was measured using the kappa statistic. HPV prevalence for high-risk types was 62.3% (95%CI: 53.7-70.2) detected by s-DRY, 56.2% (95%CI: 47.6-64.4) by Dr-WET, and 54.6% (95%CI: 46.1-62.9) by s-FTA. There was overall agreement of 70.8% between s-FTA and s-DRY samples (kappa = 0.34), and of 82.3% between self-HPV and Dr-WET samples (kappa = 0.56). Detection sensitivities for low-grade squamous intraepithelial lesion or worse (LSIL+) were: 64.0% (95%CI: 44.5-79.8) for s-FTA, 84.6% (95%CI: 66.5-93.9) for s-DRY, and 76.9% (95%CI: 58.0-89.0) for Dr-WET. The preferred self-collection method among patients was s-DRY (40.8% vs. 15.4%). Regarding costs, FTA card was five times more expensive than the swab (~5 US dollars (USD)/per card vs. ~1 USD/per swab). Self-HPV using dry swabs is sensitive for detecting LSIL+ and less expensive than s-FTA. International Standard Randomized Controlled Trial Number (ISRCTN): 43310942.

Investigating the Randomness of Numbers

Science.gov (United States)

Pendleton, Kenn L.

2009-01-01

The use of random numbers is pervasive in today's world. Random numbers have practical applications in such far-flung arenas as computer simulations, cryptography, gambling, the legal system, statistical sampling, and even the war on terrorism. Evaluating the randomness of extremely large samples is a complex, intricate process. However, the…

Dynamical implications of sample shape for avalanches in 2-dimensional random-field Ising model with saw-tooth domain wall

Science.gov (United States)

Tadić, Bosiljka

2018-03-01

We study dynamics of a built-in domain wall (DW) in 2-dimensional disordered ferromagnets with different sample shapes using random-field Ising model on a square lattice rotated by 45 degrees. The saw-tooth DW of the length Lx is created along one side and swept through the sample by slow ramping of the external field until the complete magnetisation reversal and the wall annihilation at the open top boundary at a distance Ly. By fixing the number of spins N =Lx ×Ly = 106 and the random-field distribution at a value above the critical disorder, we vary the ratio of the DW length to the annihilation distance in the range Lx /Ly ∈ [ 1 / 16 , 16 ] . The periodic boundary conditions are applied in the y-direction so that these ratios comprise different samples, i.e., surfaces of cylinders with the changing perimeter Lx and height Ly. We analyse the avalanches of the DW slips between following field updates, and the multifractal structure of the magnetisation fluctuation time series. Our main findings are that the domain-wall lengths materialised in different sample shapes have an impact on the dynamics at all scales. Moreover, the domain-wall motion at the beginning of the hysteresis loop (HLB) probes the disorder effects resulting in the fluctuations that are significantly different from the large avalanches in the central part of the loop (HLC), where the strong fields dominate. Specifically, the fluctuations in HLB exhibit a wide multi-fractal spectrum, which shifts towards higher values of the exponents when the DW length is reduced. The distributions of the avalanches in this segments of the loops obey power-law decay and the exponential cutoffs with the exponents firmly in the mean-field universality class for long DW. In contrast, the avalanches in the HLC obey Tsallis density distribution with the power-law tails which indicate the new categories of the scale invariant behaviour for different ratios Lx /Ly. The large fluctuations in the HLC, on the other

Jenis Sample: Keuntungan dan Kerugiannya

OpenAIRE

Suprapto, Agus

1994-01-01

Sample is a part of a population that are used in a study for purposes of making estimation about the nature of the total population that is obtained with sampling technic. Sampling technic is more adventagous than cencus because it can reduce cost, time, and it can gather deeper information and more accurate data. It is useful to distinguish two major types of sampling technics. First, Prob bility sampling i.e. simple random sampling. Second, Non Probability sampling i.e. systematic sam­plin...

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

Science.gov (United States)

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

Characteristics of men with substance use disorder consequent to illicit drug use: comparison of a random sample and volunteers.

Science.gov (United States)

Reynolds, Maureen D; Tarter, Ralph E; Kirisci, Levent

2004-09-06

Men qualifying for substance use disorder (SUD) consequent to consumption of an illicit drug were compared according to recruitment method. It was hypothesized that volunteers would be more self-disclosing and exhibit more severe disturbances compared to randomly recruited subjects. Personal, demographic, family, social, substance use, psychiatric, and SUD characteristics of volunteers (N = 146) were compared to randomly recruited (N = 102) subjects. Volunteers had lower socioceconomic status, were more likely to be African American, and had lower IQ than randomly recruited subjects. Volunteers also evidenced greater social and family maladjustment and more frequently had received treatment for substance abuse. In addition, lower social desirability response bias was observed in the volunteers. SUD was not more severe in the volunteers; however, they reported a higher lifetime rate of opiate, diet, depressant, and analgesic drug use. Volunteers and randomly recruited subjects qualifying for SUD consequent to illicit drug use are similar in SUD severity but differ in terms of severity of psychosocial disturbance and history of drug involvement. The factors discriminating volunteers and randomly recruited subjects are well known to impact on outcome, hence they need to be considered in research design, especially when selecting a sampling strategy in treatment research.

Random glucose is useful for individual prediction of type 2 diabetes: results of the Study of Health in Pomerania (SHIP).

Science.gov (United States)

Kowall, Bernd; Rathmann, Wolfgang; Giani, Guido; Schipf, Sabine; Baumeister, Sebastian; Wallaschofski, Henri; Nauck, Matthias; Völzke, Henry

2013-04-01

Random glucose is widely used in routine clinical practice. We investigated whether this non-standardized glycemic measure is useful for individual diabetes prediction. The Study of Health in Pomerania (SHIP), a population-based cohort study in north-east Germany, included 3107 diabetes-free persons aged 31-81 years at baseline in 1997-2001. 2475 persons participated at 5-year follow-up and gave self-reports of incident diabetes. For the total sample and for subjects aged ≥50 years, statistical properties of prediction models with and without random glucose were compared. A basic model (including age, sex, diabetes of parents, hypertension and waist circumference) and a comprehensive model (additionally including various lifestyle variables and blood parameters, but not HbA1c) performed statistically significantly better after adding random glucose (e.g., the area under the receiver-operating curve (AROC) increased from 0.824 to 0.856 after adding random glucose to the comprehensive model in the total sample). Likewise, adding random glucose to prediction models which included HbA1c led to significant improvements of predictive ability (e.g., for subjects ≥50 years, AROC increased from 0.824 to 0.849 after adding random glucose to the comprehensive model+HbA1c). Random glucose is useful for individual diabetes prediction, and improves prediction models including HbA1c. Copyright © 2012 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

Attenuation of species abundance distributions by sampling

Science.gov (United States)

Shimadzu, Hideyasu; Darnell, Ross

2015-01-01

Quantifying biodiversity aspects such as species presence/ absence, richness and abundance is an important challenge to answer scientific and resource management questions. In practice, biodiversity can only be assessed from biological material taken by surveys, a difficult task given limited time and resources. A type of random sampling, or often called sub-sampling, is a commonly used technique to reduce the amount of time and effort for investigating large quantities of biological samples. However, it is not immediately clear how (sub-)sampling affects the estimate of biodiversity aspects from a quantitative perspective. This paper specifies the effect of (sub-)sampling as attenuation of the species abundance distribution (SAD), and articulates how the sampling bias is induced to the SAD by random sampling. The framework presented also reveals some confusion in previous theoretical studies. PMID:26064626

Sampling Methods in Cardiovascular Nursing Research: An Overview.

Science.gov (United States)

Kandola, Damanpreet; Banner, Davina; O'Keefe-McCarthy, Sheila; Jassal, Debbie

2014-01-01

Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. The selection of specific participant samples is an important part of the research design and process. The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. There are two main categories of sampling methods: probability and non-probability. Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. There are five main types of probability sampling including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. Each approach offers distinct advantages and disadvantages and must be considered critically. In this research column, we provide an introduction to these key sampling techniques and draw on examples from the cardiovascular research. Understanding the differences in sampling techniques may aid nurses in effective appraisal of research literature and provide a reference pointfor nurses who engage in cardiovascular research.

Sampling strategies to measure the prevalence of common recurrent infections in longitudinal studies

Directory of Open Access Journals (Sweden)

Luby Stephen P

2010-08-01

Full Text Available Abstract Background Measuring recurrent infections such as diarrhoea or respiratory infections in epidemiological studies is a methodological challenge. Problems in measuring the incidence of recurrent infections include the episode definition, recall error, and the logistics of close follow up. Longitudinal prevalence (LP, the proportion-of-time-ill estimated by repeated prevalence measurements, is an alternative measure to incidence of recurrent infections. In contrast to incidence which usually requires continuous sampling, LP can be measured at intervals. This study explored how many more participants are needed for infrequent sampling to achieve the same study power as frequent sampling. Methods We developed a set of four empirical simulation models representing low and high risk settings with short or long episode durations. The model was used to evaluate different sampling strategies with different assumptions on recall period and recall error. Results The model identified three major factors that influence sampling strategies: (1 the clustering of episodes in individuals; (2 the duration of episodes; (3 the positive correlation between an individual's disease incidence and episode duration. Intermittent sampling (e.g. 12 times per year often requires only a slightly larger sample size compared to continuous sampling, especially in cluster-randomized trials. The collection of period prevalence data can lead to highly biased effect estimates if the exposure variable is associated with episode duration. To maximize study power, recall periods of 3 to 7 days may be preferable over shorter periods, even if this leads to inaccuracy in the prevalence estimates. Conclusion Choosing the optimal approach to measure recurrent infections in epidemiological studies depends on the setting, the study objectives, study design and budget constraints. Sampling at intervals can contribute to making epidemiological studies and trials more efficient, valid

Network Sampling with Memory: A proposal for more efficient sampling from social networks

Science.gov (United States)

Mouw, Ted; Verdery, Ashton M.

2013-01-01

Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246

Randomized, interventional, prospective, comparative study to ...

African Journals Online (AJOL)

Randomized, interventional, prospective, comparative study to evaluate the antihypertensive efficacy and tolerability of ramipril versus telmisartan in stage 1 hypertensive patients with diabetes mellitus.

[Identification and sampling of people with migration background for epidemiological studies in Germany].

Science.gov (United States)

Reiss, K; Makarova, N; Spallek, J; Zeeb, H; Razum, O

2013-06-01

In 2009, 19.6% of the population of Germany either had migrated themselves or were the offspring of people with migration experience. Migrants differ from the autochthonous German population in terms of health status, health awareness and health behaviour. To further investigate the health situation of migrants in Germany, epidemiological studies are needed. Such studies can employ existing databases which provide detailed information on migration status. Otherwise, onomastic or toponomastic procedures can be applied to identify people with migration background. If migrants have to be recruited into an epidemiological study, this can be done register-based (e. g., data from registration offices or telephone lists), based on residential location (random-route or random-walk procedure), via snowball sampling (e. g., through key persons) or via settings (e. g., school entry examination). An oversampling of people with migration background is not sufficient to avoid systematic bias in the sample due to non-participation. Additional measures have to be taken to increase access and raise participation rates. Personal contacting, multilingual instruments, multilingual interviewers and extensive public relations increase access and willingness to participate. Empirical evidence on 'successful' recruitment strategies for studies with migrants is still lacking in epidemiology and health sciences in Germany. The choice of the recruitment strategy as well as the measures to raise accessibility and willingness to participate depend on the available resources, the research question and the specific migrant target group. © Georg Thieme Verlag KG Stuttgart · New York.

[Study of spatial stratified sampling strategy of Oncomelania hupensis snail survey based on plant abundance].

Science.gov (United States)

Xun-Ping, W; An, Z

2017-07-27

Objective To optimize and simplify the survey method of Oncomelania hupensis snails in marshland endemic regions of schistosomiasis, so as to improve the precision, efficiency and economy of the snail survey. Methods A snail sampling strategy (Spatial Sampling Scenario of Oncomelania based on Plant Abundance, SOPA) which took the plant abundance as auxiliary variable was explored and an experimental study in a 50 m×50 m plot in a marshland in the Poyang Lake region was performed. Firstly, the push broom surveyed data was stratified into 5 layers by the plant abundance data; then, the required numbers of optimal sampling points of each layer through Hammond McCullagh equation were calculated; thirdly, every sample point in the line with the Multiple Directional Interpolation (MDI) placement scheme was pinpointed; and finally, the comparison study among the outcomes of the spatial random sampling strategy, the traditional systematic sampling method, the spatial stratified sampling method, Sandwich spatial sampling and inference and SOPA was performed. Results The method (SOPA) proposed in this study had the minimal absolute error of 0.213 8; and the traditional systematic sampling method had the largest estimate, and the absolute error was 0.924 4. Conclusion The snail sampling strategy (SOPA) proposed in this study obtains the higher estimation accuracy than the other four methods.

Applications of Asymptotic Sampling on High Dimensional Structural Dynamic Problems

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Bucher, Christian

2011-01-01

The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has consid...... dimensional reliability problems in structural dynamics.......The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has...... is minimized. Next, the method is applied on different cases of linear and nonlinear systems with a large number of random variables representing the dynamic excitation. The results show that asymptotic sampling is capable of providing good approximations of low failure probability events for very high...

Methodology Series Module 5: Sampling Strategies

OpenAIRE

Setia, Maninder Singh

2016-01-01

Once the research question and the research design have been finalised, it is important to select the appropriate sample for the study. The method by which the researcher selects the sample is the ? Sampling Method?. There are essentially two types of sampling methods: 1) probability sampling ? based on chance events (such as random numbers, flipping a coin etc.); and 2) non-probability sampling ? based on researcher's choice, population that accessible & available. Some of the non-probabilit...

Missing citations due to exact reference matching: Analysis of a random sample from WoS. Are publications from peripheral countries disadvantaged?

Energy Technology Data Exchange (ETDEWEB)

Donner, P.

2016-07-01

Citation counts of scientific research contributions are one fundamental data in scientometrics. Accuracy and completeness of citation links are therefore crucial data quality issues (Moed, 2005, Ch. 13). However, despite the known flaws of reference matching algorithms, usually no attempts are made to incorporate uncertainty about citation counts into indicators. This study is a step towards that goal. Particular attention is paid to the question whether publications from countries not using basic Latin script are differently affected by missed citations. The proprietary reference matching procedure of Web of Science (WoS) is based on (near) exact agreement of cited reference data (normalized during processing) to the target papers bibliographical data. Consequently, the procedure has near-optimal precision but incomplete recall - it is known to miss some slightly inaccurate reference links (Olensky, 2015). However, there has been no attempt so far to estimate the rate of missed citations by a principled method for a random sample. For this study a simple random sample of WoS source papers was drawn and it was attempted to find all reference strings of WoS indexed documents that refer to them, in particular inexact matches. The objective is to give a statistical estimate of the proportion of missed citations and to describe the relationship of the number of found citations to the number of missed citations, i.e. the conditional error distribution. The empirical error distribution is statistically analyzed and modelled. (Author)

Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation Methods.

Directory of Open Access Journals (Sweden)

Nawar Shara

Full Text Available Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS. Studying these conditions simultaneously in longitudinal studies is challenging, because the morbidity and mortality associated with these diseases result in missing data, and these data are likely not missing at random. When such data are merely excluded, study findings may be compromised. In this article, a subset of 2264 participants with complete renal function data from Strong Heart Exams 1 (1989-1991, 2 (1993-1995, and 3 (1998-1999 was used to examine the performance of five methods used to impute missing data: listwise deletion, mean of serial measures, adjacent value, multiple imputation, and pattern-mixture. Three missing at random models and one non-missing at random model were used to compare the performance of the imputation techniques on randomly and non-randomly missing data. The pattern-mixture method was found to perform best for imputing renal function data that were not missing at random. Determining whether data are missing at random or not can help in choosing the imputation method that will provide the most accurate results.

Importance sampling of heavy-tailed iterated random functions

NARCIS (Netherlands)

B. Chen (Bohan); C.H. Rhee (Chang-Han); A.P. Zwart (Bert)

2016-01-01

textabstractWe consider a stochastic recurrence equation of the form $Z_{n+1} = A_{n+1} Z_n+B_{n+1}$, where $\\mathbb{E}[\\log A_1]<0$, $\\mathbb{E}[\\log^+ B_1]<\\infty$ and $\\{(A_n,B_n)\\}_{n\\in\\mathbb{N}}$ is an i.i.d. sequence of positive random vectors. The stationary distribution of this Markov

Estimating HIES Data through Ratio and Regression Methods for Different Sampling Designs

Directory of Open Access Journals (Sweden)

Faqir Muhammad

2007-01-01

Full Text Available In this study, comparison has been made for different sampling designs, using the HIES data of North West Frontier Province (NWFP for 2001-02 and 1998-99 collected from the Federal Bureau of Statistics, Statistical Division, Government of Pakistan, Islamabad. The performance of the estimators has also been considered using bootstrap and Jacknife. A two-stage stratified random sample design is adopted by HIES. In the first stage, enumeration blocks and villages are treated as the first stage Primary Sampling Units (PSU. The sample PSU’s are selected with probability proportional to size. Secondary Sampling Units (SSU i.e., households are selected by systematic sampling with a random start. They have used a single study variable. We have compared the HIES technique with some other designs, which are: Stratified Simple Random Sampling. Stratified Systematic Sampling. Stratified Ranked Set Sampling. Stratified Two Phase Sampling. Ratio and Regression methods were applied with two study variables, which are: Income (y and Household sizes (x. Jacknife and Bootstrap are used for variance replication. Simple Random Sampling with sample size (462 to 561 gave moderate variances both by Jacknife and Bootstrap. By applying Systematic Sampling, we received moderate variance with sample size (467. In Jacknife with Systematic Sampling, we obtained variance of regression estimator greater than that of ratio estimator for a sample size (467 to 631. At a sample size (952 variance of ratio estimator gets greater than that of regression estimator. The most efficient design comes out to be Ranked set sampling compared with other designs. The Ranked set sampling with jackknife and bootstrap, gives minimum variance even with the smallest sample size (467. Two Phase sampling gave poor performance. Multi-stage sampling applied by HIES gave large variances especially if used with a single study variable.

Randomized Comparison of Two Vaginal Self-Sampling Methods for Human Papillomavirus Detection: Dry Swab versus FTA Cartridge.

Directory of Open Access Journals (Sweden)

Rosa Catarino

Full Text Available Human papillomavirus (HPV self-sampling (self-HPV is valuable in cervical cancer screening. HPV testing is usually performed on physician-collected cervical smears stored in liquid-based medium. Dry filters and swabs are an alternative. We evaluated the adequacy of self-HPV using two dry storage and transport devices, the FTA cartridge and swab.A total of 130 women performed two consecutive self-HPV samples. Randomization determined which of the two tests was performed first: self-HPV using dry swabs (s-DRY or vaginal specimen collection using a cytobrush applied to an FTA cartridge (s-FTA. After self-HPV, a physician collected a cervical sample using liquid-based medium (Dr-WET. HPV types were identified by real-time PCR. Agreement between collection methods was measured using the kappa statistic.HPV prevalence for high-risk types was 62.3% (95%CI: 53.7-70.2 detected by s-DRY, 56.2% (95%CI: 47.6-64.4 by Dr-WET, and 54.6% (95%CI: 46.1-62.9 by s-FTA. There was overall agreement of 70.8% between s-FTA and s-DRY samples (kappa = 0.34, and of 82.3% between self-HPV and Dr-WET samples (kappa = 0.56. Detection sensitivities for low-grade squamous intraepithelial lesion or worse (LSIL+ were: 64.0% (95%CI: 44.5-79.8 for s-FTA, 84.6% (95%CI: 66.5-93.9 for s-DRY, and 76.9% (95%CI: 58.0-89.0 for Dr-WET. The preferred self-collection method among patients was s-DRY (40.8% vs. 15.4%. Regarding costs, FTA card was five times more expensive than the swab (~5 US dollars (USD/per card vs. ~1 USD/per swab.Self-HPV using dry swabs is sensitive for detecting LSIL+ and less expensive than s-FTA.International Standard Randomized Controlled Trial Number (ISRCTN: 43310942.

A Bayesian Method for Weighted Sampling

OpenAIRE

Lo, Albert Y.

1993-01-01

Bayesian statistical inference for sampling from weighted distribution models is studied. Small-sample Bayesian bootstrap clone (BBC) approximations to the posterior distribution are discussed. A second-order property for the BBC in unweighted i.i.d. sampling is given. A consequence is that BBC approximations to a posterior distribution of the mean and to the sampling distribution of the sample average, can be made asymptotically accurate by a proper choice of the random variables that genera...

Power Spectrum Estimation of Randomly Sampled Signals

DEFF Research Database (Denmark)

Velte, C. M.; Buchhave, P.; K. George, W.

algorithms; sample and-hold and the direct spectral estimator without residence time weighting. The computer generated signal is a Poisson process with a sample rate proportional to velocity magnitude that consist of well-defined frequency content, which makes bias easy to spot. The idea...

Application of bias factor method using random sampling technique for prediction accuracy improvement of critical eigenvalue of BWR

International Nuclear Information System (INIS)

Ito, Motohiro; Endo, Tomohiro; Yamamoto, Akio; Kuroda, Yusuke; Yoshii, Takashi

2017-01-01

The bias factor method based on the random sampling technique is applied to the benchmark problem of Peach Bottom Unit 2. Validity and availability of the present method, i.e. correction of calculation results and reduction of uncertainty, are confirmed in addition to features and performance of the present method. In the present study, core characteristics in cycle 3 are corrected with the proposed method using predicted and 'measured' critical eigenvalues in cycles 1 and 2. As the source of uncertainty, variance-covariance of cross sections is considered. The calculation results indicate that bias between predicted and measured results, and uncertainty owing to cross section can be reduced. Extension to other uncertainties such as thermal hydraulics properties will be a future task. (author)

A Monte Carlo study of adsorption of random copolymers on random surfaces

CERN Document Server

Moghaddam, M S

2003-01-01

We study the adsorption problem of a random copolymer on a random surface in which a self-avoiding walk in three dimensions interacts with a plane defining a half-space to which the walk is confined. Each vertex of the walk is randomly labelled A with probability p sub p or B with probability 1 - p sub p , and only vertices labelled A are attracted to the surface plane. Each lattice site on the plane is also labelled either A with probability p sub s or B with probability 1 - p sub s , and only lattice sites labelled A interact with the walk. We study two variations of this model: in the first case the A-vertices of the walk interact only with the A-sites on the surface. In the second case the constraint of selective binding is removed; that is, any contact between the walk and the surface that involves an A-labelling, either from the surface or from the walk, is counted as a visit to the surface. The system is quenched in both cases, i.e. the labellings of the walk and of the surface are fixed as thermodynam...

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling.

Science.gov (United States)

Zhou, Fuqun; Zhang, Aining

2016-10-25

Nowadays, various time-series Earth Observation data with multiple bands are freely available, such as Moderate Resolution Imaging Spectroradiometer (MODIS) datasets including 8-day composites from NASA, and 10-day composites from the Canada Centre for Remote Sensing (CCRS). It is challenging to efficiently use these time-series MODIS datasets for long-term environmental monitoring due to their vast volume and information redundancy. This challenge will be greater when Sentinel 2-3 data become available. Another challenge that researchers face is the lack of in-situ data for supervised modelling, especially for time-series data analysis. In this study, we attempt to tackle the two important issues with a case study of land cover mapping using CCRS 10-day MODIS composites with the help of Random Forests' features: variable importance, outlier identification. The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring sample data available from one year to an adjacent year for supervised classification modelling. The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to that generated using the full dataset. The proposed simple but effective solution of sample transferring could make supervised modelling possible for applications lacking sample data.

A large-scale study of the random variability of a coding sequence: a study on the CFTR gene.

Science.gov (United States)

Modiano, Guido; Bombieri, Cristina; Ciminelli, Bianca Maria; Belpinati, Francesca; Giorgi, Silvia; Georges, Marie des; Scotet, Virginie; Pompei, Fiorenza; Ciccacci, Cinzia; Guittard, Caroline; Audrézet, Marie Pierre; Begnini, Angela; Toepfer, Michael; Macek, Milan; Ferec, Claude; Claustres, Mireille; Pignatti, Pier Franco

2005-02-01

Coding single nucleotide substitutions (cSNSs) have been studied on hundreds of genes using small samples (n(g) approximately 100-150 genes). In the present investigation, a large random European population sample (average n(g) approximately 1500) was studied for a single gene, the CFTR (Cystic Fibrosis Transmembrane conductance Regulator). The nonsynonymous (NS) substitutions exhibited, in accordance with previous reports, a mean probability of being polymorphic (q > 0.005), much lower than that of the synonymous (S) substitutions, but they showed a similar rate of subpolymorphic (q < 0.005) variability. This indicates that, in autosomal genes that may have harmful recessive alleles (nonduplicated genes with important functions), genetic drift overwhelms selection in the subpolymorphic range of variability, making disadvantageous alleles behave as neutral. These results imply that the majority of the subpolymorphic nonsynonymous alleles of these genes are selectively negative or even pathogenic.

Levels of dioxin (PCDD/F) and PCBs in a random sample of Australian aquaculture-produced Southern Bluefin Tuna (Thunnus maccoyii)

Energy Technology Data Exchange (ETDEWEB)

Padula, D.; Madigan, T.; Kiermeier, A.; Daughtry, B.; Pointon, A. [South Australian Research and Development Inst. (Australia)

2004-09-15

To date there has been no published information available on the levels of dioxin (PCDD/F) and PCBs in Australian aquaculture-produced Southern Bluefin Tuna (Thunnus maccoyii). Southern Bluefin Tuna are commercially farmed off the coast of Port Lincoln in the state of South Australia, Australia. This paper reports the levels of dioxin (PCDD/F) and PCBs in muscle tissue samples from 11 randomly sampled aquaculture-produced Southern Bluefin Tuna collected in 2003. Little published data exists on the levels of dioxin (PCDD/F) and PCBs in Australian aquacultureproduced seafood. Wild tuna are first caught in the Great Australian Bight in South Australian waters, and are then brought back to Port Lincoln where they are ranched in sea-cages before being harvested and exported to Japan. The aim of the study was to identify pathways whereby contaminants such as dioxin (PCDD/F) and PCBs may enter the aquaculture production system. This involved undertaking a through chain analysis of the levels of dioxin (PCDD/F) and PCBs in wild caught tuna, seafloor sediment samples from the marine environment, levels in feeds and final harvested exported product. Detailed study was also undertaken on the variation of dioxin (PCDD/F) and PCBs across individual tuna carcases. This paper addresses the levels found in final harvested product. Details on levels found in other studies will be published elsewhere shortly.

Empirically simulated study to compare and validate sampling methods used in aerial surveys of wildlife populations

NARCIS (Netherlands)

Khaemba, W.M.; Stein, A.; Rasch, D.; Leeuw, de J.; Georgiadis, N.

2001-01-01

This paper compares the distribution, sampling and estimation of abundance for two animal species in an African ecosystem by means of an intensive simulation of the sampling process under a geographical information system (GIS) environment. It focuses on systematic and random sampling designs,

The contribution of simple random sampling to observed variations in faecal egg counts.

Science.gov (United States)

Torgerson, Paul R; Paul, Michaela; Lewis, Fraser I

2012-09-10

It has been over 100 years since the classical paper published by Gosset in 1907, under the pseudonym "Student", demonstrated that yeast cells suspended in a fluid and measured by a haemocytometer conformed to a Poisson process. Similarly parasite eggs in a faecal suspension also conform to a Poisson process. Despite this there are common misconceptions how to analyse or interpret observations from the McMaster or similar quantitative parasitic diagnostic techniques, widely used for evaluating parasite eggs in faeces. The McMaster technique can easily be shown from a theoretical perspective to give variable results that inevitably arise from the random distribution of parasite eggs in a well mixed faecal sample. The Poisson processes that lead to this variability are described and illustrative examples of the potentially large confidence intervals that can arise from observed faecal eggs counts that are calculated from the observations on a McMaster slide. Attempts to modify the McMaster technique, or indeed other quantitative techniques, to ensure uniform egg counts are doomed to failure and belie ignorance of Poisson processes. A simple method to immediately identify excess variation/poor sampling from replicate counts is provided. Copyright © 2012 Elsevier B.V. All rights reserved.

An R package for spatial coverage sampling and random sampling from compact geographical strata by k-means

NARCIS (Netherlands)

Walvoort, D.J.J.; Brus, D.J.; Gruijter, de J.J.

2010-01-01

Both for mapping and for estimating spatial means of an environmental variable, the accuracy of the result will usually be increased by dispersing the sample locations so that they cover the study area as uniformly as possible. We developed a new R package for designing spatial coverage samples for

Neurofeedback Against Binge Eating: A Randomized Controlled Trial in a Female Subclinical Threshold Sample.

Science.gov (United States)

Schmidt, Jennifer; Martin, Alexandra

2016-09-01

Brain-directed treatment techniques, such as neurofeedback, have recently been proposed as adjuncts in the treatment of eating disorders to improve therapeutic outcomes. In line with this recommendation, a cue exposure EEG-neurofeedback protocol was developed. The present study aimed at the evaluation of the specific efficacy of neurofeedback to reduce subjective binge eating in a female subthreshold sample. A total of 75 subjects were randomized to EEG-neurofeedback, mental imagery with a comparable treatment set-up or a waitlist group. At post-treatment, only EEG-neurofeedback led to a reduced frequency of binge eating (p = .015, g = 0.65). The effects remained stable to a 3-month follow-up. EEG-neurofeedback further showed particular beneficial effects on perceived stress and dietary self-efficacy. Differences in outcomes did not arise from divergent treatment expectations. Because EEG-neurofeedback showed a specific efficacy, it may be a promising brain-directed approach that should be tested as a treatment adjunct in clinical groups with binge eating. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

Sample design effects in landscape genetics

Science.gov (United States)

Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.

2012-01-01

An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.

Toward a Principled Sampling Theory for Quasi-Orders.

Science.gov (United States)

Ünlü, Ali; Schrepp, Martin

2016-01-01

Quasi-orders, that is, reflexive and transitive binary relations, have numerous applications. In educational theories, the dependencies of mastery among the problems of a test can be modeled by quasi-orders. Methods such as item tree or Boolean analysis that mine for quasi-orders in empirical data are sensitive to the underlying quasi-order structure. These data mining techniques have to be compared based on extensive simulation studies, with unbiased samples of randomly generated quasi-orders at their basis. In this paper, we develop techniques that can provide the required quasi-order samples. We introduce a discrete doubly inductive procedure for incrementally constructing the set of all quasi-orders on a finite item set. A randomization of this deterministic procedure allows us to generate representative samples of random quasi-orders. With an outer level inductive algorithm, we consider the uniform random extensions of the trace quasi-orders to higher dimension. This is combined with an inner level inductive algorithm to correct the extensions that violate the transitivity property. The inner level correction step entails sampling biases. We propose three algorithms for bias correction and investigate them in simulation. It is evident that, on even up to 50 items, the new algorithms create close to representative quasi-order samples within acceptable computing time. Hence, the principled approach is a significant improvement to existing methods that are used to draw quasi-orders uniformly at random but cannot cope with reasonably large item sets.

Toward a Principled Sampling Theory for Quasi-Orders

Science.gov (United States)

Ünlü, Ali; Schrepp, Martin

2016-01-01

Quasi-orders, that is, reflexive and transitive binary relations, have numerous applications. In educational theories, the dependencies of mastery among the problems of a test can be modeled by quasi-orders. Methods such as item tree or Boolean analysis that mine for quasi-orders in empirical data are sensitive to the underlying quasi-order structure. These data mining techniques have to be compared based on extensive simulation studies, with unbiased samples of randomly generated quasi-orders at their basis. In this paper, we develop techniques that can provide the required quasi-order samples. We introduce a discrete doubly inductive procedure for incrementally constructing the set of all quasi-orders on a finite item set. A randomization of this deterministic procedure allows us to generate representative samples of random quasi-orders. With an outer level inductive algorithm, we consider the uniform random extensions of the trace quasi-orders to higher dimension. This is combined with an inner level inductive algorithm to correct the extensions that violate the transitivity property. The inner level correction step entails sampling biases. We propose three algorithms for bias correction and investigate them in simulation. It is evident that, on even up to 50 items, the new algorithms create close to representative quasi-order samples within acceptable computing time. Hence, the principled approach is a significant improvement to existing methods that are used to draw quasi-orders uniformly at random but cannot cope with reasonably large item sets. PMID:27965601

Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study.

Science.gov (United States)

Collado, María Carmen; Engen, Phillip A; Bandín, Cristina; Cabrera-Rubio, Raúl; Voigt, Robin M; Green, Stefan J; Naqib, Ankur; Keshavarzian, Ali; Scheer, Frank A J L; Garaulet, Marta

2018-04-01

The composition of the diet (what we eat) has been widely related to the microbiota profile. However, whether the timing of food consumption (when we eat) influences microbiota in humans is unknown. A randomized, crossover study was performed in 10 healthy normal-weight young women to test the effect of the timing of food intake on the human microbiota in the saliva and fecal samples. More specifically, to determine whether eating late alters daily rhythms of human salivary microbiota, we interrogated salivary microbiota in samples obtained at 4 specific time points over 24 h, to achieve a better understanding of the relationship between food timing and metabolic alterations in humans. Results revealed significant diurnal rhythms in salivary diversity and bacterial relative abundance ( i.e., TM7 and Fusobacteria) across both early and late eating conditions. More importantly, meal timing affected diurnal rhythms in diversity of salivary microbiota toward an inverted rhythm between the eating conditions, and eating late increased the number of putative proinflammatory taxa, showing a diurnal rhythm in the saliva. In a randomized, crossover study, we showed for the first time the impact of the timing of food intake on human salivary microbiota. Eating the main meal late inverts the daily rhythm of salivary microbiota diversity which may have a deleterious effect on the metabolism of the host.-Collado, M. C., Engen, P. A., Bandín, C., Cabrera-Rubio, R., Voigt, R. M., Green, S. J., Naqib, A., Keshavarzian, A., Scheer, F. A. J. L., Garaulet, M. Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study.

A shared frailty model for case-cohort samples: parent and offspring relations in an adoption study

DEFF Research Database (Denmark)

Petersen, Liselotte; Sørensen, Thorkild I A; Andersen, Per Kragh

2010-01-01

of their biological and adoptive parents were collected with the purpose of studying the association of survival between the adoptee and his/her biological or adoptive parents. Motivated by this study, we explored how to make inference in a shared frailty model for case-cohort data. Our approach was to use inverse......The Danish adoption register contains data on the 12 301 Danish nonfamilial adoptions during 1924-1947. From that register a case-cohort sample was selected consisting of all case adoptees, that is those adoptees dying before age 70 years, and a random sample of 1683 adoptees. The survival data...... probability weighting to account for the sampling in a conditional, shared frailty Poisson model and to use the robust variance estimator proposed by Moger et al. (Statist. Med. 2008; 27:1062-1074).To explore the performance of the estimation procedure, a simulation study was conducted. We studied situations...

42 CFR 431.814 - Sampling plan and procedures.

Science.gov (United States)

2010-10-01

... reliability of the reduced sample. (4) The sample selection procedure. Systematic random sampling is... sampling, and yield estimates with the same or better precision than achieved in systematic random sampling... 42 Public Health 4 2010-10-01 2010-10-01 false Sampling plan and procedures. 431.814 Section 431...

Improved sampling and analysis of images in corneal confocal microscopy.

Science.gov (United States)

Schaldemose, E L; Fontain, F I; Karlsson, P; Nyengaard, J R

2017-10-01

Corneal confocal microscopy (CCM) is a noninvasive clinical method to analyse and quantify corneal nerve fibres in vivo. Although the CCM technique is in constant progress, there are methodological limitations in terms of sampling of images and objectivity of the nerve quantification. The aim of this study was to present a randomized sampling method of the CCM images and to develop an adjusted area-dependent image analysis. Furthermore, a manual nerve fibre analysis method was compared to a fully automated method. 23 idiopathic small-fibre neuropathy patients were investigated using CCM. Corneal nerve fibre length density (CNFL) and corneal nerve fibre branch density (CNBD) were determined in both a manual and automatic manner. Differences in CNFL and CNBD between (1) the randomized and the most common sampling method, (2) the adjusted and the unadjusted area and (3) the manual and automated quantification method were investigated. The CNFL values were significantly lower when using the randomized sampling method compared to the most common method (p = 0.01). There was not a statistical significant difference in the CNBD values between the randomized and the most common sampling method (p = 0.85). CNFL and CNBD values were increased when using the adjusted area compared to the standard area. Additionally, the study found a significant increase in the CNFL and CNBD values when using the manual method compared to the automatic method (p ≤ 0.001). The study demonstrated a significant difference in the CNFL values between the randomized and common sampling method indicating the importance of clear guidelines for the image sampling. The increase in CNFL and CNBD values when using the adjusted cornea area is not surprising. The observed increases in both CNFL and CNBD values when using the manual method of nerve quantification compared to the automatic method are consistent with earlier findings. This study underlines the importance of improving the analysis of the

Sample size in qualitative interview studies

DEFF Research Database (Denmark)

Malterud, Kirsti; Siersma, Volkert Dirk; Guassora, Ann Dorrit Kristiane

2016-01-01

Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is “saturation.” Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose...... the concept “information power” to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power...... and during data collection of a qualitative study is discussed....

Stratified random sampling plans designed to assist in the determination of radon and radon daughter concentrations in underground uranium mine atmosphere

International Nuclear Information System (INIS)

Makepeace, C.E.

1981-01-01

Sampling strategies for the monitoring of deleterious agents present in uranium mine air in underground and surface mining areas are described. These methods are designed to prevent overexposure of the lining of the respiratory system of uranium miners to ionizing radiation from radon and radon daughters, and whole body overexposure to external gamma radiation. A detailed description is provided of stratified random sampling monitoring methodology for obtaining baseline data to be used as a reference for subsequent compliance assessment

Randomized controlled trial of attention bias modification in a racially diverse, socially anxious, alcohol dependent sample.

Science.gov (United States)

Clerkin, Elise M; Magee, Joshua C; Wells, Tony T; Beard, Courtney; Barnett, Nancy P

2016-12-01

Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Adult participants (N = 86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. Copyright © 2016 Elsevier Ltd. All rights reserved.

Randomized Controlled Trial of Attention Bias Modification in a Racially Diverse, Socially Anxious, Alcohol Dependent Sample

Science.gov (United States)

Clerkin, Elise M.; Magee, Joshua C.; Wells, Tony T.; Beard, Courtney; Barnett, Nancy P.

2016-01-01

Objective Attention biases may be an important treatment target for both alcohol dependence and social anxiety. This is the first ABM trial to investigate two (vs. one) targets of attention bias within a sample with co-occurring symptoms of social anxiety and alcohol dependence. Additionally, we used trial-level bias scores (TL-BS) to capture the phenomena of attention bias in a more ecologically valid, dynamic way compared to traditional attention bias scores. Method Adult participants (N=86; 41% Female; 52% African American; 40% White) with elevated social anxiety symptoms and alcohol dependence were randomly assigned to an 8-session training condition in this 2 (Social Anxiety ABM vs. Social Anxiety Control) by 2 (Alcohol ABM vs. Alcohol Control) design. Symptoms of social anxiety, alcohol dependence, and attention bias were assessed across time. Results Multilevel models estimated the trajectories for each measure within individuals, and tested whether these trajectories differed according to the randomized training conditions. Across time, there were significant or trending decreases in all attention TL-BS parameters (but not traditional attention bias scores) and most symptom measures. However, there were not significant differences in the trajectories of change between any ABM and control conditions for any symptom measures. Conclusions These findings add to previous evidence questioning the robustness of ABM and point to the need to extend the effects of ABM to samples that are racially diverse and/or have co-occurring psychopathology. The results also illustrate the potential importance of calculating trial-level attention bias scores rather than only including traditional bias scores. PMID:27591918

Saffron improved depression and reduced homocysteine level in patients with major depression: A Randomized, double-blind study

Directory of Open Access Journals (Sweden)

Gholamali Jelodar

2017-12-01

Full Text Available Objectives: A correlation between hyperhomocysteinemia, and depression has been reported. Saffron (Crocus sativus is recommended for treatment of depression; hence, in this study the effect of co-administration of saffron and fluoxetine on plasma homocysteine and depression was evaluated. Material and methods: This was a 4-week randomized and double-blind clinical trial which was conducted from March 2013 to February 2014. In this trial, 40 male and females (20-55 years old diagnosed with severe depression were selected and following filing the Beck form, were randomly divided into two groups.  Experimental group was treated with fluoxetine 20 mg/day and saffron 30 mg /day and the control group received placebo and fluoxetine 20 mg/day for four weeks. Before treatment and at the end of the study, fasting blood samples were collected. For females, blood samples were collected on the third day of their menstrual cycle. Results: A significant reduction of homocysteine levels was observed in both sex in the experimental group compared to before treatment (p

Rapid, easy, and cheap randomization: prospective evaluation in a study cohort

Directory of Open Access Journals (Sweden)

Parker Melissa J

2012-06-01

Full Text Available Abstract Background When planning a randomized controlled trial (RCT, investigators must select randomization and allocation procedures based upon a variety of factors. While third party randomization is cited as being among the most desirable randomization processes, many third party randomization procedures are neither feasible nor cost-effective for small RCTs, including pilot RCTs. In this study we present our experience with a third party randomization and allocation procedure that utilizes current technology to achieve randomization in a rapid, reliable, and cost-effective manner. Methods This method was developed by the investigators for use in a small 48-participant parallel group RCT with four study arms. As a nested study, the reliability of this randomization procedure was prospectively evaluated in this cohort. The primary outcome of this nested study was the proportion of subjects for whom allocation information was obtained by the Research Assistant within 15 min of the initial participant randomization request. A secondary outcome was the average time for communicating participant group assignment back to the Research Assistant. Descriptive information regarding any failed attempts at participant randomization as well as costs attributable to use of this method were also recorded. Statistical analyses included the calculation of simple proportions and descriptive statistics. Results Forty-eight participants were successfully randomized and group allocation instruction was received for 46 (96% within 15 min of the Research Assistant placing the initial randomization request. Time elapsed in minutes until receipt of participant allocation instruction was Mean (SD 3.1 +/− 3.6; Median (IQR 2 (2,3; Range (1–20 for the entire cohort of 48. For the two participants for whom group allocation information was not received by the Research Assistant within the 15-min pass threshold, this information was obtained following a second

Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation.

Directory of Open Access Journals (Sweden)

Jennifer L Smith

Full Text Available Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF, generally collected using the recommended gold-standard cluster randomized surveys (CRS. Integrated Threshold Mapping (ITM has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1-9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters.Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i the district prevalence of TF; (ii the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii the enrollment rate in schools.Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates

Comparison of sampling methods for hard-to-reach francophone populations: yield and adequacy of advertisement and respondent-driven sampling.

Science.gov (United States)

Ngwakongnwi, Emmanuel; King-Shier, Kathryn M; Hemmelgarn, Brenda R; Musto, Richard; Quan, Hude

2014-01-01

Francophones who live outside the primarily French-speaking province of Quebec, Canada, risk being excluded from research by lack of a sampling frame. We examined the adequacy of random sampling, advertising, and respondent-driven sampling for recruitment of francophones for survey research. We recruited francophones residing in the city of Calgary, Alberta, through advertising and respondentdriven sampling. These 2 samples were then compared with a random subsample of Calgary francophones derived from the 2006 Canadian Community Health Survey (CCHS). We assessed the effectiveness of advertising and respondent-driven sampling in relation to the CCHS sample by comparing demographic characteristics and selected items from the CCHS (specifically self-reported general health status, perceived weight, and having a family doctor). We recruited 120 francophones through advertising and 145 through respondent-driven sampling; the random sample from the CCHS consisted of 259 records. The samples derived from advertising and respondentdriven sampling differed from the CCHS in terms of age (mean ages 41.0, 37.6, and 42.5 years, respectively), sex (proportion of males 26.1%, 40.6%, and 56.6%, respectively), education (college or higher 86.7% , 77.9% , and 59.1%, respectively), place of birth (immigrants accounting for 45.8%, 55.2%, and 3.7%, respectively), and not having a regular medical doctor (16.7%, 34.5%, and 16.6%, respectively). Differences were not tested statistically because of limitations on the analysis of CCHS data imposed by Statistics Canada. The samples generated exclusively through advertising and respondent-driven sampling were not representative of the gold standard sample from the CCHS. Use of such biased samples for research studies could generate misleading results.

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

Science.gov (United States)

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.

Quantification of damage in DNA recovered from highly degraded samples – a case study on DNA in faeces

Directory of Open Access Journals (Sweden)

Eveson J Paige

2006-08-01

Full Text Available Abstract Background Poorly preserved biological tissues have become an important source of DNA for a wide range of zoological studies. Measuring the quality of DNA obtained from these samples is often desired; however, there are no widely used techniques available for quantifying damage in highly degraded DNA samples. We present a general method that can be used to determine the frequency of polymerase blocking DNA damage in specific gene-regions in such samples. The approach uses quantitative PCR to measure the amount of DNA present at several fragment sizes within a sample. According to a model of random degradation the amount of available template will decline exponentially with increasing fragment size in damaged samples, and the frequency of DNA damage (λ can be estimated by determining the rate of decline. Results The method is illustrated through the analysis of DNA extracted from sea lion faecal samples. Faeces contain a complex mixture of DNA from several sources and different components are expected to be differentially degraded. We estimated the frequency of DNA damage in both predator and prey DNA within individual faecal samples. The distribution of fragment lengths for each target fit well with the assumption of a random degradation process and, in keeping with our expectations, the estimated frequency of damage was always less in predator DNA than in prey DNA within the same sample (mean λpredator = 0.0106 per nucleotide; mean λprey = 0.0176 per nucleotide. This study is the first to explicitly define the amount of template damage in any DNA extracted from faeces and the first to quantify the amount of predator and prey DNA present within individual faecal samples. Conclusion We present an approach for characterizing mixed, highly degraded PCR templates such as those often encountered in ecological studies using non-invasive samples as a source of DNA, wildlife forensics investigations and ancient DNA research. This method will

Numerical study of microphase separation in gels and random media

International Nuclear Information System (INIS)

Uchida, Nariya

2004-01-01

Microphase separation in gels and random media is numerically studied using a Ginzburg-Landau model. A random field destroys long-range orientational (lamellar) order and gives rise to a disordered bicontinuous morphology. The dependence of the correlation length on the field strength is distinct from that of random-field magnets

Importance of participation rate in sampling of data in population based studies, with special reference to bone mass in Sweden.

OpenAIRE

Düppe, H; Gärdsell, P; Hanson, B S; Johnell, O; Nilsson, B E

1996-01-01

OBJECTIVE: To study the effects of participation rate in sampling on "normative" bone mass data. DESIGN: This was a comparison between two randomly selected samples from the same population. The participation rates in the two samples were 61.9% and 83.6%. Measurements were made of bone mass at different skeletal sites and of muscle strength, as well as an assessment of physical activity. SETTING: Malmö, Sweden. SUBJECTS: There were 230 subjects (117 men, 113 women), aged 21 to 42 years. RESUL...

Flow, transport and diffusion in random geometries II: applications

KAUST Repository

Asinari, Pietro

2015-01-07

Multilevel Monte Carlo (MLMC) is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrization of the input randomness is not available or too expensive. We present several applications of our MLMC algorithm for flow, transport and diffusion in random heterogeneous materials. The absolute permeability and effective diffusivity (or formation factor) of micro-scale porous media samples are computed and the uncertainty related to the sampling procedures is studied. The algorithm is then extended to the transport problems and multiphase flows for the estimation of dispersion and relative permeability curves. The impact of water drops on random stuctured surfaces, with microfluidics applications to self-cleaning materials, is also studied and simulated. Finally the estimation of new drag correlation laws for poly-dispersed dilute and dense suspensions is presented.

Flow, transport and diffusion in random geometries II: applications

KAUST Repository

Asinari, Pietro; Ceglia, Diego; Icardi, Matteo; Prudhomme, Serge; Tempone, Raul

2015-01-01

Multilevel Monte Carlo (MLMC) is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrization of the input randomness is not available or too expensive. We present several applications of our MLMC algorithm for flow, transport and diffusion in random heterogeneous materials. The absolute permeability and effective diffusivity (or formation factor) of micro-scale porous media samples are computed and the uncertainty related to the sampling procedures is studied. The algorithm is then extended to the transport problems and multiphase flows for the estimation of dispersion and relative permeability curves. The impact of water drops on random stuctured surfaces, with microfluidics applications to self-cleaning materials, is also studied and simulated. Finally the estimation of new drag correlation laws for poly-dispersed dilute and dense suspensions is presented.

Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

Science.gov (United States)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous

Do federal and state audits increase compliance with a grant program to improve municipal infrastructure (AUDIT study): study protocol for a randomized controlled trial.

Science.gov (United States)

De La O, Ana L; Martel García, Fernando

2014-09-03

Poor governance and accountability compromise young democracies' efforts to provide public services critical for human development, including water, sanitation, health, and education. Evidence shows that accountability agencies like superior audit institutions can reduce corruption and waste in federal grant programs financing service infrastructure. However, little is know about their effect on compliance with grant reporting and resource allocation requirements, or about the causal mechanisms. This study protocol for an exploratory randomized controlled trial tests the hypothesis that federal and state audits increase compliance with a federal grant program to improve municipal service infrastructure serving marginalized households. The AUDIT study is a block randomized, controlled, three-arm parallel group exploratory trial. A convenience sample of 5 municipalities in each of 17 states in Mexico (n=85) were block randomized to be audited by federal auditors (n=17), by state auditors (n=17), and a control condition outside the annual program of audits (n=51) in a 1:1:3 ratio. Replicable and verifiable randomization was performed using publicly available lottery numbers. Audited municipalities were included in the national program of audits and received standard audits on their use of federal public service infrastructure grants. Municipalities receiving moderate levels of grant transfers were recruited, as these were outside the auditing sampling frame--and hence audit program--or had negligible probabilities of ever being audited. The primary outcome measures capture compliance with the grant program and markers for the causal mechanisms, including deterrence and information effects. Secondary outcome measure include differences in audit reports across federal and state auditors, and measures like career concerns, political promotions, and political clientelism capturing synergistic effects with municipal accountability systems. The survey firm and research

Effects of errorless skill learning in people with mild-to-moderate or severe dementia: a randomized controlled pilot study.

NARCIS (Netherlands)

Kessels, R.P.C.; Hensken, L.M.

2009-01-01

This pilot study examines whether learning without errors is advantageous compared to trial-and-error learning in people with dementia using a procedural task and a randomized case-control design. A sample of 60 people was recruited, consisting of 20 patients with severe dementia, 20 patients with

Effects of errorless skill learning in people with mild-to-moderate or severe dementia: A randomized controlled pilot study

NARCIS (Netherlands)

Kessels, R.P.C.; Olde Hensken, L.M.G.

2009-01-01

This pilot study examines whether learning without errors is advantageous compared to trial-and-error learning in people with dementia using a procedural task and a randomized case-control design. A sample of 60 people was recruited, consisting of 20 patients with severe dementia, 20 patients with

Random walks and diffusion on networks

Science.gov (United States)

Masuda, Naoki; Porter, Mason A.; Lambiotte, Renaud

2017-11-01

Random walks are ubiquitous in the sciences, and they are interesting from both theoretical and practical perspectives. They are one of the most fundamental types of stochastic processes; can be used to model numerous phenomena, including diffusion, interactions, and opinions among humans and animals; and can be used to extract information about important entities or dense groups of entities in a network. Random walks have been studied for many decades on both regular lattices and (especially in the last couple of decades) on networks with a variety of structures. In the present article, we survey the theory and applications of random walks on networks, restricting ourselves to simple cases of single and non-adaptive random walkers. We distinguish three main types of random walks: discrete-time random walks, node-centric continuous-time random walks, and edge-centric continuous-time random walks. We first briefly survey random walks on a line, and then we consider random walks on various types of networks. We extensively discuss applications of random walks, including ranking of nodes (e.g., PageRank), community detection, respondent-driven sampling, and opinion models such as voter models.

Comparing attitudes about legal sanctions and teratogenic effects for cocaine, alcohol, tobacco and caffeine: A randomized, independent samples design

Directory of Open Access Journals (Sweden)

Alanis Kelly L

2006-02-01

Full Text Available Abstract Background Establishing more sensible measures to treat cocaine-addicted mothers and their children is essential for improving U.S. drug policy. Favorable post-natal environments have moderated potential deleterious prenatal effects. However, since cocaine is an illicit substance having long been demonized, we hypothesized that attitudes toward prenatal cocaine exposure would be more negative than for licit substances, alcohol, nicotine and caffeine. Further, media portrayals about long-term outcomes were hypothesized to influence viewers' attitudes, measured immediately post-viewing. Reducing popular crack baby stigmas could influence future policy decisions by legislators. In Study 1, 336 participants were randomly assigned to 1 of 4 conditions describing hypothetical legal sanction scenarios for pregnant women using cocaine, alcohol, nicotine or caffeine. Participants rated legal sanctions against pregnant women who used one of these substances and risk potential for developing children. In Study 2, 139 participants were randomly assigned to positive, neutral and negative media conditions. Immediately post-viewing, participants rated prenatal cocaine-exposed or non-exposed teens for their academic performance and risk for problems at age18. Results Participants in Study 1 imposed significantly greater legal sanctions for cocaine, perceiving prenatal cocaine exposure as more harmful than alcohol, nicotine or caffeine. A one-way ANOVA for independent samples showed significant differences, beyond .0001. Post-hoc Sheffe test illustrated that cocaine was rated differently from other substances. In Study 2, a one-way ANOVA for independent samples was performed on difference scores for the positive, neutral or negative media conditions about prenatal cocaine exposure. Participants in the neutral and negative media conditions estimated significantly lower grade point averages and more problems for the teen with prenatal cocaine exposure

Revisiting sample size: are big trials the answer?

Science.gov (United States)

Lurati Buse, Giovanna A L; Botto, Fernando; Devereaux, P J

2012-07-18

The superiority of the evidence generated in randomized controlled trials over observational data is not only conditional to randomization. Randomized controlled trials require proper design and implementation to provide a reliable effect estimate. Adequate random sequence generation, allocation implementation, analyses based on the intention-to-treat principle, and sufficient power are crucial to the quality of a randomized controlled trial. Power, or the probability of the trial to detect a difference when a real difference between treatments exists, strongly depends on sample size. The quality of orthopaedic randomized controlled trials is frequently threatened by a limited sample size. This paper reviews basic concepts and pitfalls in sample-size estimation and focuses on the importance of large trials in the generation of valid evidence.

Preeminence and prerequisites of sample size calculations in clinical trials

OpenAIRE

Richa Singhal; Rakesh Rana

2015-01-01

The key components while planning a clinical study are the study design, study duration, and sample size. These features are an integral part of planning a clinical trial efficiently, ethically, and cost-effectively. This article describes some of the prerequisites for sample size calculation. It also explains that sample size calculation is different for different study designs. The article in detail describes the sample size calculation for a randomized controlled trial when the primary out...

A randomized trial of a DWI intervention program for first offenders: intervention outcomes and interactions with antisocial personality disorder among a primarily American-Indian sample.

Science.gov (United States)

Woodall, W Gill; Delaney, Harold D; Kunitz, Stephen J; Westerberg, Verner S; Zhao, Hongwei

2007-06-01

Randomized trial evidence on the effectiveness of incarceration and treatment of first-time driving while intoxicated (DWI) offenders who are primarily American Indian has yet to be reported in the literature on DWI prevention. Further, research has confirmed the association of antisocial personality disorder (ASPD) with problems with alcohol including DWI. A randomized clinical trial was conducted, in conjunction with 28 days of incarceration, of a treatment program incorporating motivational interviewing principles for first-time DWI offenders. The sample of 305 offenders including 52 diagnosed as ASPD by the Diagnostic Interview Schedule were assessed before assignment to conditions and at 6, 12, and 24 months after discharge. Self-reported frequency of drinking and driving as well as various measures of drinking over the preceding 90 days were available at all assessments for 244 participants. Further, DWI rearrest data for 274 participants were available for analysis. Participants randomized to receive the first offender incarceration and treatment program reported greater reductions in alcohol consumption from baseline levels when compared with participants who were only incarcerated. Antisocial personality disorder participants reported heavier and more frequent drinking but showed significantly greater declines in drinking from intake to posttreatment assessments. Further, the treatment resulted in larger effects relative to the control on ASPD than non-ASPD participants. Nonconfrontational treatment may significantly enhance outcomes for DWI offenders with ASPD when delivered in an incarcerated setting, and in the present study, such effects were found in a primarily American-Indian sample.

Reducing sample size by combining superiority and non-inferiority for two primary endpoints in the Social Fitness study.

Science.gov (United States)

Donkers, Hanneke; Graff, Maud; Vernooij-Dassen, Myrra; Nijhuis-van der Sanden, Maria; Teerenstra, Steven

2017-01-01

In randomized controlled trials, two endpoints may be necessary to capture the multidimensional concept of the intervention and the objectives of the study adequately. We show how to calculate sample size when defining success of a trial by combinations of superiority and/or non-inferiority aims for the endpoints. The randomized controlled trial design of the Social Fitness study uses two primary endpoints, which can be combined into five different scenarios for defining success of the trial. We show how to calculate power and sample size for each scenario and compare these for different settings of power of each endpoint and correlation between them. Compared to a single primary endpoint, using two primary endpoints often gives more power when success is defined as: improvement in one of the two endpoints and no deterioration in the other. This also gives better power than when success is defined as: improvement in one prespecified endpoint and no deterioration in the remaining endpoint. When two primary endpoints are equally important, but a positive effect in both simultaneously is not per se required, the objective of having one superior and the other (at least) non-inferior could make sense and reduce sample size. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of smartphone diaries and personal dosimeters on behavior in a randomized study of methods to document sunlight exposure

DEFF Research Database (Denmark)

Køster, Brian; Søndergaard, Jens; Nielsen, Jesper Bo

2016-01-01

study. We examined the effects of wearing dosimeters and filling out diaries, measurement period and recall effect on the sun-related behavior in Denmark in 2012.Our sample included 240 participants eligible by smartphone status and who took a vacation during weeks 26-32 in 2012, randomized by gender...

Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling

Energy Technology Data Exchange (ETDEWEB)

Vrugt, Jasper A [Los Alamos National Laboratory; Hyman, James M [Los Alamos National Laboratory; Robinson, Bruce A [Los Alamos National Laboratory; Higdon, Dave [Los Alamos National Laboratory; Ter Braak, Cajo J F [NETHERLANDS; Diks, Cees G H [UNIV OF AMSTERDAM

2008-01-01

Markov chain Monte Carlo (MCMC) methods have found widespread use in many fields of study to estimate the average properties of complex systems, and for posterior inference in a Bayesian framework. Existing theory and experiments prove convergence of well constructed MCMC schemes to the appropriate limiting distribution under a variety of different conditions. In practice, however this convergence is often observed to be disturbingly slow. This is frequently caused by an inappropriate selection of the proposal distribution used to generate trial moves in the Markov Chain. Here we show that significant improvements to the efficiency of MCMC simulation can be made by using a self-adaptive Differential Evolution learning strategy within a population-based evolutionary framework. This scheme, entitled DiffeRential Evolution Adaptive Metropolis or DREAM, runs multiple different chains simultaneously for global exploration, and automatically tunes the scale and orientation of the proposal distribution in randomized subspaces during the search. Ergodicity of the algorithm is proved, and various examples involving nonlinearity, high-dimensionality, and multimodality show that DREAM is generally superior to other adaptive MCMC sampling approaches. The DREAM scheme significantly enhances the applicability of MCMC simulation to complex, multi-modal search problems.

Urine sampling techniques in symptomatic primary-care patients

DEFF Research Database (Denmark)

Holm, Anne; Aabenhus, Rune

2016-01-01

in infection rate between mid-stream-clean-catch, mid-stream-urine and random samples. Conclusions: At present, no evidence suggests that sampling technique affects the accuracy of the microbiological diagnosis in non-pregnant women with symptoms of urinary tract infection in primary care. However......Background: Choice of urine sampling technique in urinary tract infection may impact diagnostic accuracy and thus lead to possible over- or undertreatment. Currently no evidencebased consensus exists regarding correct sampling technique of urine from women with symptoms of urinary tract infection...... a randomized or paired design to compare the result of urine culture obtained with two or more collection techniques in adult, female, non-pregnant patients with symptoms of urinary tract infection. We evaluated quality of the studies and compared accuracy based on dichotomized outcomes. Results: We included...

Prevalence and predictors of Video Game Addiction: A study based on a national sample of Gamers.

OpenAIRE

Wittek, Charlotte Thoresen; Finserås, Turi Reiten; Pallesen, Ståle; Mentzoni, Rune; Hanss, Daniel; Griffiths, Mark D.; Molde, Helge

2015-01-01

Video gaming has become a popular leisure activity in many parts of the world, and an increasing number of empirical studies examine the small minority that appears to develop problems as a result of excessive gaming. This study investigated prevalence rates and predictors of video game addiction in a sample of gamers, randomly selected from the National Population Registry of Norway (N = 3389). Results showed there were 1.4 % addicted gamers, 7.3 % problem gamers, 3.9 % engaged gamers, and 8...

On Invertible Sampling and Adaptive Security

DEFF Research Database (Denmark)

Ishai, Yuval; Kumarasubramanian, Abishek; Orlandi, Claudio

2011-01-01

functionalities was left open. We provide the first convincing evidence that the answer to this question is negative, namely that some (randomized) functionalities cannot be realized with adaptive security. We obtain this result by studying the following related invertible sampling problem: given an efficient...... sampling algorithm A, obtain another sampling algorithm B such that the output of B is computationally indistinguishable from the output of A, but B can be efficiently inverted (even if A cannot). This invertible sampling problem is independently motivated by other cryptographic applications. We show......, under strong but well studied assumptions, that there exist efficient sampling algorithms A for which invertible sampling as above is impossible. At the same time, we show that a general feasibility result for adaptively secure MPC implies that invertible sampling is possible for every A, thereby...

Proteomic biomarker discovery in 1000 human plasma samples with mass spectrometry

DEFF Research Database (Denmark)

Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John

2016-01-01

automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked...

A combinatorial and probabilistic study of initial and end heights of descents in samples of geometrically distributed random variables and in permutations

Directory of Open Access Journals (Sweden)

Helmut Prodinger

2007-01-01

Full Text Available In words, generated by independent geometrically distributed random variables, we study the l th descent, which is, roughly speaking, the l th occurrence of a neighbouring pair ab with a>b. The value a is called the initial height, and b the end height. We study these two random variables (and some similar ones by combinatorial and probabilistic tools. We find in all instances a generating function Ψ(v,u, where the coefficient of v j u i refers to the j th descent (ascent, and i to the initial (end height. From this, various conclusions can be drawn, in particular expected values. In the probabilistic part, a Markov chain model is used, which allows to get explicit expressions for the heights of the second descent. In principle, one could go further, but the complexity of the results forbids it. This is extended to permutations of a large number of elements. Methods from q-analysis are used to simplify the expressions. This is the reason that we confine ourselves to the geometric distribution only. For general discrete distributions, no such tools are available.

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies

International Nuclear Information System (INIS)

Hampton, Jerrad; Doostan, Alireza

2015-01-01

Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ 1 -minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies

Science.gov (United States)

Hampton, Jerrad; Doostan, Alireza

2015-01-01

Sampling orthogonal polynomial bases via Monte Carlo is of interest for uncertainty quantification of models with random inputs, using Polynomial Chaos (PC) expansions. It is known that bounding a probabilistic parameter, referred to as coherence, yields a bound on the number of samples necessary to identify coefficients in a sparse PC expansion via solution to an ℓ1-minimization problem. Utilizing results for orthogonal polynomials, we bound the coherence parameter for polynomials of Hermite and Legendre type under their respective natural sampling distribution. In both polynomial bases we identify an importance sampling distribution which yields a bound with weaker dependence on the order of the approximation. For more general orthonormal bases, we propose the coherence-optimal sampling: a Markov Chain Monte Carlo sampling, which directly uses the basis functions under consideration to achieve a statistical optimality among all sampling schemes with identical support. We demonstrate these different sampling strategies numerically in both high-order and high-dimensional, manufactured PC expansions. In addition, the quality of each sampling method is compared in the identification of solutions to two differential equations, one with a high-dimensional random input and the other with a high-order PC expansion. In both cases, the coherence-optimal sampling scheme leads to similar or considerably improved accuracy.

Soil map disaggregation improved by soil-landscape relationships, area-proportional sampling and random forest implementation

DEFF Research Database (Denmark)

Møller, Anders Bjørn; Malone, Brendan P.; Odgers, Nathan

implementation generally improved the algorithm’s ability to predict the correct soil class. The implementation of soil-landscape relationships and area-proportional sampling generally increased the calculation time, while the random forest implementation reduced the calculation time. In the most successful......Detailed soil information is often needed to support agricultural practices, environmental protection and policy decisions. Several digital approaches can be used to map soil properties based on field observations. When soil observations are sparse or missing, an alternative approach...... is to disaggregate existing conventional soil maps. At present, the DSMART algorithm represents the most sophisticated approach for disaggregating conventional soil maps (Odgers et al., 2014). The algorithm relies on classification trees trained from resampled points, which are assigned classes according...

A randomized controlled trial of smartphone-based mindfulness training for smoking cessation: a study protocol.

Science.gov (United States)

Garrison, Kathleen A; Pal, Prasanta; Rojiani, Rahil; Dallery, Jesse; O'Malley, Stephanie S; Brewer, Judson A

2015-04-14

Tobacco use is responsible for the death of about 1 in 10 individuals worldwide. Mindfulness training has shown preliminary efficacy as a behavioral treatment for smoking cessation. Recent advances in mobile health suggest advantages to smartphone-based smoking cessation treatment including smartphone-based mindfulness training. This study evaluates the efficacy of a smartphone app-based mindfulness training program for improving smoking cessation rates at 6-months follow-up. A two-group parallel-randomized clinical trial with allocation concealment will be conducted. Group assignment will be concealed from study researchers through to follow-up. The study will be conducted by smartphone and online. Daily smokers who are interested in quitting smoking and own a smartphone (n = 140) will be recruited through study advertisements posted online. After completion of a baseline survey, participants will be allocated randomly to the control or intervention group. Participants in both groups will receive a 22-day smartphone-based treatment program for smoking. Participants in the intervention group will receive mobile mindfulness training plus experience sampling. Participants in the control group will receive experience sampling-only. The primary outcome measure will be one-week point prevalence abstinence from smoking (at 6-months follow-up) assessed using carbon monoxide breath monitoring, which will be validated through smartphone-based video chat. This is the first intervention study to evaluate smartphone-based delivery of mindfulness training for smoking cessation. Such an intervention may provide treatment in-hand, in real-world contexts, to help individuals quit smoking. Clinicaltrials.gov NCT02134509 . Registered 7 May 2014.

Aerobic physical activity and resistance training: an application of the theory of planned behavior among adults with type 2 diabetes in a random, national sample of Canadians

Directory of Open Access Journals (Sweden)

Karunamuni Nandini

2008-12-01

Full Text Available Abstract Background Aerobic physical activity (PA and resistance training are paramount in the treatment and management of type 2 diabetes (T2D, but few studies have examined the determinants of both types of exercise in the same sample. Objective The primary purpose was to investigate the utility of the Theory of Planned Behavior (TPB in explaining aerobic PA and resistance training in a population sample of T2D adults. Methods A total of 244 individuals were recruited through a random national sample which was created by generating a random list of household phone numbers. The list was proportionate to the actual number of household telephone numbers for each Canadian province (with the exception of Quebec. These individuals completed self-report TPB constructs of attitude, subjective norm, perceived behavioral control and intention, and a 3-month follow-up that assessed aerobic PA and resistance training. Results TPB explained 10% and 8% of the variance respectively for aerobic PA and resistance training; and accounted for 39% and 45% of the variance respectively for aerobic PA and resistance training intentions. Conclusion These results may guide the development of appropriate PA interventions for aerobic PA and resistance training based on the TPB.

Evaluating effectiveness of down-sampling for stratified designs and unbalanced prevalence in Random Forest models of tree species distributions in Nevada

Science.gov (United States)

Elizabeth A. Freeman; Gretchen G. Moisen; Tracy S. Frescino

2012-01-01

Random Forests is frequently used to model species distributions over large geographic areas. Complications arise when data used to train the models have been collected in stratified designs that involve different sampling intensity per stratum. The modeling process is further complicated if some of the target species are relatively rare on the landscape leading to an...

Random walk on random walks

NARCIS (Netherlands)

Hilário, M.; Hollander, den W.Th.F.; Sidoravicius, V.; Soares dos Santos, R.; Teixeira, A.

2014-01-01

In this paper we study a random walk in a one-dimensional dynamic random environment consisting of a collection of independent particles performing simple symmetric random walks in a Poisson equilibrium with density ¿¿(0,8). At each step the random walk performs a nearest-neighbour jump, moving to

a randomized, placebo- controlled study

OpenAIRE

Hall, Franziska van

2012-01-01

Introduction: Repetitive transcranial magnetic stimulation (rTMS) is a well-tolerated non-invasive method, which has also been proved to have mild antidepressant effects and is used as “add-on“-therapy in treating pharmaco-resistant major depression. Objective: The efficacy of an escitalopram plus rTMS-combination-treatment was evaluated and compared to escitalopram plus sham rTMS. Methods: We designed a four week-, randomized, rater-blinded, and controlled add-on study with two trea...

Projection correlation between two random vectors.

Science.gov (United States)

Zhu, Liping; Xu, Kai; Li, Runze; Zhong, Wei

2017-12-01

We propose the use of projection correlation to characterize dependence between two random vectors. Projection correlation has several appealing properties. It equals zero if and only if the two random vectors are independent, it is not sensitive to the dimensions of the two random vectors, it is invariant with respect to the group of orthogonal transformations, and its estimation is free of tuning parameters and does not require moment conditions on the random vectors. We show that the sample estimate of the projection correction is [Formula: see text]-consistent if the two random vectors are independent and root-[Formula: see text]-consistent otherwise. Monte Carlo simulation studies indicate that the projection correlation has higher power than the distance correlation and the ranks of distances in tests of independence, especially when the dimensions are relatively large or the moment conditions required by the distance correlation are violated.

Fetal scalp blood sampling in labor - a review

DEFF Research Database (Denmark)

Jørgensen, Jan Stener; Weber, Tom

2014-01-01

During the 1970s and 1980s, electronic fetal monitoring and fetal scalp blood sampling (FBS) were introduced without robust evidence. With a methodical review of the published literature, and using one randomized controlled trial, seven controlled studies, nine randomized studies of various...... surveillance methods and data from the Danish National Birth Registry, we have assessed the usefulness of FBS as a complementary tool to improve the specificity and sensitivity of electronic cardiotocography (CTG). Based on heterogeneous studies of modest quality with somewhat inconsistent results, we conclude...

Mental Health Impact of Hosting Disaster Refugees: Analyses from a Random Sample Survey Among Haitians Living in Miami.

Science.gov (United States)

Messiah, Antoine; Lacoste, Jérôme; Gokalsing, Erick; Shultz, James M; Rodríguez de la Vega, Pura; Castro, Grettel; Acuna, Juan M

2016-08-01

Studies on the mental health of families hosting disaster refugees are lacking. This study compares participants in households that hosted 2010 Haitian earthquake disaster refugees with their nonhost counterparts. A random sample survey was conducted from October 2011 through December 2012 in Miami-Dade County, Florida. Haitian participants were assessed regarding their 2010 earthquake exposure and impact on family and friends and whether they hosted earthquake refugees. Using standardized scores and thresholds, they were evaluated for symptoms of three common mental disorders (CMDs): posttraumatic stress disorder, generalized anxiety disorder, and major depressive disorder (MDD). Participants who hosted refugees (n = 51) had significantly higher percentages of scores beyond thresholds for MDD than those who did not host refugees (n = 365) and for at least one CMD, after adjusting for participants' earthquake exposures and effects on family and friends. Hosting refugees from a natural disaster appears to elevate the risk for MDD and possibly other CMDs, independent of risks posed by exposure to the disaster itself. Families hosting refugees deserve special attention.

Efficient sampling algorithms for Monte Carlo based treatment planning

International Nuclear Information System (INIS)

DeMarco, J.J.; Solberg, T.D.; Chetty, I.; Smathers, J.B.

1998-01-01

Efficient sampling algorithms are necessary for producing a fast Monte Carlo based treatment planning code. This study evaluates several aspects of a photon-based tracking scheme and the effect of optimal sampling algorithms on the efficiency of the code. Four areas were tested: pseudo-random number generation, generalized sampling of a discrete distribution, sampling from the exponential distribution, and delta scattering as applied to photon transport through a heterogeneous simulation geometry. Generalized sampling of a discrete distribution using the cutpoint method can produce speedup gains of one order of magnitude versus conventional sequential sampling. Photon transport modifications based upon the delta scattering method were implemented and compared with a conventional boundary and collision checking algorithm. The delta scattering algorithm is faster by a factor of six versus the conventional algorithm for a boundary size of 5 mm within a heterogeneous geometry. A comparison of portable pseudo-random number algorithms and exponential sampling techniques is also discussed

Evaluating sampling strategy for DNA barcoding study of coastal and inland halo-tolerant Poaceae and Chenopodiaceae: A case study for increased sample size.

Directory of Open Access Journals (Sweden)

Peng-Cheng Yao

Full Text Available Environmental conditions in coastal salt marsh habitats have led to the development of specialist genetic adaptations. We evaluated six DNA barcode loci of the 53 species of Poaceae and 15 species of Chenopodiaceae from China's coastal salt marsh area and inland area. Our results indicate that the optimum DNA barcode was ITS for coastal salt-tolerant Poaceae and matK for the Chenopodiaceae. Sampling strategies for ten common species of Poaceae and Chenopodiaceae were analyzed according to optimum barcode. We found that by increasing the number of samples collected from the coastal salt marsh area on the basis of inland samples, the number of haplotypes of Arundinella hirta, Digitaria ciliaris, Eleusine indica, Imperata cylindrica, Setaria viridis, and Chenopodium glaucum increased, with a principal coordinate plot clearly showing increased distribution points. The results of a Mann-Whitney test showed that for Digitaria ciliaris, Eleusine indica, Imperata cylindrica, and Setaria viridis, the distribution of intraspecific genetic distances was significantly different when samples from the coastal salt marsh area were included (P < 0.01. These results suggest that increasing the sample size in specialist habitats can improve measurements of intraspecific genetic diversity, and will have a positive effect on the application of the DNA barcodes in widely distributed species. The results of random sampling showed that when sample size reached 11 for Chloris virgata, Chenopodium glaucum, and Dysphania ambrosioides, 13 for Setaria viridis, and 15 for Eleusine indica, Imperata cylindrica and Chenopodium album, average intraspecific distance tended to reach stability. These results indicate that the sample size for DNA barcode of globally distributed species should be increased to 11-15.

A Bayesian sequential design with adaptive randomization for 2-sided hypothesis test.

Science.gov (United States)

Yu, Qingzhao; Zhu, Lin; Zhu, Han

2017-11-01

Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size. Copyright © 2017 John Wiley & Sons, Ltd.

Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers

Directory of Open Access Journals (Sweden)

Litonjua Augusto A

2011-06-01

Full Text Available Abstract Background Personalized health-care promises tailored health-care solutions to individual patients based on their genetic background and/or environmental exposure history. To date, disease prediction has been based on a few environmental factors and/or single nucleotide polymorphisms (SNPs, while complex diseases are usually affected by many genetic and environmental factors with each factor contributing a small portion to the outcome. We hypothesized that the use of random forests classifiers to select SNPs would result in an improved predictive model of asthma exacerbations. We tested this hypothesis in a population of childhood asthmatics. Methods In this study, using emergency room visits or hospitalizations as the definition of a severe asthma exacerbation, we first identified a list of top Genome Wide Association Study (GWAS SNPs ranked by Random Forests (RF importance score for the CAMP (Childhood Asthma Management Program population of 127 exacerbation cases and 290 non-exacerbation controls. We predict severe asthma exacerbations using the top 10 to 320 SNPs together with age, sex, pre-bronchodilator FEV1 percentage predicted, and treatment group. Results Testing in an independent set of the CAMP population shows that severe asthma exacerbations can be predicted with an Area Under the Curve (AUC = 0.66 with 160-320 SNPs in comparison to an AUC score of 0.57 with 10 SNPs. Using the clinical traits alone yielded AUC score of 0.54, suggesting the phenotype is affected by genetic as well as environmental factors. Conclusions Our study shows that a random forests algorithm can effectively extract and use the information contained in a small number of samples. Random forests, and other machine learning tools, can be used with GWAS studies to integrate large numbers of predictors simultaneously.

Variable screening and ranking using sampling-based sensitivity measures

International Nuclear Information System (INIS)

Wu, Y-T.; Mohanty, Sitakanta

2006-01-01

This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

Financial ties of principal investigators and randomized controlled trial outcomes: cross sectional study.

Science.gov (United States)

Ahn, Rosa; Woodbridge, Alexandra; Abraham, Ann; Saba, Susan; Korenstein, Deborah; Madden, Erin; Boscardin, W John; Keyhani, Salomeh

2017-01-17

 To examine the association between the presence of individual principal investigators' financial ties to the manufacturer of the study drug and the trial's outcomes after accounting for source of research funding.  Cross sectional study of randomized controlled trials (RCTs).  Studies published in "core clinical" journals, as identified by Medline, between 1 January 2013 and 31 December 2013.  Random sample of RCTs focused on drug efficacy.  Association between financial ties of principal investigators and study outcome.  A total of 190 papers describing 195 studies met inclusion criteria. Financial ties between principal investigators and the pharmaceutical industry were present in 132 (67.7%) studies. Of 397 principal investigators, 231 (58%) had financial ties and 166 (42%) did not. Of all principal investigators, 156 (39%) reported advisor/consultancy payments, 81 (20%) reported speakers' fees, 81 (20%) reported unspecified financial ties, 52 (13%) reported honorariums, 52 (13%) reported employee relationships, 52 (13%) reported travel fees, 41 (10%) reported stock ownership, and 20 (5%) reported having a patent related to the study drug. The prevalence of financial ties of principal investigators was 76% (103/136) among positive studies and 49% (29/59) among negative studies. In unadjusted analyses, the presence of a financial tie was associated with a positive study outcome (odds ratio 3.23, 95% confidence interval 1.7 to 6.1). In the primary multivariate analysis, a financial tie was significantly associated with positive RCT outcome after adjustment for the study funding source (odds ratio 3.57 (1.7 to 7.7). The secondary analysis controlled for additional RCT characteristics such as study phase, sample size, country of first authors, specialty, trial registration, study design, type of analysis, comparator, and outcome measure. These characteristics did not appreciably affect the relation between financial ties and study outcomes (odds ratio 3.37, 1

Visualizing the Sample Standard Deviation

Science.gov (United States)

Sarkar, Jyotirmoy; Rashid, Mamunur

2017-01-01

The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…

Correction of confounding bias in non-randomized studies by appropriate weighting.

Science.gov (United States)

Schmoor, Claudia; Gall, Christine; Stampf, Susanne; Graf, Erika

2011-03-01

In non-randomized studies, the assessment of a causal effect of treatment or exposure on outcome is hampered by possible confounding. Applying multiple regression models including the effects of treatment and covariates on outcome is the well-known classical approach to adjust for confounding. In recent years other approaches have been promoted. One of them is based on the propensity score and considers the effect of possible confounders on treatment as a relevant criterion for adjustment. Another proposal is based on using an instrumental variable. Here inference relies on a factor, the instrument, which affects treatment but is thought to be otherwise unrelated to outcome, so that it mimics randomization. Each of these approaches can basically be interpreted as a simple reweighting scheme, designed to address confounding. The procedures will be compared with respect to their fundamental properties, namely, which bias they aim to eliminate, which effect they aim to estimate, and which parameter is modelled. We will expand our overview of methods for analysis of non-randomized studies to methods for analysis of randomized controlled trials and show that analyses of both study types may target different effects and different parameters. The considerations will be illustrated using a breast cancer study with a so-called Comprehensive Cohort Study design, including a randomized controlled trial and a non-randomized study in the same patient population as sub-cohorts. This design offers ideal opportunities to discuss and illustrate the properties of the different approaches. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fast integration using quasi-random numbers

International Nuclear Information System (INIS)

Bossert, J.; Feindt, M.; Kerzel, U.

2006-01-01

Quasi-random numbers are specially constructed series of numbers optimised to evenly sample a given s-dimensional volume. Using quasi-random numbers in numerical integration converges faster with a higher accuracy compared to the case of pseudo-random numbers. The basic properties of quasi-random numbers are introduced, various generators are discussed and the achieved gain is illustrated by examples

Fast integration using quasi-random numbers

Science.gov (United States)

Bossert, J.; Feindt, M.; Kerzel, U.

2006-04-01

Quasi-random numbers are specially constructed series of numbers optimised to evenly sample a given s-dimensional volume. Using quasi-random numbers in numerical integration converges faster with a higher accuracy compared to the case of pseudo-random numbers. The basic properties of quasi-random numbers are introduced, various generators are discussed and the achieved gain is illustrated by examples.

Diagnostic-test evaluation of immunoassays for anti-Toxoplasma gondii IgG antibodies in a random sample of Mexican population.

Science.gov (United States)

Caballero-Ortega, Heriberto; Castillo-Cruz, Rocío; Murieta, Sandra; Ortíz-Alegría, Luz Belinda; Calderón-Segura, Esther; Conde-Glez, Carlos J; Cañedo-Solares, Irma; Correa, Dolores

2014-05-14

There are few articles on evaluation of Toxoplasma gondii serological tests. Besides, commercially available tests are not always useful and are expensive for studies in open population. The aim of this study was to evaluate in-house ELISA and western blot for IgG antibodies in a representative sample of people living in Mexico. Three hundred and five serum samples were randomly selected from two national seroepidemiological survey banks; they were taken from men and women of all ages and from all areas of the country. ELISA cut-off was established using the mean plus three standard deviations of negative samples. Western blots were analysed by two experienced technicians and positivity was established according to the presence of at least three diagnostic bands. A commercial ELISA kit was used as a third test. Two reference standards were built up: one using concordant results of two assays leaving the evaluated test out and the other in which the evaluated test was included (IN) with at least two concordant results to define diagnosis. the lowest values of diagnostic parameters were obtained with the OUT reference standards: in-house ELISA had 96.9% sensitivity, 62.1% specificity, 49.6% PPV, 98.1% NPV and 71.8% accuracy, while western blot presented 81.8%, 89.7%, 84.0%, 88.2% and 86.6% values and the best kappa coefficient (0.72-0.82). The in-house ELISA is useful for screening people of Mexico, due to its high sensitivity, while western blot may be used to confirm diagnosis. These techniques might prove useful in other Latin American countries.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

Science.gov (United States)

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

Science.gov (United States)

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

An improved sampling method of complex network

Science.gov (United States)

Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

2014-12-01

Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

Sampling Polya-Gamma random variates: alternate and approximate techniques

OpenAIRE

Windle, Jesse; Polson, Nicholas G.; Scott, James G.

2014-01-01

Efficiently sampling from the P\\'olya-Gamma distribution, ${PG}(b,z)$, is an essential element of P\\'olya-Gamma data augmentation. Polson et. al (2013) show how to efficiently sample from the ${PG}(1,z)$ distribution. We build two new samplers that offer improved performance when sampling from the ${PG}(b,z)$ distribution and $b$ is not unity.

Random Photon Absorption Model Elucidates How Early Gain Control in Fly Photoreceptors Arises from Quantal Sampling

Science.gov (United States)

Song, Zhuoyi; Zhou, Yu; Juusola, Mikko

2016-01-01

Many diurnal photoreceptors encode vast real-world light changes effectively, but how this performance originates from photon sampling is unclear. A 4-module biophysically-realistic fly photoreceptor model, in which information capture is limited by the number of its sampling units (microvilli) and their photon-hit recovery time (refractoriness), can accurately simulate real recordings and their information content. However, sublinear summation in quantum bump production (quantum-gain-nonlinearity) may also cause adaptation by reducing the bump/photon gain when multiple photons hit the same microvillus simultaneously. Here, we use a Random Photon Absorption Model (RandPAM), which is the 1st module of the 4-module fly photoreceptor model, to quantify the contribution of quantum-gain-nonlinearity in light adaptation. We show how quantum-gain-nonlinearity already results from photon sampling alone. In the extreme case, when two or more simultaneous photon-hits reduce to a single sublinear value, quantum-gain-nonlinearity is preset before the phototransduction reactions adapt the quantum bump waveform. However, the contribution of quantum-gain-nonlinearity in light adaptation depends upon the likelihood of multi-photon-hits, which is strictly determined by the number of microvilli and light intensity. Specifically, its contribution to light-adaptation is marginal (≤ 1%) in fly photoreceptors with many thousands of microvilli, because the probability of simultaneous multi-photon-hits on any one microvillus is low even during daylight conditions. However, in cells with fewer sampling units, the impact of quantum-gain-nonlinearity increases with brightening light. PMID:27445779

Preeminence and prerequisites of sample size calculations in clinical trials

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Richa Singhal

2015-01-01

Full Text Available The key components while planning a clinical study are the study design, study duration, and sample size. These features are an integral part of planning a clinical trial efficiently, ethically, and cost-effectively. This article describes some of the prerequisites for sample size calculation. It also explains that sample size calculation is different for different study designs. The article in detail describes the sample size calculation for a randomized controlled trial when the primary outcome is a continuous variable and when it is a proportion or a qualitative variable.

A randomized controlled trial of long term effect of BCM guided fluid management in MHD patients (BOCOMO study: rationales and study design

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Liu Li

2012-09-01

Full Text Available Abstract Background Bioimpedance analysis (BIA has been reported as helpful in identifying hypervolemia. Observation data showed that hypervolemic maintenance hemodialysis (MHD patients identified using BIA methods have higher mortality risk. However, it is not known if BIA-guided fluid management can improve MHD patients’ survival. The objectives of the BOCOMO study are to evaluate the outcome of BIA guided fluid management compared with standard care. Methods This is a multicenter, prospective, randomized, controlled trial. More than 1300 participants from 16 clinical sites will be included in the study. The enrolment period will last 6 months, and minimum length of follow-up will be 36 months. MHD patients aged between 18 years and 80 years who have been on MHD for at least 3 months and meet eligibility criteria will be invited to participate in the study. Participants will be randomized to BIA arm or control arm in a 1:1 ratio. A portable whole body bioimpedance spectroscopy device (BCM—Fresenius Medical Care D GmbH will be used for BIA measurement at baseline for both arms of the study. In the BIA arm, additional BCM measurements will be performed every 2 months. The primary intent-to-treat analysis will compare outcomes for a composite endpoint of death, acute myocardial infarction, stroke or incident peripheral arterial occlusive disease between groups. Secondary endpoints will include left ventricular wall thickness, blood pressure, medications, and incidence and length of hospitalization. Discussions Previous results regarding the benefit of strict fluid control are conflicting due to small sample sizes and unstable dry weight estimating methods. To our knowledge this is the first large-scale, multicentre, prospective, randomized controlled trial to assess whether BIS-guided volume management improves outcomes of MHD patients. The endpoints of the BOCOMO study are of utmost importance to health care providers. In order to obtain

Randomized controlled study of CBT in bronchial asthma

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Grover Naveen

2007-01-01

Full Text Available The aim of the present study was to find out efficacy of cognitive behavior therapy, as an adjunct to standard pharmacotherapy, in bronchial asthma. In a random-ized two-group design with pre-and post assessments, forty asthma patients were randomly allotted to two groups: self management group and cognitive behavior therapy group. Both groups were exposed to 6-8 weeks of intervention, asthma self management program and cognitive behavior therapy. Assessment measures used were-Semi structured interview schedule, Asthma Symptom Checklist, Asthma di-ary, Asthma Bother Profile, Hospital Anxiety & Depression Scale, AQLQ and Peak Expiratory Flow Rate. Within group comparison showed significant improvement in both groups at the post assessment. Between group comparisons showed that CBT group reported significantly greater change than that of SM group. Cognitive behavior therapy helps in improving the managment of asthma.

Health indicators: eliminating bias from convenience sampling estimators.

Science.gov (United States)

Hedt, Bethany L; Pagano, Marcello

2011-02-28

Public health practitioners are often called upon to make inference about a health indicator for a population at large when the sole available information are data gathered from a convenience sample, such as data gathered on visitors to a clinic. These data may be of the highest quality and quite extensive, but the biases inherent in a convenience sample preclude the legitimate use of powerful inferential tools that are usually associated with a random sample. In general, we know nothing about those who do not visit the clinic beyond the fact that they do not visit the clinic. An alternative is to take a random sample of the population. However, we show that this solution would be wasteful if it excluded the use of available information. Hence, we present a simple annealing methodology that combines a relatively small, and presumably far less expensive, random sample with the convenience sample. This allows us to not only take advantage of powerful inferential tools, but also provides more accurate information than that available from just using data from the random sample alone. Copyright © 2011 John Wiley & Sons, Ltd.

A random effects meta-analysis model with Box-Cox transformation.

Science.gov (United States)

Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The

A random effects meta-analysis model with Box-Cox transformation

Directory of Open Access Journals (Sweden)

Yusuke Yamaguchi

2017-07-01

Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and

Computed tomography of the brain, hepatotoxic drugs and high alcohol consumption in male alcoholic patients and a random sample from the general male population

Energy Technology Data Exchange (ETDEWEB)

Muetzell, S. (Univ. Hospital of Uppsala (Sweden). Dept. of Family Medicine)

1992-01-01

Computed tomography (CT) of the brain was performed in a random sample of a total of 195 men and 211 male alcoholic patients admitted for the first time during a period of two years from the same geographically limited area of Greater Stockholm as the sample. Laboratory tests were performed, including liver and pancreatic tests. Toxicological screening was performed and the consumption of hepatotoxic drugs was also investigated. The groups were then subdivided with respect to alcohol consumption and use of hepatotoxic drugs: group IA, men from the random sample with low or moderate alcohol consumption and no use of hepatotoxic drugs; IB, men from the random sample with low or moderate alcohol consumption with use of hepatotoxic drugs; IIA, alcoholic inpatients with use of alcohol and no drugs; and IIB, alcoholic inpatients with use of alcohol and drugs. Group IIB was found to have a higher incidence of cortical and subcortical changes than group IA. Group IB had a higher incidence of subcortical changes than group IA, and they differed only in drug use. Groups IIN and IIA only differed in drug use, and IIB had a higher incidence of brian damage except for anterior horn index and wide cerebellar sulci indicating vermian atrophy. Significantly higher serum levels of bilirubin, GGT, ASAT, ALAT, CK LD, and amylase were found in IIB. The results indicate that drug use influences the incidence of cortical and subcortical aberrations, except anterior horn index. It is concluded that the groups with alcohol abuse who used hepatotoxic drugs showed a picture of cortical changes (wide transport sulci and clear-cut of high-grade cortical changes) and also of subcortical aberrations, expressed as an increased widening on the third ventricle.

Computed tomography of the brain, hepatotoxic drugs and high alcohol consumption in male alcoholic patients and a random sample from the general male population

International Nuclear Information System (INIS)

Muetzell, S.

1992-01-01

Computed tomography (CT) of the brain was performed in a random sample of a total of 195 men and 211 male alcoholic patients admitted for the first time during a period of two years from the same geographically limited area of Greater Stockholm as the sample. Laboratory tests were performed, including liver and pancreatic tests. Toxicological screening was performed and the consumption of hepatotoxic drugs was also investigated. The groups were then subdivided with respect to alcohol consumption and use of hepatotoxic drugs: group IA, men from the random sample with low or moderate alcohol consumption and no use of hepatotoxic drugs; IB, men from the random sample with low or moderate alcohol consumption with use of hepatotoxic drugs; IIA, alcoholic inpatients with use of alcohol and no drugs; and IIB, alcoholic inpatients with use of alcohol and drugs. Group IIB was found to have a higher incidence of cortical and subcortical changes than group IA. Group IB had a higher incidence of subcortical changes than group IA, and they differed only in drug use. Groups IIN and IIA only differed in drug use, and IIB had a higher incidence of brian damage except for anterior horn index and wide cerebellar sulci indicating vermian atrophy. Significantly higher serum levels of bilirubin, GGT, ASAT, ALAT, CK LD, and amylase were found in IIB. The results indicate that drug use influences the incidence of cortical and subcortical aberrations, except anterior horn index. It is concluded that the groups with alcohol abuse who used hepatotoxic drugs showed a picture of cortical changes (wide transport sulci and clear-cut of high-grade cortical changes) and also of subcortical aberrations, expressed as an increased widening on the third ventricle

Random matrices and random difference equations

International Nuclear Information System (INIS)

Uppuluri, V.R.R.

1975-01-01

Mathematical models leading to products of random matrices and random difference equations are discussed. A one-compartment model with random behavior is introduced, and it is shown how the average concentration in the discrete time model converges to the exponential function. This is of relevance to understanding how radioactivity gets trapped in bone structure in blood--bone systems. The ideas are then generalized to two-compartment models and mammillary systems, where products of random matrices appear in a natural way. The appearance of products of random matrices in applications in demography and control theory is considered. Then random sequences motivated from the following problems are studied: constant pulsing and random decay models, random pulsing and constant decay models, and random pulsing and random decay models

Toward cost-efficient sampling methods

Science.gov (United States)

Luo, Peng; Li, Yongli; Wu, Chong; Zhang, Guijie

2015-09-01

The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper proposes two new sampling methods based on the idea that a small part of vertices with high node degree could possess the most structure information of a complex network. The two proposed sampling methods are efficient in sampling high degree nodes so that they would be useful even if the sampling rate is low, which means cost-efficient. The first new sampling method is developed on the basis of the widely used stratified random sampling (SRS) method and the second one improves the famous snowball sampling (SBS) method. In order to demonstrate the validity and accuracy of two new sampling methods, we compare them with the existing sampling methods in three commonly used simulation networks that are scale-free network, random network, small-world network, and also in two real networks. The experimental results illustrate that the two proposed sampling methods perform much better than the existing sampling methods in terms of achieving the true network structure characteristics reflected by clustering coefficient, Bonacich centrality and average path length, especially when the sampling rate is low.

Job strain and resting heart rate: a cross-sectional study in a Swedish random working sample

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Peter Eriksson

2016-03-01

Full Text Available Abstract Background Numerous studies have reported an association between stressing work conditions and cardiovascular disease. However, more evidence is needed, and the etiological mechanisms are unknown. Elevated resting heart rate has emerged as a possible risk factor for cardiovascular disease, but little is known about the relation to work-related stress. This study therefore investigated the association between job strain, job control, and job demands and resting heart rate. Methods We conducted a cross-sectional survey of randomly selected men and women in Västra Götalandsregionen, Sweden (West county of Sweden (n = 1552. Information about job strain, job demands, job control, heart rate and covariates was collected during the period 2001–2004 as part of the INTERGENE/ADONIX research project. Six different linear regression models were used with adjustments for gender, age, BMI, smoking, education, and physical activity in the fully adjusted model. Job strain was operationalized as the log-transformed ratio of job demands over job control in the statistical analyses. Results No associations were seen between resting heart rate and job demands. Job strain was associated with elevated resting heart rate in the unadjusted model (linear regression coefficient 1.26, 95 % CI 0.14 to 2.38, but not in any of the extended models. Low job control was associated with elevated resting heart rate after adjustments for gender, age, BMI, and smoking (linear regression coefficient −0.18, 95 % CI −0.30 to −0.02. However, there were no significant associations in the fully adjusted model. Conclusions Low job control and job strain, but not job demands, were associated with elevated resting heart rate. However, the observed associations were modest and may be explained by confounding effects.

Managing mobility outcomes in vulnerable seniors ( MMOVeS): a randomized controlled pilot study.

Science.gov (United States)

Figueiredo, Sabrina; Morais, Jose A; Mayo, Nancy

2017-12-01

To estimate feasibility and potential for efficacy of an individualized, exercise-focused, self-management program (i.e. Managing Mobility Outcomes In Vulnerable Seniors ( MMOVeS)), in comparison to exercise information in improving mobility after six months among seniors recently discharged from hospital. Randomized pilot study. Two McGill University-teaching hospitals. Community dwelling seniors, aged 70 years and older, recently discharged from either participating hospitals. The physiotherapy-facilitated intervention consisted of (1) evaluation of mobility capacity, (2) setting short- and long-term goals, (3) delineation of an exercise treatment plan, (4) an educational booklet to enhance mobility self-management skills, and (5) six monthly telephone calls. Control group received a booklet with information on exercises targeting mobility limitations in seniors. Mobility, pain, and health status were assessed at baseline and at six months using multiple indicators drawn from Disabilities of the Arm, Shoulder, and Hand (DASH) Score, Lower Extremity Functional Scale (LEFS) and Short-Form (SF)-36. In all, 26 people were randomized to the intervention (mean age: 81 ± 8; 39% women), and 23 were randomized to the control (mean age: 79 ± 7; 33% women). The odds ratio for the mobility outcomes combined was 3.08 and the 95% confidence interval excluded 1 (1.65-5.77). The odds ratio for pain and health perception favored the MMOVeS group, but the 95% confidence interval included the null value. This feasibility study highlights the potential for efficacy of an individualized, exercise-focused, self-management program in comparison to exercise information in improving mobility outcome for seniors. Furthermore, a home-program combining self-management skills and exercise taught with minimal supervision prove to be feasible. Finally, data from this study can be used to estimate sample size for a confirmatory trial.

Cluster randomized trial in the general practice research database: 2. Secondary prevention after first stroke (eCRT study: study protocol for a randomized controlled trial

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Dregan Alex

2012-10-01

Full Text Available Abstract Background The purpose of this research is to develop and evaluate methods for conducting pragmatic cluster randomized trials in a primary care electronic database. The proposal describes one application, in a less frequent chronic condition of public health importance, secondary prevention of stroke. A related protocol in antibiotic prescribing was reported previously. Methods/Design The study aims to implement a cluster randomized trial (CRT using the electronic patient records of the General Practice Research Database (GPRD as a sampling frame and data source. The specific objective of the trial is to evaluate the effectiveness of a computer-delivered intervention at enhancing the delivery of stroke secondary prevention in primary care. GPRD family practices will be allocated to the intervention or usual care. The intervention promotes the use of electronic prompts to support adherence with the recommendations of the UK Intercollegiate Stroke Working Party and NICE guidelines for the secondary prevention of stroke in primary care. Primary outcome measure will be the difference in systolic blood pressure between intervention and control trial arms at 12-month follow-up. Secondary outcomes will be differences in serum cholesterol, prescribing of antihypertensive drugs, statins, and antiplatelet therapy. The intervention will continue for 12 months. Information on the utilization of the decision-support tools will also be analyzed. Discussion The CRT will investigate the effectiveness of using a computer-delivered intervention to reduce the risk of stroke recurrence following a first stroke event. The study will provide methodological guidance on the implementation of CRTs in electronic databases in primary care. Trial registration Current Controlled Trials ISRCTN35701810

Study on random number generator in Monte Carlo code

International Nuclear Information System (INIS)

Oya, Kentaro; Kitada, Takanori; Tanaka, Shinichi

2011-01-01

The Monte Carlo code uses a sequence of pseudo-random numbers with a random number generator (RNG) to simulate particle histories. A pseudo-random number has its own period depending on its generation method and the period is desired to be long enough not to exceed the period during one Monte Carlo calculation to ensure the correctness especially for a standard deviation of results. The linear congruential generator (LCG) is widely used as Monte Carlo RNG and the period of LCG is not so long by considering the increasing rate of simulation histories in a Monte Carlo calculation according to the remarkable enhancement of computer performance. Recently, many kinds of RNG have been developed and some of their features are better than those of LCG. In this study, we investigate the appropriate RNG in a Monte Carlo code as an alternative to LCG especially for the case of enormous histories. It is found that xorshift has desirable features compared with LCG, and xorshift has a larger period, a comparable speed to generate random numbers, a better randomness, and good applicability to parallel calculation. (author)

Sample size methodology

CERN Document Server

Desu, M M

2012-01-01

One of the most important problems in designing an experiment or a survey is sample size determination and this book presents the currently available methodology. It includes both random sampling from standard probability distributions and from finite populations. Also discussed is sample size determination for estimating parameters in a Bayesian setting by considering the posterior distribution of the parameter and specifying the necessary requirements. The determination of the sample size is considered for ranking and selection problems as well as for the design of clinical trials. Appropria

Monte Carlo studies of two-dimensional random-anisotropy magnets

Science.gov (United States)

Denholm, D. R.; Sluckin, T. J.

1993-07-01

We have carried out a systematic set of Monte Carlo simulations of the Harris-Plischke-Zuckermann lattice model of random magnetic anisotropy on a two-dimensional square lattice, using the classical Metropolis algorithm. We have considered varying temperature T, external magnetic field H (both in the reproducible and irreproducible limits), time scale of the simulation τ in Monte Carlo steps and anisotropy ratio D/J. In the absence of randomness this model reduces to the XY model in two dimensions, which possesses the familiar Kosterlitz-Thouless low-temperature phase with algebraic but no long-range order. In the presence of random anisotropy we find evidence of a low-temperature phase with some disordered features, which might be identified with a spin-glass phase. The low-temperature Kosterlitz-Thouless phase survives at intermediate temperatures for low randomness, but is no longer present for large D/J. We have also studied the high-H approach to perfect order, for which there are theoretical predictions due to Chudnovsky.

Computing Confidence Bounds for Power and Sample Size of the General Linear Univariate Model

OpenAIRE

Taylor, Douglas J.; Muller, Keith E.

1995-01-01

The power of a test, the probability of rejecting the null hypothesis in favor of an alternative, may be computed using estimates of one or more distributional parameters. Statisticians frequently fix mean values and calculate power or sample size using a variance estimate from an existing study. Hence computed power becomes a random variable for a fixed sample size. Likewise, the sample size necessary to achieve a fixed power varies randomly. Standard statistical practice requires reporting ...

Comparison of sampling designs for estimating deforestation from landsat TM and MODIS imagery: a case study in Mato Grosso, Brazil.

Science.gov (United States)

Zhu, Shanyou; Zhang, Hailong; Liu, Ronggao; Cao, Yun; Zhang, Guixin

2014-01-01

Sampling designs are commonly used to estimate deforestation over large areas, but comparisons between different sampling strategies are required. Using PRODES deforestation data as a reference, deforestation in the state of Mato Grosso in Brazil from 2005 to 2006 is evaluated using Landsat imagery and a nearly synchronous MODIS dataset. The MODIS-derived deforestation is used to assist in sampling and extrapolation. Three sampling designs are compared according to the estimated deforestation of the entire study area based on simple extrapolation and linear regression models. The results show that stratified sampling for strata construction and sample allocation using the MODIS-derived deforestation hotspots provided more precise estimations than simple random and systematic sampling. Moreover, the relationship between the MODIS-derived and TM-derived deforestation provides a precise estimate of the total deforestation area as well as the distribution of deforestation in each block.

An experimental comparison of triggered and random pulse train uncertainties

International Nuclear Information System (INIS)

Henzlova, Daniela; Menlove, Howard O.; Swinhoe, Martyn T.

2010-01-01

response) have used only one of the two analysis methods for the nuclear material assay. The aim of this study is to provide a systematic comparison of the precision of the measured S, D, T rates and 240 Pu effective mass obtained using the above mentioned pulse train sampling techniques. In order to perform this task, a LANL developed list mode based data acquisition system is used, where the entire pulse train is recorded and subsequently analyzed. The list mode acquisition brings an essential advantage for this type of comparison, since the very same pulse train can be analyzed using signal-triggered as well as randomly triggered counting gates. The aim of this study is not only to compare the precision of signal-triggered versus random triggered sampling techniques, but also to investigate the influence of fast accidental sampling on the precision of signal-triggered results. In addition the different random sampling techniques used in safeguards are investigated. For this purpose we implement two types of random sampling - non-overlapping gates (Feynrnan approach) and periodic overlapping gates (fast accidentals). In the following sections the equations utilized in the pulse train analysis are described, experimental setup and measurement techniques are discussed and finally the results are summarized and discussed.

Assessing sample representativeness in randomized controlled trials: application to the National Institute of Drug Abuse Clinical Trials Network.

Science.gov (United States)

Susukida, Ryoko; Crum, Rosa M; Stuart, Elizabeth A; Ebnesajjad, Cyrus; Mojtabai, Ramin

2016-07-01

To compare the characteristics of individuals participating in randomized controlled trials (RCTs) of treatments of substance use disorder (SUD) with individuals receiving treatment in usual care settings, and to provide a summary quantitative measure of differences between characteristics of these two groups of individuals using propensity score methods. Design Analyses using data from RCT samples from the National Institute of Drug Abuse Clinical Trials Network (CTN) and target populations of patients drawn from the Treatment Episodes Data Set-Admissions (TEDS-A). Settings Multiple clinical trial sites and nation-wide usual SUD treatment settings in the United States. A total of 3592 individuals from 10 CTN samples and 1 602 226 individuals selected from TEDS-A between 2001 and 2009. Measurements The propensity scores for enrolling in the RCTs were computed based on the following nine observable characteristics: sex, race/ethnicity, age, education, employment status, marital status, admission to treatment through criminal justice, intravenous drug use and the number of prior treatments. Findings The proportion of those with ≥ 12 years of education and the proportion of those who had full-time jobs were significantly higher among RCT samples than among target populations (in seven and nine trials, respectively, at P difference in the mean propensity scores between the RCTs and the target population was 1.54 standard deviations and was statistically significant at P different from individuals receiving treatment in usual care settings. Notably, RCT participants tend to have more years of education and a greater likelihood of full-time work compared with people receiving care in usual care settings. © 2016 Society for the Study of Addiction.

Using Environmental Variables for Studying of the Quality of Sampling in Soil Mapping

Directory of Open Access Journals (Sweden)

A. Jafari

2016-02-01

Full Text Available Introduction: Methods of soil survey are generally empirical and based on the mental development of the surveyor, correlating soil with underlying geology, landforms, vegetation and air-photo interpretation. Since there are no statistical criteria for traditional soil sampling; this may lead to bias in the areas being sampled. In digital soil mapping, soil samples may be used to elaborate quantitative relationships or models between soil attributes and soil covariates. Because the relationships are based on the soil observations, the quality of the resulting soil map depends also on the soil observation quality. An appropriate sampling design for digital soil mapping depends on how much data is available and where the data is located. Some statistical methods have been developed for optimizing data sampling for soil surveys. Some of these methods deal with the use of ancillary information. The purpose of this study was to evaluate the quality of sampling of existing data. Materials and Methods: The study area is located in the central basin of the Iranian plateau (Figure 1. The geologic infrastructure of the area is mainly Cretaceous limestone, Mesozoic shale and sandstone. Air photo interpretation (API was used to differentiate geomorphic patterns based on their formation processes, general structure and morphometry. The patterns were differentiated through a nested geomorphic hierarchy (Fig. 2. A four-level geomorphic hierarchy is used to breakdown the complexity of different landscapes of the study area. In the lower level of the hierarchy, the geomorphic surfaces, which were formed by a unique process during a specific geologic time, were defined. A stratified sampling scheme was designed based on geomorphic mapping. In the stratified simple random sampling, the area was divided into sub-areas referred to as strata based on geomorphic surfaces, and within each stratum, sampling locations were randomly selected (Figure 2. This resulted in 191

Sampling guidelines for oral fluid-based surveys of group-housed animals.

Science.gov (United States)

Rotolo, Marisa L; Sun, Yaxuan; Wang, Chong; Giménez-Lirola, Luis; Baum, David H; Gauger, Phillip C; Harmon, Karen M; Hoogland, Marlin; Main, Rodger; Zimmerman, Jeffrey J

2017-09-01

Formulas and software for calculating sample size for surveys based on individual animal samples are readily available. However, sample size formulas are not available for oral fluids and other aggregate samples that are increasingly used in production settings. Therefore, the objective of this study was to develop sampling guidelines for oral fluid-based porcine reproductive and respiratory syndrome virus (PRRSV) surveys in commercial swine farms. Oral fluid samples were collected in 9 weekly samplings from all pens in 3 barns on one production site beginning shortly after placement of weaned pigs. Samples (n=972) were tested by real-time reverse-transcription PCR (RT-rtPCR) and the binary results analyzed using a piecewise exponential survival model for interval-censored, time-to-event data with misclassification. Thereafter, simulation studies were used to study the barn-level probability of PRRSV detection as a function of sample size, sample allocation (simple random sampling vs fixed spatial sampling), assay diagnostic sensitivity and specificity, and pen-level prevalence. These studies provided estimates of the probability of detection by sample size and within-barn prevalence. Detection using fixed spatial sampling was as good as, or better than, simple random sampling. Sampling multiple barns on a site increased the probability of detection with the number of barns sampled. These results are relevant to PRRSV control or elimination projects at the herd, regional, or national levels, but the results are also broadly applicable to contagious pathogens of swine for which oral fluid tests of equivalent performance are available. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Randomized Oversampling for Generalized Multiscale Finite Element Methods

KAUST Repository

Calo, Victor M.; Efendiev, Yalchin R.; Galvis, Juan; Li, Guanglian

2016-01-01

boundary conditions defined in a domain larger than the target region. Furthermore, we perform an eigenvalue decomposition in this small space. We study the application of randomized sampling for GMsFEM in conjunction with adaptivity, where local multiscale

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta‐analysis and group level studies

Science.gov (United States)

Bakbergenuly, Ilyas; Morgenthaler, Stephan

2016-01-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group‐level studies or in meta‐analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log‐odds and arcsine transformations of the estimated probability p^, both for single‐group studies and in combining results from several groups or studies in meta‐analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta‐analysis and result in abysmal coverage of the combined effect for large K. We also propose bias‐correction for the arcsine transformation. Our simulations demonstrate that this bias‐correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta‐analyses of prevalence. PMID:27192062

Assessment of the effect of population and diary sampling methods on estimation of school-age children exposure to fine particles.

Science.gov (United States)

Che, W W; Frey, H Christopher; Lau, Alexis K H

2014-12-01

Population and diary sampling methods are employed in exposure models to sample simulated individuals and their daily activity on each simulation day. Different sampling methods may lead to variations in estimated human exposure. In this study, two population sampling methods (stratified-random and random-random) and three diary sampling methods (random resampling, diversity and autocorrelation, and Markov-chain cluster [MCC]) are evaluated. Their impacts on estimated children's exposure to ambient fine particulate matter (PM2.5 ) are quantified via case studies for children in Wake County, NC for July 2002. The estimated mean daily average exposure is 12.9 μg/m(3) for simulated children using the stratified population sampling method, and 12.2 μg/m(3) using the random sampling method. These minor differences are caused by the random sampling among ages within census tracts. Among the three diary sampling methods, there are differences in the estimated number of individuals with multiple days of exposures exceeding a benchmark of concern of 25 μg/m(3) due to differences in how multiday longitudinal diaries are estimated. The MCC method is relatively more conservative. In case studies evaluated here, the MCC method led to 10% higher estimation of the number of individuals with repeated exposures exceeding the benchmark. The comparisons help to identify and contrast the capabilities of each method and to offer insight regarding implications of method choice. Exposure simulation results are robust to the two population sampling methods evaluated, and are sensitive to the choice of method for simulating longitudinal diaries, particularly when analyzing results for specific microenvironments or for exposures exceeding a benchmark of concern. © 2014 Society for Risk Analysis.

Measuring larval nematode contamination on cattle pastures: Comparing two herbage sampling methods.

Science.gov (United States)

Verschave, S H; Levecke, B; Duchateau, L; Vercruysse, J; Charlier, J

2015-06-15

Assessing levels of pasture larval contamination is frequently used to study the population dynamics of the free-living stages of parasitic nematodes of livestock. Direct quantification of infective larvae (L3) on herbage is the most applied method to measure pasture larval contamination. However, herbage collection remains labour intensive and there is a lack of studies addressing the variation induced by the sampling method and the required sample size. The aim of this study was (1) to compare two different sampling methods in terms of pasture larval count results and time required to sample, (2) to assess the amount of variation in larval counts at the level of sample plot, pasture and season, respectively and (3) to calculate the required sample size to assess pasture larval contamination with a predefined precision using random plots across pasture. Eight young stock pastures of different commercial dairy herds were sampled in three consecutive seasons during the grazing season (spring, summer and autumn). On each pasture, herbage samples were collected through both a double-crossed W-transect with samples taken every 10 steps (method 1) and four random located plots of 0.16 m(2) with collection of all herbage within the plot (method 2). The average (± standard deviation (SD)) pasture larval contamination using sampling methods 1 and 2 was 325 (± 479) and 305 (± 444)L3/kg dry herbage (DH), respectively. Large discrepancies in pasture larval counts of the same pasture and season were often seen between methods, but no significant difference (P = 0.38) in larval counts between methods was found. Less time was required to collect samples with method 2. This difference in collection time between methods was most pronounced for pastures with a surface area larger than 1 ha. The variation in pasture larval counts from samples generated by random plot sampling was mainly due to the repeated measurements on the same pasture in the same season (residual variance

Scalability on LHS (Latin Hypercube Sampling) samples for use in uncertainty analysis of large numerical models

International Nuclear Information System (INIS)

Baron, Jorge H.; Nunez Mac Leod, J.E.

2000-01-01

The present paper deals with the utilization of advanced sampling statistical methods to perform uncertainty and sensitivity analysis on numerical models. Such models may represent physical phenomena, logical structures (such as boolean expressions) or other systems, and various of their intrinsic parameters and/or input variables are usually treated as random variables simultaneously. In the present paper a simple method to scale-up Latin Hypercube Sampling (LHS) samples is presented, starting with a small sample and duplicating its size at each step, making it possible to use the already run numerical model results with the smaller sample. The method does not distort the statistical properties of the random variables and does not add any bias to the samples. The results is a significant reduction in numerical models running time can be achieved (by re-using the previously run samples), keeping all the advantages of LHS, until an acceptable representation level is achieved in the output variables. (author)

Predictors of Suicide Ideation in a Random Digit Dial Study: Exposure to Suicide Matters.

Science.gov (United States)

van de Venne, Judy; Cerel, Julie; Moore, Melinda; Maple, Myfanwy

2017-07-03

Suicide is an important public health concern requiring ongoing research to understand risk factors for suicide ideation. A dual-frame, random digit dial survey was utilized to identify demographic and suicide-related factors associated with suicide ideation in a statewide sample of 1,736 adults. The PH-Q 9 Depression scale suicide ideation question was used to assess current suicide ideation in both the full sample and suicide exposed sub-sample. Being non-married and having previous suicide exposure were separately associated with higher risks of suicide ideation in the full sample. Being male, having increased suicide exposures, and having increased perceptions of closeness to the decedent increased risks, while older age decreased risks for the suicide exposed. Implications for future screening and research are discussed.

Mendelian Randomization Study of Body Mass Index and Colorectal Cancer Risk

DEFF Research Database (Denmark)

Thrift, Aaron P.; Gong, Jian; Peters, Ulrike

2015-01-01

Background: High body mass index (BMI) is consistently linked to increased risk of colorectal cancer for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate...... the causal association between BMI and colorectal cancer. Methods: We used data from 10,226 colorectal cancer cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study–identified variants associated......, rather than overall obesity, is a more important risk factor for men requires further investigation. Impact: Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of colorectal cancer....

Comparison of Sampling Designs for Estimating Deforestation from Landsat TM and MODIS Imagery: A Case Study in Mato Grosso, Brazil

Directory of Open Access Journals (Sweden)

Shanyou Zhu

2014-01-01

Full Text Available Sampling designs are commonly used to estimate deforestation over large areas, but comparisons between different sampling strategies are required. Using PRODES deforestation data as a reference, deforestation in the state of Mato Grosso in Brazil from 2005 to 2006 is evaluated using Landsat imagery and a nearly synchronous MODIS dataset. The MODIS-derived deforestation is used to assist in sampling and extrapolation. Three sampling designs are compared according to the estimated deforestation of the entire study area based on simple extrapolation and linear regression models. The results show that stratified sampling for strata construction and sample allocation using the MODIS-derived deforestation hotspots provided more precise estimations than simple random and systematic sampling. Moreover, the relationship between the MODIS-derived and TM-derived deforestation provides a precise estimate of the total deforestation area as well as the distribution of deforestation in each block.

Rain dance: the role of randomization in clinical trials

Directory of Open Access Journals (Sweden)

Diniz JB

2016-07-01

Full Text Available Juliana Belo Diniz,1 Victor Fossaluza,2 Carlos Alberto de Bragança Pereira,1,2 Sergio Wechsler2 1Institute of Psychiatry, Clinics Hospital University of São Paulo Medical School, 2Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil Abstract: Randomized clinical trials are the gold standard for testing efficacy of treatment interventions. However, although randomization protects against deliberately biased samples, it does not guarantee random imbalances will not occur. Methods of intentional allocation that can overcome such deficiency of randomization have been developed, but are less frequently applied than randomization. Initially, we introduce a fictitious case example to revise and discuss the reasons of researchers' resistance to intentionally allocate instead of simply randomizing. We then introduce a real case example to evaluate the performance of an intentional protocol for allocation based on compositional data balance. A real case of allocation of 50 patients in two arms was compared with an optimal allocation of global instead of sequential arrivals. Performance was measured by a weighted average of Aitchison distances, between arms, of prognostic factors. To compare the intentional allocation with simple random allocation, 50,000 arrival orderings of 50 patients were simulated. To each one of the orders, both kinds of allocations into two arms were considered. Intentional allocation performed as well as optimal allocation in the case considered. In addition, out of the 50,000 simulated orders, 61% of them performed better with intentional allocation than random allocation. Hence, we conclude that intentional allocation should be encouraged in the design of future interventional clinical trials as a way to prevent unbalanced samples. Our sequential method is a viable alternative to overcome technical difficulties for study designs that require sequential inclusion of

Asymptotic laws for random knot diagrams

Science.gov (United States)

Chapman, Harrison

2017-06-01

We study random knotting by considering knot and link diagrams as decorated, (rooted) topological maps on spheres and pulling them uniformly from among sets of a given number of vertices n, as first established in recent work with Cantarella and Mastin. The knot diagram model is an exciting new model which captures both the random geometry of space curve models of knotting as well as the ease of computing invariants from diagrams. We prove that unknot diagrams are asymptotically exponentially rare, an analogue of Sumners and Whittington’s landmark result for self-avoiding polygons. Our proof uses the same key idea: we first show that knot diagrams obey a pattern theorem, which describes their fractal structure. We examine how quickly this behavior occurs in practice. As a consequence, almost all diagrams are asymmetric, simplifying sampling from this model. We conclude with experimental data on knotting in this model. This model of random knotting is similar to those studied by Diao et al, and Dunfield et al.

A facility specialist model for improving retention of nursing home staff: results from a randomized, controlled study.

Science.gov (United States)

Pillemer, Karl; Meador, Rhoda; Henderson, Charles; Robison, Julie; Hegeman, Carol; Graham, Edwin; Schultz, Leslie

2008-07-01

This article reports on a randomized, controlled intervention study designed to reduce employee turnover by creating a retention specialist position in nursing homes. We collected data three times over a 1-year period in 30 nursing homes, sampled in stratified random manner from facilities in New York State and Connecticut and randomly assigned to treatment and control conditions. Staff outcomes were measured through certified nursing assistant interviews, and turnover rates were measured over the course of the year. In the intervention condition, a staff member was selected to be the facility retention specialist, who would advocate for and implement programs to improve staff retention and commitment throughout the facility. Retention specialists received an intensive 3-day training in retention leadership and in a number of evidence-based retention programs. Ongoing support was provided throughout the project. Treatment facilities experienced significant declines in turnover rates compared to control facilities. As predicted, we found positive effects on certified nursing assistant assessments of the quality of retention efforts and of care provided in the facility; we did not find effects for job satisfaction or stress. The study provides evidence for the effectiveness of the retention specialist model. Findings from a detailed process evaluation suggest modifications of the program that may increase program effects.

Effects of Herbal vigRX on Premature Ejaculation: A randomized, double-blind study

Directory of Open Access Journals (Sweden)

Z Ghafuri

2010-05-01

Full Text Available Objective :   "nWe conducted a double-blind, placebo-controlled study todetermine the efficacy of an herbal sexual supplement (vigRX on premature ejaculation (PE. Method: "nA randomized double blind study was conducted on a fixed dose of herbal vigRX at Roozbeh Psychiatry Hospital, Tehran University of Medical Sciences. The sample consisted of 85 married patients diagnosed withprimary PE according to Diagnostic and Statistical Manual of Mental Disorders. Each patient underwent diagnostic evaluation by one trained psychiatrist, using Structured Clinical Interview for DSM-IV-TR. Each patient was evaluated by researchers to exclude the organic sexual dysfunctions. The patients were randomly assigned in to two groups: group 1 consisting of 42 patients receiving placebo, and group 2 consisting of 43 patients receiving 540 mg herbal vigRX for a 4-week treatment course. The effects of the drug on the ejaculatory function in each group were assessed by the intravaginal ejaculation latency time (IELT, and the Chinese Index of Premature Ejaculation (CIPE before and at the end of the treatment course. Statistical analysis was performed using SPSS software (15th version.      Results: "nThe mean IELT increased 22.4 and 32.0 seconds in the placebo and the vigRX group respectively after the treatment course. The mean IELT differences between the two groups was not significant. The mean CIPE score increased 2.40 and 4.37 in the placebo and the vigRX group respectively .The mean CIPE score differences between the two groups was not significant.No side effect was reported by the subjects in neither groups during the treatment course. "nConclusion: Although the improvement in IELT and CIPE scores in the herbal vigRX group was more than the placebo group, this difference was not statistically significant. The increasing of IELT and CIPE score in the placebo group may be due to the placebo effects. Further studies with higher vigRX doses, greater sample size

Coupling methods for multistage sampling

OpenAIRE

Chauvet, Guillaume

2015-01-01

Multistage sampling is commonly used for household surveys when there exists no sampling frame, or when the population is scattered over a wide area. Multistage sampling usually introduces a complex dependence in the selection of the final units, which makes asymptotic results quite difficult to prove. In this work, we consider multistage sampling with simple random without replacement sampling at the first stage, and with an arbitrary sampling design for further stages. We consider coupling ...

Systematic sampling of discrete and continuous populations: sample selection and the choice of estimator

Science.gov (United States)

Harry T. Valentine; David L. R. Affleck; Timothy G. Gregoire

2009-01-01

Systematic sampling is easy, efficient, and widely used, though it is not generally recognized that a systematic sample may be drawn from the population of interest with or without restrictions on randomization. The restrictions or the lack of them determine which estimators are unbiased, when using the sampling design as the basis for inference. We describe the...

A sero-survey of rinderpest in nomadic pastoral systems in central and southern Somalia from 2002 to 2003, using a spatially integrated random sampling approach.

Science.gov (United States)

Tempia, S; Salman, M D; Keefe, T; Morley, P; Freier, J E; DeMartini, J C; Wamwayi, H M; Njeumi, F; Soumaré, B; Abdi, A M

2010-12-01

A cross-sectional sero-survey, using a two-stage cluster sampling design, was conducted between 2002 and 2003 in ten administrative regions of central and southern Somalia, to estimate the seroprevalence and geographic distribution of rinderpest (RP) in the study area, as well as to identify potential risk factors for the observed seroprevalence distribution. The study was also used to test the feasibility of the spatially integrated investigation technique in nomadic and semi-nomadic pastoral systems. In the absence of a systematic list of livestock holdings, the primary sampling units were selected by generating random map coordinates. A total of 9,216 serum samples were collected from cattle aged 12 to 36 months at 562 sampling sites. Two apparent clusters of RP seroprevalence were detected. Four potential risk factors associated with the observed seroprevalence were identified: the mobility of cattle herds, the cattle population density, the proximity of cattle herds to cattle trade routes and cattle herd size. Risk maps were then generated to assist in designing more targeted surveillance strategies. The observed seroprevalence in these areas declined over time. In subsequent years, similar seroprevalence studies in neighbouring areas of Kenya and Ethiopia also showed a very low seroprevalence of RP or the absence of antibodies against RP. The progressive decline in RP antibody prevalence is consistent with virus extinction. Verification of freedom from RP infection in the Somali ecosystem is currently in progress.

MiDAS ENCORE: Randomized Controlled Study Design and Protocol.

Science.gov (United States)

Benyamin, Ramsin M; Staats, Peter S

2015-01-01

Epidural steroid injections (ESIs) are commonly used for treatment of symptomatic lumbar spinal stenosis (LSS). ESIs are generally administered after failure of conservative therapy. For LSS patients suffering from neurogenic claudication, the mild® procedure provides an alternative to ESIs via minimally invasive lumbar decompression. Both ESIs and mild offer interventional pain treatment options for LSS patients experiencing neurogenic claudication refractory to more conservative therapies. Prospective, multi-center, randomized controlled, clinical study. Twenty-six interventional pain management centers throughout the United States. To compare patient outcomes following treatment with either mild or ESIs in LSS patients with neurogenic claudication and having verified ligamentum flavum hypertrophy. Study participants include Medicare beneficiaries who meet study inclusion/exclusion criteria. Eligible patients will be randomized in a 1:1 ratio to one of 2 treatment arms, mild (treatment group) or ESI (control group). Each study group will include approximately 150 patients who have experienced neurogenic claudication symptoms for ≥ 3 months duration who have failed to respond to physical therapy, home exercise programs, and oral analgesics. Those randomized to mild are prohibited from receiving lumbar ESIs during the study period, while those randomized to ESI may receive ESIs up to 4 times per year. Patient assessments will occur at baseline, 6 months, and one year. An additional assessment will be conducted for the mild patient group at 2 years. The primary efficacy outcome measure is the proportion of Oswestry Disability Index (ODI) responders from baseline to one year follow-up in the treatment group (mild) versus the control group (ESI). ODI responders are defined as those patients achieving the validated Minimal Important Change (MIC) of ≥ 10 point improvement in ODI from baseline to follow-up as a clinically significant efficacy threshold. Secondary

Evaluating the optimal timing of surgical antimicrobial prophylaxis: study protocol for a randomized controlled trial.

Science.gov (United States)

Mujagic, Edin; Zwimpfer, Tibor; Marti, Walter R; Zwahlen, Marcel; Hoffmann, Henry; Kindler, Christoph; Fux, Christoph; Misteli, Heidi; Iselin, Lukas; Lugli, Andrea Kopp; Nebiker, Christian A; von Holzen, Urs; Vinzens, Fabrizio; von Strauss, Marco; Reck, Stefan; Kraljević, Marko; Widmer, Andreas F; Oertli, Daniel; Rosenthal, Rachel; Weber, Walter P

2014-05-24

Surgical site infections are the most common hospital-acquired infections among surgical patients. The administration of surgical antimicrobial prophylaxis reduces the risk of surgical site infections . The optimal timing of this procedure is still a matter of debate. While most studies suggest that it should be given as close to the incision time as possible, others conclude that this may be too late for optimal prevention of surgical site infections. A large observational study suggests that surgical antimicrobial prophylaxis should be administered 74 to 30 minutes before surgery. The aim of this article is to report the design and protocol of a randomized controlled trial investigating the optimal timing of surgical antimicrobial prophylaxis. In this bi-center randomized controlled trial conducted at two tertiary referral centers in Switzerland, we plan to include 5,000 patients undergoing general, oncologic, vascular and orthopedic trauma procedures. Patients are randomized in a 1:1 ratio into two groups: one receiving surgical antimicrobial prophylaxis in the anesthesia room (75 to 30 minutes before incision) and the other receiving surgical antimicrobial prophylaxis in the operating room (less than 30 minutes before incision). We expect a significantly lower rate of surgical site infections with surgical antimicrobial prophylaxis administered more than 30 minutes before the scheduled incision. The primary outcome is the occurrence of surgical site infections during a 30-day follow-up period (one year with an implant in place). When assuming a 5% surgical site infection risk with administration of surgical antimicrobial prophylaxis in the operating room, the planned sample size has an 80% power to detect a relative risk reduction for surgical site infections of 33% when administering surgical antimicrobial prophylaxis in the anesthesia room (with a two-sided type I error of 5%). We expect the study to be completed within three years. The results of this

Seroincidence of non-typhoid Salmonella infections: convenience vs. random community-based sampling.

Science.gov (United States)

Emborg, H-D; Simonsen, J; Jørgensen, C S; Harritshøj, L H; Krogfelt, K A; Linneberg, A; Mølbak, K

2016-01-01

The incidence of reported infections of non-typhoid Salmonella is affected by biases inherent to passive laboratory surveillance, whereas analysis of blood sera may provide a less biased alternative to estimate the force of Salmonella transmission in humans. We developed a mathematical model that enabled a back-calculation of the annual seroincidence of Salmonella based on measurements of specific antibodies. The aim of the present study was to determine the seroincidence in two convenience samples from 2012 (Danish blood donors, n = 500, and pregnant women, n = 637) and a community-based sample of healthy individuals from 2006 to 2007 (n = 1780). The lowest antibody levels were measured in the samples from the community cohort and the highest in pregnant women. The annual Salmonella seroincidences were 319 infections/1000 pregnant women [90% credibility interval (CrI) 210-441], 182/1000 in blood donors (90% CrI 85-298) and 77/1000 in the community cohort (90% CrI 45-114). Although the differences between study populations decreased when accounting for different age distributions the estimates depend on the study population. It is important to be aware of this issue and define a certain population under surveillance in order to obtain consistent results in an application of serological measures for public health purposes.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

Science.gov (United States)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

High Field In Vivo 13C Magnetic Resonance Spectroscopy of Brain by Random Radiofrequency Heteronuclear Decoupling and Data Sampling

Science.gov (United States)

Li, Ningzhi; Li, Shizhe; Shen, Jun

2017-06-01

In vivo 13C magnetic resonance spectroscopy (MRS) is a unique and effective tool for studying dynamic human brain metabolism and the cycling of neurotransmitters. One of the major technical challenges for in vivo 13C-MRS is the high radio frequency (RF) power necessary for heteronuclear decoupling. In the common practice of in vivo 13C-MRS, alkanyl carbons are detected in the spectra range of 10-65ppm. The amplitude of decoupling pulses has to be significantly greater than the large one-bond 1H-13C scalar coupling (1JCH=125-145 Hz). Two main proton decoupling methods have been developed: broadband stochastic decoupling and coherent composite or adiabatic pulse decoupling (e.g., WALTZ); the latter is widely used because of its efficiency and superb performance under inhomogeneous B1 field. Because the RF power required for proton decoupling increases quadratically with field strength, in vivo 13C-MRS using coherent decoupling is often limited to low magnetic fields (protons via weak long-range 1H-13C scalar couplings, which can be decoupled using low RF power broadband stochastic decoupling. Recently, the carboxylic/amide 13C-MRS technique using low power random RF heteronuclear decoupling was safely applied to human brain studies at 7T. Here, we review the two major decoupling methods and the carboxylic/amide 13C-MRS with low power decoupling strategy. Further decreases in RF power deposition by frequency-domain windowing and time-domain random under-sampling are also discussed. Low RF power decoupling opens the possibility of performing in vivo 13C experiments of human brain at very high magnetic fields (such as 11.7T), where signal-to-noise ratio as well as spatial and temporal spectral resolution are more favorable than lower fields.

Use of Matrix Sampling Procedures to Assess Achievement in Solving Open Addition and Subtraction Sentences.

Science.gov (United States)

Montague, Margariete A.

This study investigated the feasibility of concurrently and randomly sampling examinees and items in order to estimate group achievement. Seven 32-item tests reflecting a 640-item universe of simple open sentences were used such that item selection (random, systematic) and assignment (random, systematic) of items (four, eight, sixteen) to forms…

On Angular Sampling Methods for 3-D Spatial Channel Models

DEFF Research Database (Denmark)

Fan, Wei; Jämsä, Tommi; Nielsen, Jesper Ødum

2015-01-01

This paper discusses generating three dimensional (3D) spatial channel models with emphasis on the angular sampling methods. Three angular sampling methods, i.e. modified uniform power sampling, modified uniform angular sampling, and random pairing methods are proposed and investigated in detail....... The random pairing method, which uses only twenty sinusoids in the ray-based model for generating the channels, presents good results if the spatial channel cluster is with a small elevation angle spread. For spatial clusters with large elevation angle spreads, however, the random pairing method would fail...... and the other two methods should be considered....

Statistical sampling strategies

International Nuclear Information System (INIS)

Andres, T.H.

1987-01-01

Systems assessment codes use mathematical models to simulate natural and engineered systems. Probabilistic systems assessment codes carry out multiple simulations to reveal the uncertainty in values of output variables due to uncertainty in the values of the model parameters. In this paper, methods are described for sampling sets of parameter values to be used in a probabilistic systems assessment code. Three Monte Carlo parameter selection methods are discussed: simple random sampling, Latin hypercube sampling, and sampling using two-level orthogonal arrays. Three post-selection transformations are also described: truncation, importance transformation, and discretization. Advantages and disadvantages of each method are summarized

Effects of changing the random number stride in Monte Carlo calculations

International Nuclear Information System (INIS)

Hendricks, J.S.

1991-01-01

This paper reports on a common practice in Monte Carlo radiation transport codes which is to start each random walk a specified number of steps up the random number sequence from the previous one. This is called the stride in the random number sequence between source particles. It is used for correlated sampling or to provide tree-structured random numbers. A new random number generator algorithm for the major Monte Carlo code MCNP has been written to allow adjustment of the random number stride. This random number generator is machine portable. The effects of varying the stride for several sample problems are examined

Application of random amplified polymorphic DNA (RAPD) markers ...

African Journals Online (AJOL)

SAM

2014-06-11

Jun 11, 2014 ... variety share an identical genome. In this field one of the most successful techniques is random ... To each minced sample, 350 µL of the same extraction buffer was added and the samples were ..... using fingerprints produced by random primers. J. Hort. Sci. 69:123-. 130. Levi A, Rowland LJ, Hartung JS ...

Micro-Texture Synthesis by Phase Randomization

Directory of Open Access Journals (Sweden)

Bruno Galerne

2011-09-01

Full Text Available This contribution is concerned with texture synthesis by example, the process of generating new texture images from a given sample. The Random Phase Noise algorithm presented here synthesizes a texture from an original image by simply randomizing its Fourier phase. It is able to reproduce textures which are characterized by their Fourier modulus, namely the random phase textures (or micro-textures.

Treatability study sample exemption: update

International Nuclear Information System (INIS)

1997-01-01

This document is a RCRA Information Brief intended to update the information in the 1991 Small-Scale Treatability Study Information Brief, and to address questions about the waste and treatability study sample exemptions that have arisen since References 3 and 5 were published

[Saarland Growth Study: sampling design].

Science.gov (United States)

Danker-Hopfe, H; Zabransky, S

2000-01-01

The use of reference data to evaluate the physical development of children and adolescents is part of the daily routine in the paediatric ambulance. The construction of such reference data is based on the collection of extensive reference data. There are different kinds of reference data: cross sectional references, which are based on data collected from a big representative cross-sectional sample of the population, longitudinal references, which are based on follow-up surveys of usually smaller samples of individuals from birth to maturity, and mixed longitudinal references, which are a combination of longitudinal and cross-sectional reference data. The advantages and disadvantages of the different methods of data collection and the resulting reference data are discussed. The Saarland Growth Study was conducted for several reasons: growth processes are subject to secular changes, there are no specific reference data for children and adolescents from this part of the country and the growth charts in use in the paediatric praxis are possibly not appropriate any more. Therefore, the Saarland Growth Study served two purposes a) to create actual regional reference data and b) to create a database for future studies on secular trends in growth processes of children and adolescents from Saarland. The present contribution focusses on general remarks on the sampling design of (cross-sectional) growth surveys and its inferences for the design of the present study.

Online CBT life skills programme for low mood and anxiety: study protocol for a pilot randomized controlled trial.

Science.gov (United States)

Williams, Christopher; McClay, Carrie-Anne; Martinez, Rebeca; Morrison, Jill; Haig, Caroline; Jones, Ray; Farrand, Paul

2016-04-27

Low mood is a common mental health problem with significant health consequences. Studies have shown that cognitive behavioural therapy (CBT) is an effective treatment for low mood and anxiety when delivered one-to-one by an expert practitioner. However, access to this talking therapy is often limited and waiting lists can be long, although a range of low-intensity interventions that can increase access to services are available. These include guided self-help materials delivered via books, classes and online packages. This project aims to pilot a randomized controlled trial of an online CBT-based life skills course with community-based individuals experiencing low mood and anxiety. Individuals with elevated symptoms of depression will be recruited directly from the community via online and newspaper advertisements. Participants will be remotely randomized to receive either immediate access or delayed access to the Living Life to the Full guided online CBT-based life skills package, with telephone or email support provided whilst they use the online intervention. The primary end point will be at 3 months post-randomization, at which point the delayed-access group will be offered the intervention. Levels of depression, anxiety, social functioning and satisfaction will be assessed. This pilot study will test the trial design, and ability to recruit and deliver the intervention. Drop-out rates will be assessed and the completion and acceptability of the package will be investigated. The study will also inform a sample size power calculation for a subsequent substantive randomized controlled trial. ISRCTN ISRCTN12890709.

Two to five repeated measurements per patient reduced the required sample size considerably in a randomized clinical trial for patients with inflammatory rheumatic diseases

Directory of Open Access Journals (Sweden)

Smedslund Geir

2013-02-01

Full Text Available Abstract Background Patient reported outcomes are accepted as important outcome measures in rheumatology. The fluctuating symptoms in patients with rheumatic diseases have serious implications for sample size in clinical trials. We estimated the effects of measuring the outcome 1-5 times on the sample size required in a two-armed trial. Findings In a randomized controlled trial that evaluated the effects of a mindfulness-based group intervention for patients with inflammatory arthritis (n=71, the outcome variables Numerical Rating Scales (NRS (pain, fatigue, disease activity, self-care ability, and emotional wellbeing and General Health Questionnaire (GHQ-20 were measured five times before and after the intervention. For each variable we calculated the necessary sample sizes for obtaining 80% power (α=.05 for one up to five measurements. Two, three, and four measures reduced the required sample sizes by 15%, 21%, and 24%, respectively. With three (and five measures, the required sample size per group was reduced from 56 to 39 (32 for the GHQ-20, from 71 to 60 (55 for pain, 96 to 71 (73 for fatigue, 57 to 51 (48 for disease activity, 59 to 44 (45 for self-care, and 47 to 37 (33 for emotional wellbeing. Conclusions Measuring the outcomes five times rather than once reduced the necessary sample size by an average of 27%. When planning a study, researchers should carefully compare the advantages and disadvantages of increasing sample size versus employing three to five repeated measurements in order to obtain the required statistical power.

A randomized multifactorial intervention study for prevention of ischaemic heart disease (Inter99): the long-term effect on physical activity

DEFF Research Database (Denmark)

von Huth Smith, Lisa; Ladelund, Steen; Borch-Johnsen, Knut

2008-01-01

, group B, n=1,308) were invited for a health examination, an assessment of absolute risk of developing IHD, and an individualized lifestyle intervention. The participation rate was 52.5%. High-risk persons in group A were also offered diet/physical activity and/or smoking cessation group counselling....... High-risk persons in group B were referred to their GP. High-risk persons were re-counselled after 12 and 36 months. The control group (group C, n=5,264, response rate=61.3%) answered a mailed questionnaire. Data were analysed using longitudinal linear regression models with random effects. MAIN......AIM: To examine the effect of a randomized multiple risk factor intervention study for prevention of ischaemic heart disease (IHD) on the development in physical activity over a 36-month period. METHODS: Two random samples (high intensity intervention, group A, n=11,708; low intensity intervention...

A randomized multifactorial intervention study for prevention of ischaemic heart disease (Inter99): The long-term effect on physical activity

DEFF Research Database (Denmark)

Smith, L.V.H.; Ladelund, S.; Borch-Johnsen, K.

2008-01-01

, group B, n=1,308) were invited for a health examination, an assessment of absolute risk of developing IHD, and an individualized lifestyle intervention. The participation rate was 52.5%. High-risk persons in group A were also offered diet/physical activity and/or smoking cessation group counselling....... High-risk persons in group B were referred to their GP. High-risk persons were re-counselled after 12 and 36 months. The control group (group C, n=5,264, response rate=61.3%) answered a mailed questionnaire. Data were analysed using longitudinal linear regression models with random effects. MAIN......AIM: To examine the effect of a randomized multiple risk factor intervention study for prevention of ischaemic heart disease (IHD) on the development in physical activity over a 36-month period. METHODS: Two random samples (high intensity intervention, group A, n=11,708; low intensity intervention...

Groundwater-quality data in 12 GAMA study units: Results from the 2006–10 initial sampling period and the 2008–13 trend sampling period, California GAMA Priority Basin Project

Science.gov (United States)

Mathany, Timothy M.

2017-03-09

The Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) program was developed in response to the Groundwater Quality Monitoring Act of 2001 and is being conducted by the U.S. Geological Survey in cooperation with the California State Water Resources Control Board. From 2004 through 2012, the GAMA-PBP collected samples and assessed the quality of groundwater resources that supply public drinking water in 35 study units across the State. Selected sites in each study unit were sampled again approximately 3 years after initial sampling as part of an assessment of temporal trends in water quality by the GAMA-PBP. Twelve of the study units, initially sampled during 2006–11 (initial sampling period) and sampled a second time during 2008–13 (trend sampling period) to assess temporal trends, are the subject of this report.The initial sampling was designed to provide a spatially unbiased assessment of the quality of untreated groundwater used for public water supplies in the 12 study units. In these study units, 550 sampling sites were selected by using a spatially distributed, randomized, grid-based method to provide spatially unbiased representation of the areas assessed (grid sites, also called “status sites”). After the initial sampling period, 76 of the previously sampled status sites (approximately 10 percent in each study unit) were randomly selected for trend sampling (“trend sites”). The 12 study units sampled both during the initial sampling and during the trend sampling period were distributed among 6 hydrogeologic provinces: Coastal (Northern and Southern), Transverse Ranges and Selected Peninsular Ranges, Klamath, Modoc Plateau and Cascades, and Sierra Nevada Hydrogeologic Provinces. For the purposes of this trend report, the six hydrogeologic provinces were grouped into two hydrogeologic regions based on location: Coastal and Mountain.The groundwater samples were analyzed for a number of synthetic organic

Influence of random setup error on dose distribution

International Nuclear Information System (INIS)

Zhai Zhenyu

2008-01-01

Objective: To investigate the influence of random setup error on dose distribution in radiotherapy and determine the margin from ITV to PTV. Methods: A random sample approach was used to simulate the fields position in target coordinate system. Cumulative effect of random setup error was the sum of dose distributions of all individual treatment fractions. Study of 100 cumulative effects might get shift sizes of 90% dose point position. Margins from ITV to PTV caused by random setup error were chosen by 95% probability. Spearman's correlation was used to analyze the influence of each factor. Results: The average shift sizes of 90% dose point position was 0.62, 1.84, 3.13, 4.78, 6.34 and 8.03 mm if random setup error was 1,2,3,4,5 and 6 mm,respectively. Univariate analysis showed the size of margin was associated only by the size of random setup error. Conclusions: Margin of ITV to PTV is 1.2 times random setup error for head-and-neck cancer and 1.5 times for thoracic and abdominal cancer. Field size, energy and target depth, unlike random setup error, have no relation with the size of the margin. (authors)

Towards Cost-efficient Sampling Methods

OpenAIRE

Peng, Luo; Yongli, Li; Chong, Wu

2014-01-01

The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper presents two new sampling methods based on the perspective that a small part of vertices with high node degree can possess the most structure information of a network. The two proposed sampling methods are efficient in sampling the nodes with high degree. The first new sampling method is improved on the basis of the stratified random sampling method and...

Effectiveness of Wii-based rehabilitation in stroke: A randomized controlled study

OpenAIRE

Ayça Utkan Karasu; Elif Balevi Batur; Gülçin Kaymak Karataş

2018-01-01

Objective: To investigate the efficacy of Nintendo Wii Fit®-based balance rehabilitation as an adjunc-tive therapy to conventional rehabilitation in stroke patients. Methods: During the study period, 70 stroke patients were evaluated. Of these, 23 who met the study criteria were randomly assigned to either the experimental group (n = 12) or the control group (n = 11) by block randomization. Primary outcome measures were Berg Balance Scale, Functional Reach Test, Postural Asses...

Recovery from work-related stress: a randomized controlled trial of a stress management intervention in a clinical sample.

Science.gov (United States)

Glasscock, David J; Carstensen, Ole; Dalgaard, Vita Ligaya

2018-05-28

Randomized controlled trials (RCTs) of interventions aimed at reducing work-related stress indicate that cognitive behavioural therapy (CBT) is more effective than other interventions. However, definitions of study populations are often unclear and there is a lack of interventions targeting both the individual and the workplace. The aim of this study was to determine whether a stress management intervention combining individual CBT and a workplace focus is superior to no treatment in the reduction of perceived stress and stress symptoms and time to lasting return to work (RTW) in a clinical sample. Patients with work-related stress reactions or adjustment disorders were randomly assigned to an intervention group (n = 57, 84.2% female) or a control group (n = 80, 83.8% female). Subjects were followed via questionnaires and register data. The intervention contained individual CBT and the offer of a workplace meeting. We examined intervention effects by analysing group differences in score changes on the Perceived Stress Scale (PSS-10) and the General Health Questionnaire (GHQ-30). We also tested if intervention led to faster lasting RTW. Mean baseline values of PSS were 24.79 in the intervention group and 23.26 in the control group while the corresponding values for GHQ were 21.3 and 20.27, respectively. There was a significant effect of time. 10 months after baseline, both groups reported less perceived stress and improved mental health. 4 months after baseline, we found significant treatment effects for both perceived stress and mental health. The difference in mean change in PSS after 4 months was - 3.09 (- 5.47, - 0.72), while for GHQ it was - 3.91 (- 7.15, - 0.68). There were no group differences in RTW. The intervention led to faster reductions in perceived stress and stress symptoms amongst patients with work-related stress reactions and adjustment disorders. 6 months after the intervention ended there were no longer differences between

Topics in random walks in random environment

International Nuclear Information System (INIS)

Sznitman, A.-S.

2004-01-01

Over the last twenty-five years random motions in random media have been intensively investigated and some new general methods and paradigms have by now emerged. Random walks in random environment constitute one of the canonical models of the field. However in dimension bigger than one they are still poorly understood and many of the basic issues remain to this day unresolved. The present series of lectures attempt to give an account of the progresses which have been made over the last few years, especially in the study of multi-dimensional random walks in random environment with ballistic behavior. (author)

Study on Nonlinear Vibration Analysis of Gear System with Random Parameters

Science.gov (United States)

Tong, Cao; Liu, Xiaoyuan; Fan, Li

2018-03-01

In order to study the dynamic characteristics of gear nonlinear vibration system and the influence of random parameters, firstly, a nonlinear stochastic vibration analysis model of gear 3-DOF is established based on Newton’s Law. And the random response of gear vibration is simulated by stepwise integration method. Secondly, the influence of stochastic parameters such as meshing damping, tooth side gap and excitation frequency on the dynamic response of gear nonlinear system is analyzed by using the stability analysis method such as bifurcation diagram and Lyapunov exponent method. The analysis shows that the stochastic process can not be neglected, which can cause the random bifurcation and chaos of the system response. This study will provide important reference value for vibration engineering designers.

Subrandom methods for multidimensional nonuniform sampling.

Science.gov (United States)

Worley, Bradley

2016-08-01

Methods of nonuniform sampling that utilize pseudorandom number sequences to select points from a weighted Nyquist grid are commonplace in biomolecular NMR studies, due to the beneficial incoherence introduced by pseudorandom sampling. However, these methods require the specification of a non-arbitrary seed number in order to initialize a pseudorandom number generator. Because the performance of pseudorandom sampling schedules can substantially vary based on seed number, this can complicate the task of routine data collection. Approaches such as jittered sampling and stochastic gap sampling are effective at reducing random seed dependence of nonuniform sampling schedules, but still require the specification of a seed number. This work formalizes the use of subrandom number sequences in nonuniform sampling as a means of seed-independent sampling, and compares the performance of three subrandom methods to their pseudorandom counterparts using commonly applied schedule performance metrics. Reconstruction results using experimental datasets are also provided to validate claims made using these performance metrics. Copyright © 2016 Elsevier Inc. All rights reserved.

Sampling strategy to develop a primary core collection of apple ...

African Journals Online (AJOL)

PRECIOUS

2010-01-11

Jan 11, 2010 ... Physiology and Molecular Biology for Fruit, Tree, Beijing 100193, China. ... analyzed on genetic diversity to ensure their represen- .... strategy, cluster and random sampling. .... on isozyme data―A simulation study, Theor.

Sampling in epidemiological research: issues, hazards and pitfalls

Science.gov (United States)

Tyrer, Stephen; Heyman, Bob

2016-01-01

Surveys of people's opinions are fraught with difficulties. It is easier to obtain information from those who respond to text messages or to emails than to attempt to obtain a representative sample. Samples of the population that are selected non-randomly in this way are termed convenience samples as they are easy to recruit. This introduces a sampling bias. Such non-probability samples have merit in many situations, but an epidemiological enquiry is of little value unless a random sample is obtained. If a sufficient number of those selected actually complete a survey, the results are likely to be representative of the population. This editorial describes probability and non-probability sampling methods and illustrates the difficulties and suggested solutions in performing accurate epidemiological research. PMID:27087985

Monte Carlo method for random surfaces

International Nuclear Information System (INIS)

Berg, B.

1985-01-01

Previously two of the authors proposed a Monte Carlo method for sampling statistical ensembles of random walks and surfaces with a Boltzmann probabilistic weight. In the present paper we work out the details for several models of random surfaces, defined on d-dimensional hypercubic lattices. (orig.)

Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses.

Science.gov (United States)

Zhang, Wenbing; Tang, Yang; Huang, Tingwen; Kurths, Jurgen

In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

Science.gov (United States)

Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

2016-07-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Experimental and Sampling Design for the INL-2 Sample Collection Operational Test

Energy Technology Data Exchange (ETDEWEB)

Piepel, Gregory F.; Amidan, Brett G.; Matzke, Brett D.

2009-02-16

, sample extraction, and analytical methods to be used in the INL-2 study. For each of the five test events, the specified floor of the INL building will be contaminated with BG using a point-release device located in the room specified in the experimental design. Then quality control (QC), reference material coupon (RMC), judgmental, and probabilistic samples will be collected according to the sampling plan for each test event. Judgmental samples will be selected based on professional judgment and prior information. Probabilistic samples were selected with a random aspect and in sufficient numbers to provide desired confidence for detecting contamination or clearing uncontaminated (or decontaminated) areas. Following sample collection for a given test event, the INL building will be decontaminated. For possibly contaminated areas, the numbers of probabilistic samples were chosen to provide 95% confidence of detecting contaminated areas of specified sizes. For rooms that may be uncontaminated following a contamination event, or for whole floors after decontamination, the numbers of judgmental and probabilistic samples were chosen using the CJR approach. The numbers of samples were chosen to support making X%/Y% clearance statements with X = 95% or 99% and Y = 96% or 97%. The experimental and sampling design also provides for making X%/Y% clearance statements using only probabilistic samples. For each test event, the numbers of characterization and clearance samples were selected within limits based on operational considerations while still maintaining high confidence for detection and clearance aspects. The sampling design for all five test events contains 2085 samples, with 1142 after contamination and 943 after decontamination. These numbers include QC, RMC, judgmental, and probabilistic samples. The experimental and sampling design specified in this report provides a good statistical foundation for achieving the objectives of the INL-2 study.

The High/Scope Perry Preschool Study: A Case Study in Random Assignment.

Science.gov (United States)

Schweinhart, Lawrence J.

2000-01-01

Studied the long-term benefits of preschool programs for young children living in poverty in the High/Scope Perry Preschool Study, which examined the lives of 123 African Americans randomly divided into a preschool treatment group and a no-preschool comparison group. Cost-benefit analyses of data on these students to age 27 show beneficial effects…

The relationship between blood viscosity and blood pressure in a random sample of the population aged 55 to 74 years.

Science.gov (United States)

Fowkes, F G; Lowe, G D; Rumley, A; Lennie, S E; Smith, F B; Donnan, P T

1993-05-01

Blood viscosity is elevated in hypertensive subjects, but the association of viscosity with arterial blood pressure in the general population, and the influence of social, lifestyle and disease characteristics on this association, are not established. In the Edinburgh Artery Study, 1592 men and women aged 55-74 years selected randomly from the general population attended a university clinic. A fasting blood sample was taken for the measurement of blood viscosity and its major determinants (haematocrit, plasma viscosity and fibrinogen). Systolic pressure was related univariately to blood viscosity (P viscosity (P index. Diastolic pressure was related univariately to blood viscosity (P viscosity (P viscosity and systolic pressure was confined to males. Blood viscosity was associated equally with systolic and diastolic pressures in males, and remained independently related on multivariate analysis adjusting for age, sex, body mass index, social class, smoking, alcohol intake, exercise, angina, HDL and non-HDL cholesterol, diabetes mellitus, plasma viscosity, fibrinogen, and haematocrit.

Creating ensembles of decision trees through sampling

Science.gov (United States)

Kamath, Chandrika; Cantu-Paz, Erick

2005-08-30

A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies1

Science.gov (United States)

Bowden, Jack; Relton, Caroline; Davey Smith, George

2016-01-01

Mendelian randomization (MR) is an increasingly important tool for appraising causality in observational epidemiology. The technique exploits the principle that genotypes are not generally susceptible to reverse causation bias and confounding, reflecting their fixed nature and Mendel’s first and second laws of inheritance. The approach is, however, subject to important limitations and assumptions that, if unaddressed or compounded by poor study design, can lead to erroneous conclusions. Nevertheless, the advent of 2-sample approaches (in which exposure and outcome are measured in separate samples) and the increasing availability of open-access data from large consortia of genome-wide association studies and population biobanks mean that the approach is likely to become routine practice in evidence synthesis and causal inference research. In this article we provide an overview of the design, analysis, and interpretation of MR studies, with a special emphasis on assumptions and limitations. We also consider different analytic strategies for strengthening causal inference. Although impossible to prove causality with any single approach, MR is a highly cost-effective strategy for prioritizing intervention targets for disease prevention and for strengthening the evidence base for public health policy. PMID:26961927

A study of western pharmaceuticals contained within samples of Chinese herbal/patent medicines collected from New York City's Chinatown.

Science.gov (United States)

Miller, Gretchen M; Stripp, Richard

2007-09-01

In America, recent growth in the popularity of Chinese herbal/patent medicines (CHM/CPM) has generated concerns as to the safety of these and other herbal remedies. Lack of strict federal regulations has lead to the possibility of improper labeling and even adulteration of these products with western drugs or other chemical contaminants. Our laboratory has conducted an analytical study to determine the presence of undeclared pharmaceuticals and therapeutic substances within CHM/CPM sold in New York City's Chinatown. Ninety representative samples randomly purchased in the form of pills, tablets, creams and teas were screened by appropriate analytical techniques including TLC, GC/MS and HPLC. Five samples contained nine different western pharmaceuticals. Two of these samples contained undeclared or mislabeled substances. One sample contained two pharmaceuticals contraindicated in people for whom the product was intended. Drugs identified include promethazine, chlormethiazole, chlorpheniramine, diclofenac, chlordiazepoxide, hydrochlorothiazide, triamterene, diphenhydramine and sildenafil citrate (Viagra).

Random numbers spring from alpha decay

International Nuclear Information System (INIS)

Frigerio, N.A.; Sanathanan, L.P.; Morley, M.; Clark, N.A.; Tyler, S.A.

1980-05-01

Congruential random number generators, which are widely used in Monte Carlo simulations, are deficient in that the number they generate are concentrated in a relatively small number of hyperplanes. While this deficiency may not be a limitation in small Monte Carlo studies involving a few variables, it introduces a significant bias in large simulations requiring high resolution. This bias was recognized and assessed during preparations for an accident analysis study of nuclear power plants. This report describes a random number device based on the radioactive decay of alpha particles from a 235 U source in a high-resolution gas proportional counter. The signals were fed to a 4096-channel analyzer and for each channel the frequency of signals registered in a 20,000-microsecond interval was recorded. The parity bits of these frequency counts (0 for an even count and 1 for an odd count) were then assembled in sequence to form 31-bit binary random numbers and transcribed to a magnetic tape. This cycle was repeated as many times as were necessary to create 3 million random numbers. The frequency distribution of counts from the present device conforms to the Brockwell-Moyal distribution, which takes into account the dead time of the counter (both the dead time and decay constant of the underlying Poisson process were estimated). Analysis of the count data and tests of randomness on a sample set of the 31-bit binary numbers indicate that this random number device is a highly reliable source of truly random numbers. Its use is, therefore, recommended in Monte Carlo simulations for which the congruential pseudorandom number generators are found to be inadequate. 6 figures, 5 tables

Inferences about Variance Components and Reliability-Generalizability Coefficients in the Absence of Random Sampling.

Science.gov (United States)

Kane, Michael

2002-01-01

Reviews the criticisms of sampling assumptions in generalizability theory (and in reliability theory) and examines the feasibility of using representative sampling, stratification, homogeneity assumptions, and replications to address these criticisms. Suggests some general outlines for the conduct of generalizability theory studies. (SLD)

A random matrix approach to VARMA processes

International Nuclear Information System (INIS)

Burda, Zdzislaw; Jarosz, Andrzej; Nowak, Maciej A; Snarska, Malgorzata

2010-01-01

We apply random matrix theory to derive the spectral density of large sample covariance matrices generated by multivariate VMA(q), VAR(q) and VARMA(q 1 , q 2 ) processes. In particular, we consider a limit where the number of random variables N and the number of consecutive time measurements T are large but the ratio N/T is fixed. In this regime, the underlying random matrices are asymptotically equivalent to free random variables (FRV). We apply the FRV calculus to calculate the eigenvalue density of the sample covariance for several VARMA-type processes. We explicitly solve the VARMA(1, 1) case and demonstrate perfect agreement between the analytical result and the spectra obtained by Monte Carlo simulations. The proposed method is purely algebraic and can be easily generalized to q 1 >1 and q 2 >1.

Disentangling Complexity from Randomness and Chaos

Directory of Open Access Journals (Sweden)

Lena C. Zuchowski

2012-02-01

Full Text Available This study aims to disentangle complexity from randomness and chaos, and to present a definition of complexity that emphasizes its epistemically distinct qualities. I will review existing attempts at defining complexity and argue that these suffer from two major faults: a tendency to neglect the underlying dynamics and to focus exclusively on the phenomenology of complex systems; and linguistic imprecisions in describing these phenomenologies. I will argue that the tendency to discuss phenomenology removed from the underlying dynamics is the main root of the difficulties in distinguishing complex from chaotic or random systems. In my own definition, I will explicitly try to avoid these pitfalls. The theoretical contemplations in this paper will be tested on a sample of five models: the random Kac ring, the chaotic CA30, the regular CA90, the complex CA110 and the complex Bak-Sneppen model. Although these modelling studies are restricted in scope and can only be seen as preliminary, they still constitute on of the first attempts to investigate complex systems comparatively.

Monolith Chromatography as Sample Preparation Step in Virome Studies of Water Samples.

Science.gov (United States)

Gutiérrez-Aguirre, Ion; Kutnjak, Denis; Rački, Nejc; Rupar, Matevž; Ravnikar, Maja

2018-01-01

Viruses exist in aquatic media and many of them use this media as transmission route. Next-generation sequencing (NGS) technologies have opened new doors in virus research, allowing also to reveal a hidden diversity of viral species in aquatic environments. Not surprisingly, many of the newly discovered viruses are found in environmental fresh and marine waters. One of the problems in virome research can be the low amount of viral nucleic acids present in the sample in contrast to the background ones (host, eukaryotic, prokaryotic, environmental). Therefore, virus enrichment prior to NGS is necessary in many cases. In water samples, an added problem resides in the low concentration of viruses typically present in aquatic media. Different concentration strategies have been used to overcome such limitations. CIM monoliths are a new generation of chromatographic supports that due to their particular structural characteristics are very efficient in concentration and purification of viruses. In this chapter, we describe the use of CIM monolithic chromatography for sample preparation step in NGS studies targeting viruses in fresh or marine water. The step-by-step protocol will include a case study where CIM concentration was used to study the virome of a wastewater sample using NGS.

Random Walks on Directed Networks: Inference and Respondent-Driven Sampling

Directory of Open Access Journals (Sweden)

Malmros Jens

2016-06-01

Full Text Available Respondent-driven sampling (RDS is often used to estimate population properties (e.g., sexual risk behavior in hard-to-reach populations. In RDS, already sampled individuals recruit population members to the sample from their social contacts in an efficient snowball-like sampling procedure. By assuming a Markov model for the recruitment of individuals, asymptotically unbiased estimates of population characteristics can be obtained. Current RDS estimation methodology assumes that the social network is undirected, that is, all edges are reciprocal. However, empirical social networks in general also include a substantial number of nonreciprocal edges. In this article, we develop an estimation method for RDS in populations connected by social networks that include reciprocal and nonreciprocal edges. We derive estimators of the selection probabilities of individuals as a function of the number of outgoing edges of sampled individuals. The proposed estimators are evaluated on artificial and empirical networks and are shown to generally perform better than existing estimators. This is the case in particular when the fraction of directed edges in the network is large.

Piroxicam immediate release formulations: A fasting randomized open-label crossover bioequivalence study in healthy volunteers.

Science.gov (United States)

Helmy, Sally A; El-Bedaiwy, Heba M

2014-11-01

Piroxicam is a NSAID with analgesic and antipyretic properties, used for the treatment of rheumatoid diseases. The aim of this study was to evaluate the bioequivalence of two brands of piroxicam capsules (20 mg) in 24 Egyptian volunteers. The in vivo study was established according to a single-center, randomized, single-dose, laboratory-blinded, 2-period, 2-sequence, crossover study with a washout period of 3 weeks. Under fasting conditions, 24 healthy male volunteers were randomly selected to receive a single oral dose of one capsule (20 mg) of either test or reference product. Plasma samples were obtained over a 144-hour interval and analyzed for piroxicam by HPLC with UV detection. The pharmacokinetic parameters Cmax , tmax , AUC0-t , AUC0-∞ , Vd /F, Cl/F, and t1/2 were determined from plasma concentration-time profiles. The 90% confidence intervals for the ratio of log transformed values of Cmax , AUC0-t , and AUC0-∞ of the two treatments were within the acceptable range (0.8-1.25) for bioequivalence. From PK perspectives, the two piroxicam formulations were considered bioequivalent, based on the rate and extent of absorption. No adverse events occurred or were reported after a single 20-mg piroxicam and both formulations were well-tolerated. © 2014, The American College of Clinical Pharmacology.

Network meta-analysis incorporating randomized controlled trials and non-randomized comparative cohort studies for assessing the safety and effectiveness of medical treatments: challenges and opportunities

OpenAIRE

Cameron, Chris; Fireman, Bruce; Hutton, Brian; Clifford, Tammy; Coyle, Doug; Wells, George; Dormuth, Colin R.; Platt, Robert; Toh, Sengwee

2015-01-01

Network meta-analysis is increasingly used to allow comparison of multiple treatment alternatives simultaneously, some of which may not have been compared directly in primary research studies. The majority of network meta-analyses published to date have incorporated data from randomized controlled trials (RCTs) only; however, inclusion of non-randomized studies may sometimes be considered. Non-randomized studies can complement RCTs or address some of their limitations, such as short follow-up...

The Effect of Iron Status on Risk of Coronary Artery Disease: A Mendelian Randomization Study-Brief Report.

Science.gov (United States)

Gill, Dipender; Del Greco M, Fabiola; Walker, Ann P; Srai, Surjit K S; Laffan, Michael A; Minelli, Cosetta

2017-09-01

Iron status is a modifiable trait that has been implicated in cardiovascular disease. This study uses the Mendelian randomization technique to investigate whether there is any causal effect of iron status on risk of coronary artery disease (CAD). A 2-sample Mendelian randomization approach is used to estimate the effect of iron status on CAD risk. Three loci (rs1800562 and rs1799945 in the HFE gene and rs855791 in TMPRSS6 ) that are each associated with serum iron, transferrin saturation, ferritin, and transferrin in a pattern suggestive of an association with systemic iron status are used as instruments. SNP (single-nucleotide polymorphism)-iron status association estimates are based on a genome-wide association study meta-analysis of 48 972 individuals. SNP-CAD estimates are derived by combining the results of a genome-wide association study meta-analysis of 60 801 CAD cases and 123 504 controls with those of a meta-analysis of 63 746 CAD cases and 130 681 controls obtained from Metabochip and genome-wide association studies. Combined Mendelian randomization estimates are obtained for each marker by pooling results across the 3 instruments. We find evidence of a protective effect of higher iron status on CAD risk (iron odds ratio, 0.94 per SD unit increase; 95% confidence interval, 0.88-1.00; P =0.039; transferrin saturation odds ratio, 0.95 per SD unit increase; 95% confidence interval, 0.91-0.99; P =0.027; log-transformed ferritin odds ratio, 0.85 per SD unit increase; 95% confidence interval, 0.73-0.98; P =0.024; and transferrin odds ratio, 1.08 per SD unit increase; 95% confidence interval, 1.01-1.16; P =0.034). This Mendelian randomization study supports the hypothesis that higher iron status reduces CAD risk. These findings may highlight a therapeutic target. © 2017 American Heart Association, Inc.

Buspirone Versus Methylphenidate in the Treatment of Children with Attention- Deficit/ Hyperactivity Disorder: Randomized Double-Blind Study

Directory of Open Access Journals (Sweden)

Shahin Akhondzadeh

2012-11-01

Full Text Available A recent randomized clinical trial showed buspirone efficacy in the treatment of attention-deficit/hyperactivity disorder (ADHD in children. However, results from a recent multi-site controlled clinical trial of transdermal buspirone failed to separate it from placebo in a large sample of children with ADHD. Therefore, due to these inconsistent findings, this study was designed to assess the efficacy of buspirone in the treatment of children with ADHD compared to methylphenidate in a double blind randomized clinical trial. Forty outpatients with a DSM-IV-TR diagnosis of ADHD were study population of this trial. Subjects were recruited from an outpatient child and adolescent clinic for a 6 week double blind, randomized clinical trial. All study subjects were randomly assigned to receive treatment using tablet of buspirone at a dose of 20-30 mg/day depending on weight (20 mg/day for 30kg (group 1 or methylphenidate at a dose of 20-30 mg/day depending on weight (20 mg/day for 30kg (group 2 for a 6 week double blind, randomized clinical trial. The principal measure of outcome was the Teacher and Parent ADHD Rating Scale IV. Patients were assessed at baseline and at 21 and 42 days after the medication started. Significant differences were observed between the two groups on the Parent and Teacher Rating Scale scores. The changes at the endpoint compared to baseline were: -8.95±8.73 (mean±SD and -15.60±7.81 (mean±SD for buspirone and methyphenidate, for Parent ADHD Rating Scale. The changes at the endpoint compared to baseline were: -9.80 ±7.06 (mean±SD and -22.40±9.90 (mean±SD for buspirone and methyphenidate, respectively for Teacher ADHD Rating Scale. The difference between the buspirone and methylphenidate groups in the frequency of side effects was not significant except for decreased appetite, headache and insomnia that were observed more frequently in the methylphenidate group. The results of this study suggest that administration of

Open-Label Randomized Trial of Titrated Disease Management for Patients with Hypertension: Study Design and Baseline Sample Characteristics

Science.gov (United States)

Jackson, George L.; Weinberger, Morris; Kirshner, Miriam A.; Stechuchak, Karen M.; Melnyk, Stephanie D.; Bosworth, Hayden B.; Coffman, Cynthia J.; Neelon, Brian; Van Houtven, Courtney; Gentry, Pamela W.; Morris, Isis J.; Rose, Cynthia M.; Taylor, Jennifer P.; May, Carrie L.; Han, Byungjoo; Wainwright, Christi; Alkon, Aviel; Powell, Lesa; Edelman, David

2016-01-01

Despite the availability of efficacious treatments, only half of patients with hypertension achieve adequate blood pressure (BP) control. This paper describes the protocol and baseline subject characteristics of a 2-arm, 18-month randomized clinical trial of titrated disease management (TDM) for patients with pharmaceutically-treated hypertension for whom systolic blood pressure (SBP) is not controlled (≥140mmHg for non-diabetic or ≥130mmHg for diabetic patients). The trial is being conducted among patients of four clinic locations associated with a Veterans Affairs Medical Center. An intervention arm has a TDM strategy in which patients' hypertension control at baseline, 6, and 12 months determines the resource intensity of disease management. Intensity levels include: a low-intensity strategy utilizing a licensed practical nurse to provide bi-monthly, non-tailored behavioral support calls to patients whose SBP comes under control; medium-intensity strategy utilizing a registered nurse to provide monthly tailored behavioral support telephone calls plus home BP monitoring; and high-intensity strategy utilizing a pharmacist to provide monthly tailored behavioral support telephone calls, home BP monitoring, and pharmacist-directed medication management. Control arm patients receive the low-intensity strategy regardless of BP control. The primary outcome is SBP. There are 385 randomized (192 intervention; 193 control) veterans that are predominately older (mean age 63.5 years) men (92.5%). 61.8% are African American, and the mean baseline SBP for all subjects is 143.6mmHg. This trial will determine if a disease management program that is titrated by matching the intensity of resources to patients' BP control leads to superior outcomes compared to a low-intensity management strategy. PMID:27417982

Sampling from the normal and exponential distributions

International Nuclear Information System (INIS)

Chaplin, K.R.; Wills, C.A.

1982-01-01

Methods for generating random numbers from the normal and exponential distributions are described. These involve dividing each function into subregions, and for each of these developing a method of sampling usually based on an acceptance rejection technique. When sampling from the normal or exponential distribution, each subregion provides the required random value with probability equal to the ratio of its area to the total area. Procedures written in FORTRAN for the CYBER 175/CDC 6600 system are provided to implement the two algorithms

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence

Directory of Open Access Journals (Sweden)

Chunrong Mi

2017-01-01

Full Text Available Species distribution models (SDMs have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane (Grus monacha, n = 33, White-naped Crane (Grus vipio, n = 40, and Black-necked Crane (Grus nigricollis, n = 75 in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model, Random Forest, CART (Classification and Regression Tree and Maxent (Maximum Entropy Models. In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC and true skill statistic (TSS were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid

Why choose Random Forest to predict rare species distribution with few samples in large undersampled areas? Three Asian crane species models provide supporting evidence.

Science.gov (United States)

Mi, Chunrong; Huettmann, Falk; Guo, Yumin; Han, Xuesong; Wen, Lijia

2017-01-01

Species distribution models (SDMs) have become an essential tool in ecology, biogeography, evolution and, more recently, in conservation biology. How to generalize species distributions in large undersampled areas, especially with few samples, is a fundamental issue of SDMs. In order to explore this issue, we used the best available presence records for the Hooded Crane ( Grus monacha , n  = 33), White-naped Crane ( Grus vipio , n  = 40), and Black-necked Crane ( Grus nigricollis , n  = 75) in China as three case studies, employing four powerful and commonly used machine learning algorithms to map the breeding distributions of the three species: TreeNet (Stochastic Gradient Boosting, Boosted Regression Tree Model), Random Forest, CART (Classification and Regression Tree) and Maxent (Maximum Entropy Models). In addition, we developed an ensemble forecast by averaging predicted probability of the above four models results. Commonly used model performance metrics (Area under ROC (AUC) and true skill statistic (TSS)) were employed to evaluate model accuracy. The latest satellite tracking data and compiled literature data were used as two independent testing datasets to confront model predictions. We found Random Forest demonstrated the best performance for the most assessment method, provided a better model fit to the testing data, and achieved better species range maps for each crane species in undersampled areas. Random Forest has been generally available for more than 20 years and has been known to perform extremely well in ecological predictions. However, while increasingly on the rise, its potential is still widely underused in conservation, (spatial) ecological applications and for inference. Our results show that it informs ecological and biogeographical theories as well as being suitable for conservation applications, specifically when the study area is undersampled. This method helps to save model-selection time and effort, and allows robust and rapid

Positive random variables with a discrete probability mass at the origin: Parameter estimation for left-censored samples with application to air quality monitoring data

International Nuclear Information System (INIS)

Gogolak, C.V.

1986-11-01

The concentration of a contaminant measured in a particular medium might be distributed as a positive random variable when it is present, but it may not always be present. If there is a level below which the concentration cannot be distinguished from zero by the analytical apparatus, a sample from such a population will be censored on the left. The presence of both zeros and positive values in the censored portion of such samples complicates the problem of estimating the parameters of the underlying positive random variable and the probability of a zero observation. Using the method of maximum likelihood, it is shown that the solution to this estimation problem reduces largely to that of estimating the parameters of the distribution truncated at the point of censorship. The maximum likelihood estimate of the proportion of zero values follows directly. The derivation of the maximum likelihood estimates for a lognormal population with zeros is given in detail, and the asymptotic properties of the estimates are examined. The estimation method was used to fit several different distributions to a set of severely censored 85 Kr monitoring data from six locations at the Savannah River Plant chemical separations facilities

A Comparison of the Number of Men Who Have Sex with Men among Rural-To-Urban Migrants with Non-Migrant Rural and Urban Residents in Wuhan, China: A GIS/GPS-Assisted Random Sample Survey Study

Science.gov (United States)

Chen, Xinguang; Yu, Bin; Zhou, Dunjin; Zhou, Wang; Gong, Jie; Li, Shiyue; Stanton, Bonita

2015-01-01

Background Mobile populations and men who have sex with men (MSM) play an increasing role in the current HIV epidemic in China and across the globe. While considerable research has addressed both of these at-risk populations, more effective HIV control requires accurate data on the number of MSM at the population level, particularly MSM among migrant populations. Methods Survey data from a random sample of male rural-to-urban migrants (aged 18-45, n=572) in Wuhan, China were analyzed and compared with those of randomly selected non-migrant urban (n=566) and rural counterparts (580). The GIS/GPS technologies were used for sampling and the survey estimation method was used for data analysis. Results HIV-related risk behaviors among rural-to-urban migrants were similar to those among the two comparison groups. The estimated proportion of MSM among migrants [95% CI] was 5.8% [4.7, 6.8], higher than 2.8% [1.2, 4.5] for rural residents and 1.0% [0.0, 2.4] for urban residents, respectively. Among these migrants, the MSM were more likely than non-MSM to be older in age, married, and migrated to more cities. They were also more likely to co-habit with others in rental properties located in new town and neighborhoods with fewer old acquaintances and more entertainment establishments. In addition, they were more likely to engage in commercial sex and less likely to consistently use condoms. Conclusion Findings of this study indicate that compared to rural and urban populations, the migrant population in Wuhan consists of a higher proportion of MSM who also exhibit higher levels of HIV-related risk behaviors. More effective interventions should target this population with a focus on neighborhood factors, social capital and collective efficacy for risk reduction. PMID:26241900

Benefits of expressive writing in reducing test anxiety: A randomized controlled trial in Chinese samples.

Science.gov (United States)

Shen, Lujun; Yang, Lei; Zhang, Jing; Zhang, Meng

2018-01-01

To explore the effect of expressive writing of positive emotions on test anxiety among senior-high-school students. The Test Anxiety Scale (TAS) was used to assess the anxiety level of 200 senior-high-school students. Seventy-five students with high anxiety were recruited and divided randomly into experimental and control groups. Each day for 30 days, the experimental group engaged in 20 minutes of expressive writing of positive emotions, while the control group was asked to merely write down their daily events. A second test was given after the month-long experiment to analyze whether there had been a reduction in anxiety among the sample. Quantitative data was obtained from TAS scores. The NVivo10.0 software program was used to examine the frequency of particular word categories used in participants' writing manuscripts. Senior-high-school students indicated moderate to high test anxiety. There was a significant difference in post-test results (P 0.05). Students' writing manuscripts were mainly encoded on five code categories: cause, anxiety manifestation, positive emotion, insight and evaluation. There was a negative relation between positive emotion, insight codes and test anxiety. There were significant differences in the positive emotion, anxiety manifestation, and insight code categories between the first 10 days' manuscripts and the last 10 days' ones. Long-term expressive writing of positive emotions appears to help reduce test anxiety by using insight and positive emotion words for Chinese students. Efficient and effective intervention programs to ease test anxiety can be designed based on this study.

Benefits of expressive writing in reducing test anxiety: A randomized controlled trial in Chinese samples.

Directory of Open Access Journals (Sweden)

Lujun Shen

Full Text Available To explore the effect of expressive writing of positive emotions on test anxiety among senior-high-school students.The Test Anxiety Scale (TAS was used to assess the anxiety level of 200 senior-high-school students. Seventy-five students with high anxiety were recruited and divided randomly into experimental and control groups. Each day for 30 days, the experimental group engaged in 20 minutes of expressive writing of positive emotions, while the control group was asked to merely write down their daily events. A second test was given after the month-long experiment to analyze whether there had been a reduction in anxiety among the sample. Quantitative data was obtained from TAS scores. The NVivo10.0 software program was used to examine the frequency of particular word categories used in participants' writing manuscripts.Senior-high-school students indicated moderate to high test anxiety. There was a significant difference in post-test results (P 0.05. Students' writing manuscripts were mainly encoded on five code categories: cause, anxiety manifestation, positive emotion, insight and evaluation. There was a negative relation between positive emotion, insight codes and test anxiety. There were significant differences in the positive emotion, anxiety manifestation, and insight code categories between the first 10 days' manuscripts and the last 10 days' ones.Long-term expressive writing of positive emotions appears to help reduce test anxiety by using insight and positive emotion words for Chinese students. Efficient and effective intervention programs to ease test anxiety can be designed based on this study.

Benefits of expressive writing in reducing test anxiety: A randomized controlled trial in Chinese samples

Science.gov (United States)

Zhang, Jing; Zhang, Meng

2018-01-01

Purpose To explore the effect of expressive writing of positive emotions on test anxiety among senior-high-school students. Methods The Test Anxiety Scale (TAS) was used to assess the anxiety level of 200 senior-high-school students. Seventy-five students with high anxiety were recruited and divided randomly into experimental and control groups. Each day for 30 days, the experimental group engaged in 20 minutes of expressive writing of positive emotions, while the control group was asked to merely write down their daily events. A second test was given after the month-long experiment to analyze whether there had been a reduction in anxiety among the sample. Quantitative data was obtained from TAS scores. The NVivo10.0 software program was used to examine the frequency of particular word categories used in participants’ writing manuscripts. Results Senior-high-school students indicated moderate to high test anxiety. There was a significant difference in post-test results (P 0.05). Students’ writing manuscripts were mainly encoded on five code categories: cause, anxiety manifestation, positive emotion, insight and evaluation. There was a negative relation between positive emotion, insight codes and test anxiety. There were significant differences in the positive emotion, anxiety manifestation, and insight code categories between the first 10 days’ manuscripts and the last 10 days’ ones. Conclusions Long-term expressive writing of positive emotions appears to help reduce test anxiety by using insight and positive emotion words for Chinese students. Efficient and effective intervention programs to ease test anxiety can be designed based on this study. PMID:29401473

Sampling for stereology in lungs

Directory of Open Access Journals (Sweden)

J. R. Nyengaard

2006-12-01

Full Text Available The present article reviews the relevant stereological estimators for obtaining reliable quantitative structural data from the lungs. Stereological sampling achieves reliable, quantitative information either about the whole lung or complete lobes, whilst minimising the workload. Studies have used systematic random sampling, which has fixed and constant sampling probabilities on all blocks, sections and fields of view. For an estimation of total lung or lobe volume, the Cavalieri principle can be used, but it is not useful in estimating individual cell volume due to various effects from over- or underprojection. If the number of certain structures is required, two methods can be used: the disector and the fractionator. The disector method is a three-dimensional stereological probe for sampling objects according to their number. However, it may be affected on tissue deformation and, therefore, the fractionator method is often the preferred sampling principle. In this method, a known and predetermined fraction of an object is sampled in one or more steps, with the final step estimating the number. Both methods can be performed in a physical and optical manner, therefore enabling cells and larger lung structure numbers (e.g. number of alveoli to be estimated. Some estimators also require randomisation of orientation, so that all directions have an equal chance of being chosen. Using such isotropic sections, surface area, length, and diameter can be estimated on a Cavalieri set of sections. Stereology can also illustrate the potential for transport between two compartments by analysing the barrier width. Estimating the individual volume of cells can be achieved by local stereology using a two-step procedure that first samples lung cells using the disector and then introduces individual volume estimation of the sampled cells. The coefficient of error of most unbiased stereological estimators is a combination of variance from blocks, sections, fields

Systematic lymphadenectomy versus sampling of ipsilateral mediastinal lymph-nodes during lobectomy for non-small-cell lung cancer: a systematic review of randomized trials and a meta-analysis.

Science.gov (United States)

Mokhles, Sahar; Macbeth, Fergus; Treasure, Tom; Younes, Riad N; Rintoul, Robert C; Fiorentino, Francesca; Bogers, Ad J J C; Takkenberg, Johanna J M

2017-06-01

To re-examine the evidence for recommendations for complete dissection versus sampling of ipsilateral mediastinal lymph nodes during lobectomy for cancer. We searched for randomized trials of systematic mediastinal lymphadenectomy versus mediastinal sampling. We performed a textual analysis of the authors' own starting assumptions and conclusion. We analysed the trial designs and risk of bias. We extracted data on early mortality, perioperative complications, overall survival, local recurrence and distant recurrence for meta-analysis. We found five randomized controlled trials recruiting 1980 patients spanning 1989-2007. The expressed starting position in 3/5 studies was a conviction that systematic dissection was effective. Long-term survival was better with lymphadenectomy compared with sampling (Hazard Ratio 0.78; 95% CI 0.69-0.89) as was perioperative survival (Odds Ratio 0.59; 95% CI 0.25-1.36, non-significant). But there was an overall high risk of bias and a lack of intention to treat analysis. There were higher rates (non-significant) of perioperative complications including bleeding, chylothorax and recurrent nerve palsy with lymphadenectomy. The high risk of bias in these trials makes the overall conclusion insecure. The finding of clinically important surgically related morbidities but lower perioperative mortality with lymphadenectomy seems inconsistent. The multiple variables in patients, cancers and available treatments suggest that large pragmatic multicentre trials, testing currently available strategies, are the best way to find out which are more effective. The number of patients affected with lung cancer makes trials feasible. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Optimizing sampling approaches along ecological gradients

DEFF Research Database (Denmark)

Schweiger, Andreas; Irl, Severin D. H.; Steinbauer, Manuel

2016-01-01

1. Natural scientists and especially ecologists use manipulative experiments or field observations along gradients to differentiate patterns driven by processes from those caused by random noise. A well-conceived sampling design is essential for identifying, analysing and reporting underlying...... patterns in a statistically solid and reproducible manner, given the normal restrictions in labour, time and money. However, a technical guideline about an adequate sampling design to maximize prediction success under restricted resources is lacking. This study aims at developing such a solid...... and reproducible guideline for sampling along gradients in all fields of ecology and science in general. 2. We conducted simulations with artificial data for five common response types known in ecology, each represented by a simple function (no response, linear, exponential, symmetric unimodal and asymmetric...

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much.

Science.gov (United States)

He, Bryan; De Sa, Christopher; Mitliagkas, Ioannis; Ré, Christopher

2016-01-01

Gibbs sampling is a Markov Chain Monte Carlo sampling technique that iteratively samples variables from their conditional distributions. There are two common scan orders for the variables: random scan and systematic scan. Due to the benefits of locality in hardware, systematic scan is commonly used, even though most statistical guarantees are only for random scan. While it has been conjectured that the mixing times of random scan and systematic scan do not differ by more than a logarithmic factor, we show by counterexample that this is not the case, and we prove that that the mixing times do not differ by more than a polynomial factor under mild conditions. To prove these relative bounds, we introduce a method of augmenting the state space to study systematic scan using conductance.

Randomization Does Not Help Much, Comparability Does

Science.gov (United States)

Saint-Mont, Uwe

2015-01-01

According to R.A. Fisher, randomization “relieves the experimenter from the anxiety of considering innumerable causes by which the data may be disturbed.” Since, in particular, it is said to control for known and unknown nuisance factors that may considerably challenge the validity of a result, it has become very popular. This contribution challenges the received view. First, looking for quantitative support, we study a number of straightforward, mathematically simple models. They all demonstrate that the optimism surrounding randomization is questionable: In small to medium-sized samples, random allocation of units to treatments typically yields a considerable imbalance between the groups, i.e., confounding due to randomization is the rule rather than the exception. In the second part of this contribution, the reasoning is extended to a number of traditional arguments in favour of randomization. This discussion is rather non-technical, and sometimes touches on the rather fundamental Frequentist/Bayesian debate. However, the result of this analysis turns out to be quite similar: While the contribution of randomization remains doubtful, comparability contributes much to a compelling conclusion. Summing up, classical experimentation based on sound background theory and the systematic construction of exchangeable groups seems to be advisable. PMID:26193621

Chorionic villus sampling and amniocentesis.

Science.gov (United States)

Brambati, Bruno; Tului, Lucia

2005-04-01

The advantages and disadvantages of common invasive methods for prenatal diagnosis are presented in light of new investigations. Several aspects of first-trimester chorionic villus sampling and mid-trimester amniocentesis remain controversial, especially fetal loss rate, feto-maternal complications, and the extension of both sampling methods to less traditional gestational ages (early amniocentesis, late chorionic villus sampling), all of which complicate genetic counseling. A recent randomized trial involving early amniocentesis and late chorionic villus sampling has confirmed previous studies, leading to the unquestionable conclusion that transabdominal chorionic villus sampling is safer. The old dispute over whether limb reduction defects are caused by chorionic villus sampling gains new vigor, with a paper suggesting that this technique has distinctive teratogenic effects. The large experience involving maternal and fetal complications following mid-trimester amniocentesis allows a better estimate of risk for comparison with chorionic villus sampling. Transabdominal chorionic villus sampling, which appears to be the gold standard sampling method for genetic investigations between 10 and 15 completed weeks, permits rapid diagnosis in high-risk cases detected by first-trimester screening of aneuploidies. Sampling efficiency and karyotyping reliability are as high as in mid-trimester amniocentesis with fewer complications, provided the operator has the required training, skill and experience.

Employing a Multi-level Approach to Recruit a Representative Sample of Women with Recent Gestational Diabetes Mellitus into a Randomized Lifestyle Intervention Trial.

Science.gov (United States)

Nicklas, Jacinda M; Skurnik, Geraldine; Zera, Chloe A; Reforma, Liberty G; Levkoff, Sue E; Seely, Ellen W

2016-02-01

The postpartum period is a window of opportunity for diabetes prevention in women with recent gestational diabetes (GDM), but recruitment for clinical trials during this period of life is a major challenge. We adapted a social-ecologic model to develop a multi-level recruitment strategy at the macro (high or institutional level), meso (mid or provider level), and micro (individual) levels. Our goal was to recruit 100 women with recent GDM into the Balance after Baby randomized controlled trial over a 17-month period. Participants were asked to attend three in-person study visits at 6 weeks, 6, and 12 months postpartum. They were randomized into a control arm or a web-based intervention arm at the end of the baseline visit at six weeks postpartum. At the end of the recruitment period, we compared population characteristics of our enrolled subjects to the entire population of women with GDM delivering at Brigham and Women's Hospital (BWH). We successfully recruited 107 of 156 (69 %) women assessed for eligibility, with the majority (92) recruited during pregnancy at a mean 30 (SD ± 5) weeks of gestation, and 15 recruited postpartum, at a mean 2 (SD ± 3) weeks postpartum. 78 subjects attended the initial baseline visit, and 75 subjects were randomized into the trial at a mean 7 (SD ± 2) weeks postpartum. The recruited subjects were similar in age and race/ethnicity to the total population of 538 GDM deliveries at BWH over the 17-month recruitment period. Our multilevel approach allowed us to successfully meet our recruitment goal and recruit a representative sample of women with recent GDM. We believe that our most successful strategies included using a dedicated in-person recruiter, integrating recruitment into clinical flow, allowing for flexibility in recruitment, minimizing barriers to participation, and using an opt-out strategy with providers. Although the majority of women were recruited while pregnant, women recruited in the early postpartum period were

Estimating the encounter rate variance in distance sampling

Science.gov (United States)

Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

2009-01-01

The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

A mindfulness-based stress prevention training for medical students (MediMind): study protocol for a randomized controlled trial.

Science.gov (United States)

Kuhlmann, Sophie Merle; Bürger, Arne; Esser, Günter; Hammerle, Florian

2015-02-08

Medical training is very demanding and associated with a high prevalence of psychological distress. Compared to the general population, medical students are at a greater risk of developing a psychological disorder. Various attempts of stress management training in medical school have achieved positive results on minimizing psychological distress; however, there are often limitations. Therefore, the use of a rigorous scientific method is needed. The present study protocol describes a randomized controlled trial to examine the effectiveness of a specifically developed mindfulness-based stress prevention training for medical students that includes selected elements of cognitive behavioral strategies (MediMind). This study protocol presents a prospective randomized controlled trial, involving four assessment time points: baseline, post-intervention, one-year follow-up and five-year follow-up. The aims include evaluating the effect on stress, coping, psychological morbidity and personality traits with validated measures. Participants are allocated randomly to one of three conditions: MediMind, Autogenic Training or control group. Eligible participants are medical or dental students in the second or eighth semester of a German university. They form a population of approximately 420 students in each academic term. A final total sample size of 126 (at five-year follow-up) is targeted. The trainings (MediMind and Autogenic Training) comprise five weekly sessions lasting 90 minutes each. MediMind will be offered to participants of the control group once the five-year follow-up is completed. The allotment is randomized with a stratified allocation ratio by course of studies, semester, and gender. After descriptive statistics have been evaluated, inferential statistical analysis will be carried out with a repeated measures ANOVA-design with interactions between time and group. Effect sizes will be calculated using partial η-square values. Potential limitations of this study

Systematic screening with information and home sampling for genital Chlamydia trachomatis infections in young men and women in Norway: a randomized controlled trial.

Science.gov (United States)

Kløvstad, Hilde; Natås, Olav; Tverdal, Aage; Aavitsland, Preben

2013-01-23

As most genital Chlamydia trachomatis infections are asymptomatic, many patients do not seek health care for testing. Infections remain undiagnosed and untreated. We studied whether screening with information and home sampling resulted in more young people getting tested, diagnosed and treated for chlamydia in the three months following the intervention compared to the current strategy of testing in the health care system. We conducted a population based randomized controlled trial among all persons aged 18-25 years in one Norwegian county (41 519 persons). 10 000 persons (intervention) received an invitation by mail with chlamydia information and a mail-back urine sampling kit. 31 519 persons received no intervention and continued with usual care (control). All samples from both groups were analysed in the same laboratory. Information on treatment was obtained from the Norwegian Prescription Database (NorPD). We estimated risk ratios and risk differences of being tested, diagnosed and treated in the intervention group compared to the control group. In the intervention group 16.5% got tested and in the control group 3.4%, risk ratio 4.9 (95% CI 4.5-5.2). The intervention led to 2.6 (95% CI 2.0-3.4) times as many individuals being diagnosed and 2.5 (95% CI 1.9-3.4) times as many individuals receiving treatment for chlamydia compared to no intervention in the three months following the intervention. In Norway, systematic screening with information and home sampling results in more young people being tested, diagnosed and treated for chlamydia in the three months following the intervention than the current strategy of testing in the health care system. However, the study has not established that the intervention will reduce the chlamydia prevalence or the risk of complications from chlamydia.

Sample size calculations for case-control studies

Science.gov (United States)

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

The concentration of heavy metals: zinc, cadmium, lead, copper, mercury, iron and calcium in head hair of a randomly selected sample of Kenyan people

International Nuclear Information System (INIS)

Wandiga, S.O.; Jumba, I.O.

1982-01-01

An intercomparative analysis of the concentration of heavy metals:zinc, cadmium, lead, copper, mercury, iron and calcium in head hair of a randomly selected sample of Kenyan people using the techniques of atomic absorption spectrophotometry (AAS) and differential pulse anodic stripping voltammetry (DPAS) has been undertaken. The percent relative standard deviation for each sample analysed using either of the techniques show good sensitivity and correlation between the techniques. The DPAS was found to be slightly sensitive than the AAs instrument used. The recalculated body burden rations of Cd to Zn, Pb to Fe reveal no unusual health impairement symptoms and suggest a relatively clean environment in Kenya.(author)

PERSONAL NETWORK SAMPLING, OUTDEGREE ANALYSIS AND MULTILEVEL ANALYSIS - INTRODUCING THE NETWORK CONCEPT IN STUDIES OF HIDDEN POPULATIONS

NARCIS (Netherlands)

SPREEN, M; ZWAAGSTRA, R

1994-01-01

Populations, such as heroin and cocaine users, the homeless and the like (hidden populations), are among the most difficult populations to which to apply classic random sampling procedures. A frequently used data collection method for these hidden populations is the snowball procedure. The

GRD: An SPSS extension command for generating random data

Directory of Open Access Journals (Sweden)

Bradley Harding

2014-09-01

Full Text Available To master statistics and data analysis tools, it is necessary to understand a number of concepts, manyof which are quite abstract. For example, sampling from a theoretical distribution can help individuals explore andunderstand randomness. Sampling can also be used to build exercises aimed to help students master statistics. Here, we present GRD (Generator of Random Data, an extension command for SPSS (version 17 and above. With GRD, it is possible to get random data from a given distribution. In its simplest use, GRD will return a set of simulated data from a normal distribution.With subcommands to GRD, it is possible to get data from multiple groups, over multiple repeated measures, and with desired effectsizes. Group sizes can be equal or unequal. With further subcommands, it is possible to sample from any theoretical population, (not simply the normal distribution, introduce non-homogeneous variances,fix or randomize subject effects, etc. Finally, GRD’s generated data are in a format ready to be analyzed.

Study protocol: a randomized controlled trial investigating the effects of a psychosexual training program for adolescents with autism spectrum disorder.

Science.gov (United States)

Visser, Kirsten; Greaves-Lord, Kirstin; Tick, Nouchka T; Verhulst, Frank C; Maras, Athanasios; van der Vegt, Esther J M

2015-08-28

Previous research shows that adolescents with autism spectrum disorder (ASD) run several risks in their psychosexual development and that these adolescents can have limited access to reliable information on puberty and sexuality, emphasizing the need for specific guidance of adolescents with ASD in their psychosexual development. Few studies have investigated the effects of psychosexual training programs for adolescents with ASD and to date no randomized controlled trials are available to study the effects of psychosexual interventions for this target group. The randomized controlled trial (RCT) described in this study protocol aims to investigate the effects of the Tackling Teenage Training (TTT) program on the psychosexual development of adolescents with ASD. This parallel clinical trial, conducted in the South-West of the Netherlands, has a simple equal randomization design with an intervention and a waiting-list control condition. Two hundred adolescents and their parents participate in this study. We assess the participants in both conditions using self-report as well as parent-report questionnaires at three time points during 1 year: at baseline (T1), post-treatment (T2), and for follow-up (T3). To our knowledge, the current study is the first that uses a randomized controlled design to study the effects of a psychosexual training program for adolescents with ASD. It has a number of methodological strengths, namely a large sample size, a wide range of functionally relevant outcome measures, the use of multiple informants, and a standardized research and intervention protocol. Also some limitations of the described study are identified, for instance not making a comparison between two treatment conditions, and no use of blinded observational measures to investigate the ecological validity of the research results. Dutch Trial Register NTR2860. Registered on 20 April 2011.

Safety and feasibility of transcranial direct current stimulation in pediatric hemiparesis: randomized controlled preliminary study.

Science.gov (United States)

Gillick, Bernadette T; Feyma, Tim; Menk, Jeremiah; Usset, Michelle; Vaith, Amy; Wood, Teddi Jean; Worthington, Rebecca; Krach, Linda E

2015-03-01

Transcranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation that has shown improved adult stroke outcomes. Applying tDCS in children with congenital hemiparesis has not yet been explored. The primary objective of this study was to explore the safety and feasibility of single-session tDCS through an adverse events profile and symptom assessment within a double-blind, randomized placebo-controlled preliminary study in children with congenital hemiparesis. A secondary objective was to assess the stability of hand and cognitive function. A double-blind, randomized placebo-controlled pretest/posttest/follow-up study was conducted. The study was conducted in a university pediatric research laboratory. Thirteen children, ages 7 to 18 years, with congenital hemiparesis participated. Adverse events/safety assessment and hand function were measured. Participants were randomly assigned to either an intervention group or a control group, with safety and functional assessments at pretest, at posttest on the same day, and at a 1-week follow-up session. An intervention of 10 minutes of 0.7 mA tDCS was applied to bilateral primary motor cortices. The tDCS intervention was considered safe if there was no individual decline of 25% or group decline of 2 standard deviations for motor evoked potentials (MEPs) and behavioral data and no report of adverse events. No major adverse events were found, including no seizures. Two participants did not complete the study due to lack of MEP and discomfort. For the 11 participants who completed the study, group differences in MEPs and behavioral data did not exceed 2 standard deviations in those who received the tDCS (n=5) and those in the control group (n=6). The study was completed without the need for stopping per medical monitor and biostatisticial analysis. A limitation of the study was the small sample size, with data available for 11 participants. Based on the results of this study, tDCS appears to be safe

Validation of a new HPV self-sampling device for cervical cancer screening: The Cervical and Self-Sample In Screening (CASSIS) study.

Science.gov (United States)

El-Zein, Mariam; Bouten, Sheila; Louvanto, Karolina; Gilbert, Lucy; Gotlieb, Walter; Hemmings, Robert; Behr, Marcel A; Franco, Eduardo L; Liang, Victoria; Martins, Claudia; Duarte, Silvy; Sarban, Natalia; Geddes, Patricia; Massa, Ana; Samios, Kathrin; Aboufadl, Siham; Verdon, Sophie; Pereria, Cynthia; Lacroix, Isabelle

2018-04-17

We compared the self-sampling performance of the newly designed HerSwab™ device with a physician-collected cervical sample and another self-sample using the cobas® PCR Female swab for the detection of cervical intraepithelial neoplasia (CIN) and cancer. Women referred for colposcopy at McGill University affiliated hospital clinics collected two consecutive self-samples, one with HerSwab™ and one with cobas® swab, after receiving instructions. The order of sampling was randomized. The colposcopist then collected a cervical sample and conducted a colposcopic examination. Samples were tested for human papillomavirus (HPV) DNA. Sensitivity and specificity to detect CIN2+ and respective 95% confidence intervals (CI) were calculated to compare sampling approaches. The HPV testing agreement between samples was measured using the Kappa statistic. Of 1217 women enrolled, 1076 had complete results for HPV and cytology; 148 (13.8%) had CIN1, 147 (13.7%) had CIN2/3, and 5 (0.5%) had cancer. There was very good agreement between methods for HPV detection (HerSwab™ versus physician: kappa=0.84; cobas® swabs versus physician: kappa=0.81; HerSwab™ versus cobas® swabs: kappa=0.87). The sensitivity of HPV detection for CIN2+ was 87.6% (95%CI: 79.8-93.2) with self-sampling using HerSwab™, 88.6% (95%CI: 80.9-94.0) with self-sampling using the cobas® swab, and 92.4% (95%CI: 85.5-96.7) with physician sampling. Corresponding estimates of specificity were 58.1% (95%CI: 54.1-62.1), 55.0% (95%CI: 50.9-59.0) and 58.7% (95%CI: 54.6-62.6). Cytology (ASC-US or more severe) done on the physician-collected specimen was 80.2% (95%CI: 70.8-87.6) sensitive and 61.4% (95%CI: 57.2-65.5) specific for CIN2+. The HerSwab™ had good agreement with physician sampling in detecting HPV, and adequate performance in detecting high-grade lesions among women referred to colposcopy for abnormal cytology. Copyright © 2018 Elsevier Inc. All rights reserved.

Modeling of Residential Water Demand Using Random Effect Model,Case Study: Arak City

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Seyed Hossein Sajadifar

2011-10-01

Full Text Available The present study tries to apply the “Partial Adjustment Model” and “Random Effect Model” techniques to the Stone-Greay’s linear expenditure system, in order to estimate the "Residential Seasonal Demand" for water in Arak city. Per capita water consumption of family residences is regressed on marginal price, per capita income, price of other goods, average temperature and average rainfall. Panel data approaches based on a sample of 152 observations from Arak city referred to 1993-2003. From the estimation of the Elasticity-price of the residential water demand, we want to know how a policy of responsive pricing can lead to more efficient household water consumption inArakcity. Results also indicated that summer price elasticity was twice the winter and price and income elasticity was less than 1 in all cases.

Thromboembolism and mechanical heart valves : A randomized study revisited

NARCIS (Netherlands)

Kuntze, CEE; Blackstone, EH; Ebels, T

Background. This study was designed to revise and substantiate previous inferences, based on short-term follow-up, about differences in the incidence of anticoagulant-related events after heart valve replacement among patients who had been randomly assigned to receive either a Bjork-Shiley,

Equilibrium Molecular Thermodynamics from Kirkwood Sampling

OpenAIRE

Somani, Sandeep; Okamoto, Yuko; Ballard, Andrew J.; Wales, David J.

2015-01-01

We present two methods for barrierless equilibrium sampling of molecular systems based on the recently proposed Kirkwood method (J. Chem. Phys. 2009, 130, 134102). Kirkwood sampling employs low-order correlations among internal coordinates of a molecule for random (or non-Markovian) sampling of the high dimensional conformational space. This is a geometrical sampling method independent of the potential energy surface. The first method is a variant of biased Monte Carlo, wher...

Mars Sample Return Architecture Assessment Study

Science.gov (United States)

Centuori, S.; Hermosín, P.; Martín, J.; De Zaiacomo, G.; Colin, S.; Godfrey, A.; Myles, J.; Johnson, H.; Sachdev, T.; Ahmed, R.

2018-04-01

Current paper presents the results of ESA funded activity "Mars Sample Return Architecture Assessment Study" carried-out by DEIMOS Space, Lockheed Martin UK Ampthill, and MDA Corporation, where more than 500 mission design options have been studied.

On-Demand Treatment of Premature Ejaculation with Citalopram: A Randomized Double-Blind Study

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Ghafuri Zahra

2009-10-01

Full Text Available "nAs the most common male sexual disorder premature ejaculation (PE, also referred to as early ejaculation (EE or rapid ejaculation (RE, affects 30%-40% of sexually active men. Despite the limited number of available studies comparing the efficacy of selective serotonin re-uptake inhibitors (SSRI they have been thought to have beneficial effects for the treatment of patients with PE. In the present study, we assessed the efficacy of on-demand use of citalopram, in the treatment of premature ejaculation. A randomized double blind study of fixed dose on-demand use of citalopram was performed in Roozbeh Psychiatry Hospital, Tehran University of Medical Sciences. The sample was consisted of 80 married patients diagnosed with PE according to Diagnostic and Statistical Manual of Mental Disorders. The patients were randomly assigned to two groups: group 1 consisting of 42 patients received 20mg citalopram, and group 2 consisting of 38 patients received placebo four hours before intercourse for a 4-week treatment course. The effects of drug on the ejaculatory function in each group were assessed by the intravaginal ejaculation latency time (IELT, and the Chinese Index of Premature Ejaculation (CIPE before and at the end of treatment course. The mean IELT increased from 66.78±36.94 to 80.85±43.05 seconds in group 1 and from 63.44±33.16 to 65.71±34.26 seconds in group 2 (P = 0.000. Mean CIPE score increased 1.14±1.04 and 0.52±0.50 in group 1 and 2 respectively (P = 0.002. The patients treated with on demand citalopram showed significantly greater improvement in IELT and CIPE score compared to the patients receiving placebo. It seems that citalopram may be an effective treatment of premature ejaculation with on-demand usage. However further studies are warranted.

The generalization ability of online SVM classification based on Markov sampling.

Science.gov (United States)

Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

2015-03-01

In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

Prediction of soil CO2 flux in sugarcane management systems using the Random Forest approach

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Rose Luiza Moraes Tavares

Full Text Available ABSTRACT: The Random Forest algorithm is a data mining technique used for classifying attributes in order of importance to explain the variation in an attribute-target, as soil CO2 flux. This study aimed to identify prediction of soil CO2 flux variables in management systems of sugarcane through the machine-learning algorithm called Random Forest. Two different management areas of sugarcane in the state of São Paulo, Brazil, were selected: burned and green. In each area, we assembled a sampling grid with 81 georeferenced points to assess soil CO2 flux through automated portable soil gas chamber with measuring spectroscopy in the infrared during the dry season of 2011 and the rainy season of 2012. In addition, we sampled the soil to evaluate physical, chemical, and microbiological attributes. For data interpretation, we used the Random Forest algorithm, based on the combination of predicted decision trees (machine learning algorithms in which every tree depends on the values of a random vector sampled independently with the same distribution to all the trees of the forest. The results indicated that clay content in the soil was the most important attribute to explain the CO2 flux in the areas studied during the evaluated period. The use of the Random Forest algorithm originated a model with a good fit (R2 = 0.80 for predicted and observed values.

Prednisolone and acupuncture in Bell's palsy: study protocol for a randomized, controlled trial

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Wang Kangjun

2011-06-01

Full Text Available Abstract Background There are a variety of treatment options for Bell's palsy. Evidence from randomized controlled trials indicates corticosteroids can be used as a proven therapy for Bell's palsy. Acupuncture is one of the most commonly used methods to treat Bell's palsy in China. Recent studies suggest that staging treatment is more suitable for Bell's palsy, according to different path-stages of this disease. The aim of this study is to compare the effects of prednisolone and staging acupuncture in the recovery of the affected facial nerve, and to verify whether prednisolone in combination with staging acupuncture is more effective than prednisolone alone for Bell's palsy in a large number of patients. Methods/Design In this article, we report the design and protocol of a large sample multi-center randomized controlled trial to treat Bell's palsy with prednisolone and/or acupuncture. In total, 1200 patients aged 18 to 75 years within 72 h of onset of acute, unilateral, peripheral facial palsy will be assessed. There are six treatment groups, with four treated according to different path-stages and two not. These patients are randomly assigned to be in one of the following six treatment groups, i.e. 1 placebo prednisolone group, 2 prednisolone group, 3 placebo prednisolone plus acute stage acupuncture group, 4 prednisolone plus acute stage acupuncture group, 5 placebo prednisolone plus resting stage acupuncture group, 6 prednisolone plus resting stage acupuncture group. The primary outcome is the time to complete recovery of facial function, assessed by Sunnybrook system and House-Brackmann scale. The secondary outcomes include the incidence of ipsilateral pain in the early stage of palsy (and the duration of this pain, the proportion of patients with severe pain, the occurrence of synkinesis, facial spasm or contracture, and the severity of residual facial symptoms during the study period. Discussion The result of this trial will assess the

Novel approach to systematic random sampling in population surveys: Lessons from the United Arab Emirates National Diabetes Study (UAEDIAB).

Science.gov (United States)

Sulaiman, Nabil; Albadawi, Salah; Abusnana, Salah; Fikri, Mahmoud; Madani, Abdulrazzag; Mairghani, Maisoon; Alawadi, Fatheya; Zimmet, Paul; Shaw, Jonathan

2015-09-01

The prevalence of diabetes has risen rapidly in the Middle East, particularly in the Gulf Region. However, some prevalence estimates have not fully accounted for large migrant worker populations and have focused on minority indigenous populations. The objectives of the UAE National Diabetes and Lifestyle Study are to: (i) define the prevalence of, and risk factors for, T2DM; (ii) describe the distribution and determinants of T2DM risk factors; (iii) study health knowledge, attitudes, and (iv) identify gene-environment interactions; and (v) develop baseline data for evaluation of future intervention programs. Given the high burden of diabetes in the region and the absence of accurate data on non-UAE nationals in the UAE, a representative sample of the non-UAE nationals was essential. We used an innovative methodology in which non-UAE nationals were sampled when attending the mandatory biannual health check that is required for visa renewal. Such an approach could also be used in other countries in the region. Complete data were available for 2719 eligible non-UAE nationals (25.9% Arabs, 70.7% Asian non-Arabs, 1.1% African non-Arabs, and 2.3% Westerners). Most were men < 65 years of age. The response rate was 68%, and the non-response was greater among women than men; 26.9% earned less than UAE Dirham (AED) 24 000 (US$6500) and the most common areas of employment were as managers or professionals, in service and sales, and unskilled occupations. Most (37.4%) had completed high school and 4.1% had a postgraduate degree. This novel methodology could provide insights for epidemiological studies in the UAE and other Gulf States, particularly for expatriates. © 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Selection of representative calibration sample sets for near-infrared reflectance spectroscopy to predict nitrogen concentration in grasses

DEFF Research Database (Denmark)

Shetty, Nisha; Rinnan, Åsmund; Gislum, René

2012-01-01

) algorithm were used and compared. Both Puchwein and CADEX methods provide a calibration set equally distributed in space, and both methods require a minimum prior of knowledge. The samples were also selected randomly using complete random, cultivar random (year fixed), year random (cultivar fixed......) and interaction (cultivar × year fixed) random procedures to see the influence of different factors on sample selection. Puchwein's method performed best with lowest RMSEP followed by CADEX, interaction random, year random, cultivar random and complete random. Out of 118 samples of the complete calibration set...... effectively enhance the cost-effectiveness of NIR spectral analysis by reducing the number of analyzed samples in the calibration set by more than 80%, which substantially reduces the effort of laboratory analyses with no significant loss in prediction accuracy....

Sampling Strategies for Evaluating the Rate of Adventitious Transgene Presence in Non-Genetically Modified Crop Fields.

Science.gov (United States)

Makowski, David; Bancal, Rémi; Bensadoun, Arnaud; Monod, Hervé; Messéan, Antoine

2017-09-01

According to E.U. regulations, the maximum allowable rate of adventitious transgene presence in non-genetically modified (GM) crops is 0.9%. We compared four sampling methods for the detection of transgenic material in agricultural non-GM maize fields: random sampling, stratified sampling, random sampling + ratio reweighting, random sampling + regression reweighting. Random sampling involves simply sampling maize grains from different locations selected at random from the field concerned. The stratified and reweighting sampling methods make use of an auxiliary variable corresponding to the output of a gene-flow model (a zero-inflated Poisson model) simulating cross-pollination as a function of wind speed, wind direction, and distance to the closest GM maize field. With the stratified sampling method, an auxiliary variable is used to define several strata with contrasting transgene presence rates, and grains are then sampled at random from each stratum. With the two methods involving reweighting, grains are first sampled at random from various locations within the field, and the observations are then reweighted according to the auxiliary variable. Data collected from three maize fields were used to compare the four sampling methods, and the results were used to determine the extent to which transgene presence rate estimation was improved by the use of stratified and reweighting sampling methods. We found that transgene rate estimates were more accurate and that substantially smaller samples could be used with sampling strategies based on an auxiliary variable derived from a gene-flow model. © 2017 Society for Risk Analysis.

Study of C-MYC amplification and expression in Iranian gastric cancer samples using CISH and IHC methods.

Science.gov (United States)

Khaleghian, Malihea; Jahanzad, Issa; Shakoori, Abbas; Ardalan, Farid Azmoudeh; Azimi, Cyrus

2015-01-01

Gastric cancer is the fourth most frequent malignancy and the second cause of cancer-related mortality worldwide. It has been suggested that in gastric carcinogenesis, the C-MYC gene has an important function. The objective of this study is to establish the preference of Chromogenic in situ hybridization (CISH) and Immunohistochemistry (IHC) in the diagnosis and prognosis of gastric cancer. Samples comprised of 50 randomly selected patients of whom 40 were male and 10 female. To evaluate the MYC copy number and its protein expression, CISH and IHC analyses were performed for 50 gastric adenocarcinomas, in Iran. The location of the tumor in 64% of the patients was the fundus, and in 72% of patients, the tumors were of a diffuse type; 22 samples showed no amplification, and 28 samples were with amplification. MYC immunoreactivity was observed in 13 samples. Twelve samples showed both MYC amplification and MYC immunoreactivity. In addition, among the 28 CISH+ samples, 12 samples had positive signals for IHC and 16 samples had negative signals for IHC. A majority of the IHC-negative patients had no amplification, but only one patient with IHC positive had no amplification. Our conclusion was that for the management and treatment of gastric cancer, and for special attention of clinicians, for prognosis and tumor progression, the CISH was a better and more feasible test than IHC, in regard to the sensitivity and specificity.

Study of C-MYC amplification and expression in Iranian gastric cancer samples using CISH and IHC methods

Directory of Open Access Journals (Sweden)

Malihea Khaleghian

2015-01-01

Full Text Available Background: Gastric cancer is the fourth most frequent malignancy and the second cause of cancer-related mortality worldwide. It has been suggested that in gastric carcinogenesis, the C-MYC gene has an important function. The objective of this study is to establish the preference of Chromogenic in situ hybridization (CISH and Immunohistochemistry (IHC in the diagnosis and prognosis of gastric cancer. Materials and Methods: Samples comprised of 50 randomly selected patients of whom 40 were male and 10 female. To evaluate the MYC copy number and its protein expression, CISH and IHC analyses were performed for 50 gastric adenocarcinomas, in Iran. Results: The location of the tumor in 64% of the patients was the fundus, and in 72% of patients, the tumors were of a diffuse type; 22 samples showed no amplification, and 28 samples were with amplification. MYC immunoreactivity was observed in 13 samples. Twelve samples showed both MYC amplification and MYC immunoreactivity. In addition, among the 28 CISH+ samples, 12 samples had positive signals for IHC and 16 samples had negative signals for IHC. A majority of the IHC-negative patients had no amplification, but only one patient with IHC positive had no amplification. Conclusion: Our conclusion was that for the management and treatment of gastric cancer, and for special attention of clinicians, for prognosis and tumor progression, the CISH was a better and more feasible test than IHC, in regard to the sensitivity and specificity.

A randomized crossover clinical study showing that methylphenidate-SODAS improves attention-deficit/hyperactivity disorder symptoms in adolescents with substance use disorder

Directory of Open Access Journals (Sweden)

C.M. Szobot

2008-03-01

Full Text Available Our objective was to evaluate the effectiveness of a long-acting formulation of methylphenidate (MPH-SODAS on attention-deficit/hyperactivity disorder (ADHD symptoms in an outpatient sample of adolescents with ADHD and substance use disorders (SUD. Secondary goals were to evaluate the tolerability and impact on drug use of MPH-SODAS. This was a 6-week, single-blind, placebo-controlled crossover study assessing efficacy of escalated doses of MPH-SODAS on ADHD symptoms in 16 adolescents with ADHD/SUD. Participants were randomly allocated to either group A (weeks 1-3 on MPH-SODAS, weeks 4-6 on placebo or group B (reverse order. The primary outcome measures were the Swanson, Nolan and Pelham Scale, version IV (SNAP-IV and the Clinical Global Impression Scale (CGI. We also evaluated the adverse effects of MPH-SODAS using the Barkley Side Effect Rating Scale and subject reports of drug use during the study. The sample consisted of marijuana (N = 16; 100% and cocaine users (N = 7; 43.8%. Subjects had a significantly greater reduction in SNAP-IV and CGI scores (P < 0.001 for all analyses during MPH-SODAS treatment compared to placebo. No significant effects for period or sequence were found in analyses with the SNAP-IV and CGI scales. There was no significant effect on drug use. MPH-SODAS was well tolerated but was associated with more severe appetite reduction than placebo (P < 0.001. MPH-SODAS was more effective than placebo in reducing ADHD symptoms in a non-abstinent outpatient sample of adolescents with comorbid SUD. Randomized clinical trials, with larger samples and SUD intervention, are recommended.

Media Use and Source Trust among Muslims in Seven Countries: Results of a Large Random Sample Survey

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Steven R. Corman

2013-12-01

Full Text Available Despite the perceived importance of media in the spread of and resistance against Islamist extremism, little is known about how Muslims use different kinds of media to get information about religious issues, and what sources they trust when doing so. This paper reports the results of a large, random sample survey among Muslims in seven countries Southeast Asia, West Africa and Western Europe, which helps fill this gap. Results show a diverse set of profiles of media use and source trust that differ by country, with overall low trust in mediated sources of information. Based on these findings, we conclude that mass media is still the most common source of religious information for Muslims, but that trust in mediated information is low overall. This suggests that media are probably best used to persuade opinion leaders, who will then carry anti-extremist messages through more personal means.