Extending cluster lot quality assurance sampling designs for surveillance programs.

PubMed

Hund, Lauren; Pagano, Marcello

2014-07-20

Lot quality assurance sampling (LQAS) has a long history of applications in industrial quality control. LQAS is frequently used for rapid surveillance in global health settings, with areas classified as poor or acceptable performance on the basis of the binary classification of an indicator. Historically, LQAS surveys have relied on simple random samples from the population; however, implementing two-stage cluster designs for surveillance sampling is often more cost-effective than simple random sampling. By applying survey sampling results to the binary classification procedure, we develop a simple and flexible nonparametric procedure to incorporate clustering effects into the LQAS sample design to appropriately inflate the sample size, accommodating finite numbers of clusters in the population when relevant. We use this framework to then discuss principled selection of survey design parameters in longitudinal surveillance programs. We apply this framework to design surveys to detect rises in malnutrition prevalence in nutrition surveillance programs in Kenya and South Sudan, accounting for clustering within villages. By combining historical information with data from previous surveys, we design surveys to detect spikes in the childhood malnutrition rate. Copyright © 2014 John Wiley & Sons, Ltd.

Sample size calculations for stepped wedge and cluster randomised trials: a unified approach

PubMed Central

Hemming, Karla; Taljaard, Monica

2016-01-01

Objectives To clarify and illustrate sample size calculations for the cross-sectional stepped wedge cluster randomized trial (SW-CRT) and to present a simple approach for comparing the efficiencies of competing designs within a unified framework. Study Design and Setting We summarize design effects for the SW-CRT, the parallel cluster randomized trial (CRT), and the parallel cluster randomized trial with before and after observations (CRT-BA), assuming cross-sectional samples are selected over time. We present new formulas that enable trialists to determine the required cluster size for a given number of clusters. We illustrate by example how to implement the presented design effects and give practical guidance on the design of stepped wedge studies. Results For a fixed total cluster size, the choice of study design that provides the greatest power depends on the intracluster correlation coefficient (ICC) and the cluster size. When the ICC is small, the CRT tends to be more efficient; when the ICC is large, the SW-CRT tends to be more efficient and can serve as an alternative design when the CRT is an infeasible design. Conclusion Our unified approach allows trialists to easily compare the efficiencies of three competing designs to inform the decision about the most efficient design in a given scenario. PMID:26344808

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.

PubMed

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.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR).

PubMed

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-06-01

Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy.

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

PubMed

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 of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.

A cluster randomized trial of strategies to increase uptake amongst young women invited for their first cervical screen: The STRATEGIC trial.

PubMed

Kitchener, H; Gittins, M; Cruickshank, M; Moseley, C; Fletcher, S; Albrow, R; Gray, A; Brabin, L; Torgerson, D; Crosbie, E J; Sargent, A; Roberts, C

2018-06-01

Objectives To measure the feasibility and effectiveness of interventions to increase cervical screening uptake amongst young women. Methods A two-phase cluster randomized trial conducted in general practices in the NHS Cervical Screening Programme. In Phase 1, women in practices randomized to intervention due for their first invitation to cervical screening received a pre-invitation leaflet and, separately, access to online booking. In Phase 2, non-attenders at six months were randomized to one of: vaginal self-sample kits sent unrequested or offered; timed appointments; nurse navigator; or the choice between nurse navigator or self-sample kits. Primary outcome was uplift in intervention vs. control practices, at 3 and 12 months post invitation. Results Phase 1 randomized 20,879 women. Neither pre-invitation leaflet nor online booking increased screening uptake by three months (18.8% pre-invitation leaflet vs. 19.2% control and 17.8% online booking vs. 17.2% control). Uptake was higher amongst human papillomavirus vaccinees at three months (OR 2.07, 95% CI 1.69-2.53, p < 0.001). Phase 2 randomized 10,126 non-attenders, with 32-34 clusters for each intervention and 100 clusters as controls. Sending self-sample kits increased uptake at 12 months (OR 1.51, 95% CI 1.20-1.91, p = 0.001), as did timed appointments (OR 1.41, 95% CI 1.14-1.74, p = 0.001). The offer of a nurse navigator, a self-sample kits on request, and choice between timed appointments and nurse navigator were ineffective. Conclusions Amongst non-attenders, self-sample kits sent and timed appointments achieved an uplift in screening over the short term; longer term impact is less certain. Prior human papillomavirus vaccination was associated with increased screening uptake.

Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

PubMed

Nixon, R M; Thompson, S G

2003-09-15

Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for. Copyright 2003 John Wiley & Sons, Ltd.

Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

PubMed Central

Liu, Wenfen

2017-01-01

Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically; compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted k-means clustering and thus gives the theoretical guarantee to this special kind of k-means clustering where each point has its corresponding weight. PMID:29312447

Sample size calculations for the design of cluster randomized trials: A summary of methodology.

PubMed

Gao, Fei; Earnest, Arul; Matchar, David B; Campbell, Michael J; Machin, David

2015-05-01

Cluster randomized trial designs are growing in popularity in, for example, cardiovascular medicine research and other clinical areas and parallel statistical developments concerned with the design and analysis of these trials have been stimulated. Nevertheless, reviews suggest that design issues associated with cluster randomized trials are often poorly appreciated and there remain inadequacies in, for example, describing how the trial size is determined and the associated results are presented. In this paper, our aim is to provide pragmatic guidance for researchers on the methods of calculating sample sizes. We focus attention on designs with the primary purpose of comparing two interventions with respect to continuous, binary, ordered categorical, incidence rate and time-to-event outcome variables. Issues of aggregate and non-aggregate cluster trials, adjustment for variation in cluster size and the effect size are detailed. The problem of establishing the anticipated magnitude of between- and within-cluster variation to enable planning values of the intra-cluster correlation coefficient and the coefficient of variation are also described. Illustrative examples of calculations of trial sizes for each endpoint type are included. Copyright © 2015 Elsevier Inc. All rights reserved.

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

ERIC Educational Resources Information Center

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)

Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

PubMed

Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

2014-07-10

In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

The Effect of Cluster Sampling Design in Survey Research on the Standard Error Statistic.

ERIC Educational Resources Information Center

Wang, Lin; Fan, Xitao

Standard statistical methods are used to analyze data that is assumed to be collected using a simple random sampling scheme. These methods, however, tend to underestimate variance when the data is collected with a cluster design, which is often found in educational survey research. The purposes of this paper are to demonstrate how a cluster design…

Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach

ERIC Educational Resources Information Center

Rotondi, Michael A.; Donner, Allan

2009-01-01

The educational field has now accumulated an extensive literature reporting on values of the intraclass correlation coefficient, a parameter essential to determining the required size of a planned cluster randomized trial. We propose here a simple simulation-based approach including all relevant information that can facilitate this task. An…

Efficient design of cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances.

PubMed

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

2018-06-10

Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment-to-control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment-dependent costs (cost-considered design). The results show that the balanced design is the MMD if the treatment-to control cost ratio is the same at both design levels (cluster, person) and within the range for the treatment-to-control variance ratio. It still is highly efficient and better than the cost-considered design if the cost ratio is within the range for the squared variance ratio. Outside that range, the cost-considered design is better and highly efficient, but it is not the MMD. An example shows sample size calculation for the MMD, and the computer code (SPSS and R) is provided as supplementary material. The MMD is recommended for trial planning if the study costs are treatment-dependent and homogeneity of variances cannot be assumed. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Intra-class correlation estimates for assessment of vitamin A intake in children.

PubMed

Agarwal, Girdhar G; Awasthi, Shally; Walter, Stephen D

2005-03-01

In many community-based surveys, multi-level sampling is inherent in the design. In the design of these studies, especially to calculate the appropriate sample size, investigators need good estimates of intra-class correlation coefficient (ICC), along with the cluster size, to adjust for variation inflation due to clustering at each level. The present study used data on the assessment of clinical vitamin A deficiency and intake of vitamin A-rich food in children in a district in India. For the survey, 16 households were sampled from 200 villages nested within eight randomly-selected blocks of the district. ICCs and components of variances were estimated from a three-level hierarchical random effects analysis of variance model. Estimates of ICCs and variance components were obtained at village and block levels. Between-cluster variation was evident at each level of clustering. In these estimates, ICCs were inversely related to cluster size, but the design effect could be substantial for large clusters. At the block level, most ICC estimates were below 0.07. At the village level, many ICC estimates ranged from 0.014 to 0.45. These estimates may provide useful information for the design of epidemiological studies in which the sampled (or allocated) units range in size from households to large administrative zones.

Quantifying opening-mode fracture spatial organization in horizontal wellbore image logs, core and outcrop: Application to Upper Cretaceous Frontier Formation tight gas sandstones, USA

NASA Astrophysics Data System (ADS)

Li, J. Z.; Laubach, S. E.; Gale, J. F. W.; Marrett, R. A.

2018-03-01

The Upper Cretaceous Frontier Formation is a naturally fractured gas-producing sandstone in Wyoming. Regionally, random and statistically more clustered than random patterns exist in the same upper to lower shoreface depositional facies. East-west- and north-south-striking regional fractures sampled using image logs and cores from three horizontal wells exhibit clustered patterns, whereas data collected from east-west-striking fractures in outcrop have patterns that are indistinguishable from random. Image log data analyzed with the correlation count method shows clusters ∼35 m wide and spaced ∼50 to 90 m apart as well as clusters up to 12 m wide with periodic inter-cluster spacings. A hierarchy of cluster sizes exists; organization within clusters is likely fractal. These rocks have markedly different structural and burial histories, so regional differences in degree of clustering are unsurprising. Clustered patterns correspond to fractures having core quartz deposition contemporaneous with fracture opening, circumstances that some models suggest might affect spacing patterns by interfering with fracture growth. Our results show that quantifying and identifying patterns as statistically more or less clustered than random delineates differences in fracture patterns that are not otherwise apparent but that may influence gas and water production, and therefore may be economically important.

The Method of Randomization for Cluster-Randomized Trials: Challenges of Including Patients with Multiple Chronic Conditions

PubMed Central

Esserman, Denise; Allore, Heather G.; Travison, Thomas G.

2016-01-01

Cluster-randomized clinical trials (CRT) are trials in which the unit of randomization is not a participant but a group (e.g. healthcare systems or community centers). They are suitable when the intervention applies naturally to the cluster (e.g. healthcare policy); when lack of independence among participants may occur (e.g. nursing home hygiene); or when it is most ethical to apply an intervention to all within a group (e.g. school-level immunization). Because participants in the same cluster receive the same intervention, CRT may approximate clinical practice, and may produce generalizable findings. However, when not properly designed or interpreted, CRT may induce biased results. CRT designs have features that add complexity to statistical estimation and inference. Chief among these is the cluster-level correlation in response measurements induced by the randomization. A critical consideration is the experimental unit of inference; often it is desirable to consider intervention effects at the level of the individual rather than the cluster. Finally, given that the number of clusters available may be limited, simple forms of randomization may not achieve balance between intervention and control arms at either the cluster- or participant-level. In non-clustered clinical trials, balance of key factors may be easier to achieve because the sample can be homogenous by exclusion of participants with multiple chronic conditions (MCC). CRTs, which are often pragmatic, may eschew such restrictions. Failure to account for imbalance may induce bias and reducing validity. This article focuses on the complexities of randomization in the design of CRTs, such as the inclusion of patients with MCC, and imbalances in covariate factors across clusters. PMID:27478520

An improved initialization center k-means clustering algorithm based on distance and density

NASA Astrophysics Data System (ADS)

Duan, Yanling; Liu, Qun; Xia, Shuyin

2018-04-01

Aiming at the problem of the random initial clustering center of k means algorithm that the clustering results are influenced by outlier data sample and are unstable in multiple clustering, a method of central point initialization method based on larger distance and higher density is proposed. The reciprocal of the weighted average of distance is used to represent the sample density, and the data sample with the larger distance and the higher density are selected as the initial clustering centers to optimize the clustering results. Then, a clustering evaluation method based on distance and density is designed to verify the feasibility of the algorithm and the practicality, the experimental results on UCI data sets show that the algorithm has a certain stability and practicality.

Cluster Randomized Test-Negative Design (CR-TND) Trials: A Novel and Efficient Method to Assess the Efficacy of Community Level Dengue Interventions.

PubMed

Anders, Katherine L; Cutcher, Zoe; Kleinschmidt, Immo; Donnelly, Christl A; Ferguson, Neil M; Indriani, Citra; O'Neill, Scott L; Jewell, Nicholas P; Simmons, Cameron P

2018-05-07

Cluster randomized trials are the gold standard for assessing efficacy of community-level interventions, such as vector control strategies against dengue. We describe a novel cluster randomized trial methodology with a test-negative design, which offers advantages over traditional approaches. It utilizes outcome-based sampling of patients presenting with a syndrome consistent with the disease of interest, who are subsequently classified as test-positive cases or test-negative controls on the basis of diagnostic testing. We use simulations of a cluster trial to demonstrate validity of efficacy estimates under the test-negative approach. This demonstrates that, provided study arms are balanced for both test-negative and test-positive illness at baseline and that other test-negative design assumptions are met, the efficacy estimates closely match true efficacy. We also briefly discuss analytical considerations for an odds ratio-based effect estimate arising from clustered data, and outline potential approaches to analysis. We conclude that application of the test-negative design to certain cluster randomized trials could increase their efficiency and ease of implementation.

Probability of coincidental similarity among the orbits of small bodies - I. Pairing

NASA Astrophysics Data System (ADS)

Jopek, Tadeusz Jan; Bronikowska, Małgorzata

2017-09-01

Probability of coincidental clustering among orbits of comets, asteroids and meteoroids depends on many factors like: the size of the orbital sample searched for clusters or the size of the identified group, it is different for groups of 2,3,4,… members. Probability of coincidental clustering is assessed by the numerical simulation, therefore, it depends also on the method used for the synthetic orbits generation. We have tested the impact of some of these factors. For a given size of the orbital sample we have assessed probability of random pairing among several orbital populations of different sizes. We have found how these probabilities vary with the size of the orbital samples. Finally, keeping fixed size of the orbital sample we have shown that the probability of random pairing can be significantly different for the orbital samples obtained by different observation techniques. Also for the user convenience we have obtained several formulae which, for given size of the orbital sample can be used to calculate the similarity threshold corresponding to the small value of the probability of coincidental similarity among two orbits.

Enhancing local health department disaster response capacity with rapid community needs assessments: validation of a computerized program for binary attribute cluster sampling.

PubMed

Groenewold, Matthew R

2006-01-01

Local health departments are among the first agencies to respond to disasters or other mass emergencies. However, they often lack the ability to handle large-scale events. Plans including locally developed and deployed tools may enhance local response. Simplified cluster sampling methods can be useful in assessing community needs after a sudden-onset, short duration event. Using an adaptation of the methodology used by the World Health Organization Expanded Programme on Immunization (EPI), a Microsoft Access-based application for two-stage cluster sampling of residential addresses in Louisville/Jefferson County Metro, Kentucky was developed. The sampling frame was derived from geographically referenced data on residential addresses and political districts available through the Louisville/Jefferson County Information Consortium (LOJIC). The program randomly selected 30 clusters, defined as election precincts, from within the area of interest, and then, randomly selected 10 residential addresses from each cluster. The program, called the Rapid Assessment Tools Package (RATP), was tested in terms of accuracy and precision using data on a dichotomous characteristic of residential addresses available from the local tax assessor database. A series of 30 samples were produced and analyzed with respect to their precision and accuracy in estimating the prevalence of the study attribute. Point estimates with 95% confidence intervals were calculated by determining the proportion of the study attribute values in each of the samples and compared with the population proportion. To estimate the design effect, corresponding simple random samples of 300 addresses were taken after each of the 30 cluster samples. The sample proportion fell within +/-10 absolute percentage points of the true proportion in 80% of the samples. In 93.3% of the samples, the point estimate fell within +/-12.5%, and 96.7% fell within +/-15%. All of the point estimates fell within +/-20% of the true proportion. Estimates of the design effect ranged from 0.926 to 1.436 (mean = 1.157, median = 1.170) for the 30 samples. Although prospective evaluation of its performance in field trials or a real emergency is required to confirm its utility, this study suggests that the RATP, a locally designed and deployed tool, may provide population-based estimates of community needs or the extent of event-related consequences that are precise enough to serve as the basis for the initial post-event decisions regarding relief efforts.

Small Sample Performance of Bias-corrected Sandwich Estimators for Cluster-Randomized Trials with Binary Outcomes

PubMed Central

Li, Peng; Redden, David T.

2014-01-01

SUMMARY The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster-randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias-corrected sandwich estimators. Our results suggest that the GEE Wald z test should be avoided in the analyses of CRTs with few clusters even when bias-corrected sandwich estimators are used. With t-distribution approximation, the Kauermann and Carroll (KC)-correction can keep the test size to nominal levels even when the number of clusters is as low as 10, and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)-correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t test and KC-correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes due to fewer assumptions and robustness to the misspecification of the covariance structure. PMID:25345738

Emotional Intelligence and Life Adjustment for Nigerian Secondary Students

ERIC Educational Resources Information Center

Ogoemeka, Obioma Helen

2013-01-01

In the process of educating adolescents, good emotional development and life adjustment are two significant factors for teachers to know. This study employed random cluster sampling of senior secondary school students in Ondo and Oyo States in south-western Nigeria. The Random sampling was employed to select 1,070 students. The data collected were…

A pilot cluster randomized controlled trial of structured goal-setting following stroke.

PubMed

Taylor, William J; Brown, Melanie; William, Levack; McPherson, Kathryn M; Reed, Kirk; Dean, Sarah G; Weatherall, Mark

2012-04-01

To determine the feasibility, the cluster design effect and the variance and minimal clinical importance difference in the primary outcome in a pilot study of a structured approach to goal-setting. A cluster randomized controlled trial. Inpatient rehabilitation facilities. People who were admitted to inpatient rehabilitation following stroke who had sufficient cognition to engage in structured goal-setting and complete the primary outcome measure. Structured goal elicitation using the Canadian Occupational Performance Measure. Quality of life at 12 weeks using the Schedule for Individualised Quality of Life (SEIQOL-DW), Functional Independence Measure, Short Form 36 and Patient Perception of Rehabilitation (measuring satisfaction with rehabilitation). Assessors were blinded to the intervention. Four rehabilitation services and 41 patients were randomized. We found high values of the intraclass correlation for the outcome measures (ranging from 0.03 to 0.40) and high variance of the SEIQOL-DW (SD 19.6) in relation to the minimally importance difference of 2.1, leading to impractically large sample size requirements for a cluster randomized design. A cluster randomized design is not a practical means of avoiding contamination effects in studies of inpatient rehabilitation goal-setting. Other techniques for coping with contamination effects are necessary.

Relative efficiency of unequal versus equal cluster sizes in cluster randomized trials using generalized estimating equation models.

PubMed

Liu, Jingxia; Colditz, Graham A

2018-05-01

There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the "working correlation structure" is introduced and the association pattern depends on a vector of association parameters denoted by ρ. In this paper, we utilize GEE models to test the treatment effect in a two-group comparison for continuous, binary, or count data in CRTs. The variances of the estimator of the treatment effect are derived for the different types of outcome. RE is defined as the ratio of variance of the estimator of the treatment effect for equal to unequal cluster sizes. We discuss a commonly used structure in CRTs-exchangeable, and derive the simpler formula of RE with continuous, binary, and count outcomes. Finally, REs are investigated for several scenarios of cluster size distributions through simulation studies. We propose an adjusted sample size due to efficiency loss. Additionally, we also propose an optimal sample size estimation based on the GEE models under a fixed budget for known and unknown association parameter (ρ) in the working correlation structure within the cluster. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Effect of Cluster-Based Instruction on Mathematic Achievement in Inclusive Schools

ERIC Educational Resources Information Center

Gunarhadi, Sunardi; Anwar, Mohammad; Andayani, Tri Rejeki; Shaari, Abdull Sukor

2016-01-01

The research aimed to investigate the effect of Cluster-Based Instruction (CBI) on the academic achievement of Mathematics in inclusive schools. The sample was 68 students in two intact classes, including those with learning disabilities, selected using a cluster random technique among 17 inclusive schools in the regency of Surakarta. The two…

Effects of a Physical Education-Based Programme on Health-Related Physical Fitness and Its Maintenance in High School Students: A Cluster-Randomized Controlled Trial

ERIC Educational Resources Information Center

Mayorga-Vega, Daniel; Montoro-Escaño, Jorge; Merino-Marban, Rafael; Viciana, Jesús

2016-01-01

The purpose of this study was to examine the effects of a physical education-based development and maintenance programme on objective and perceived health-related physical fitness in high school students. A sample of 111 students aged 12-14 years old from six classes were cluster-randomly assigned to an experimental group (n = 54) or a control…

Visualizing Time-Varying Distribution Data in EOS Application

NASA Technical Reports Server (NTRS)

Shen, Han-Wei

2004-01-01

In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.

Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.

PubMed

Johnson, Jacqueline L; Kreidler, Sarah M; Catellier, Diane J; Murray, David M; Muller, Keith E; Glueck, Deborah H

2015-11-30

We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes and accounts for within-cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist, and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least six clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Because small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach. Copyright © 2015 John Wiley & Sons, Ltd.

Design of a Phase III cluster randomized trial to assess the efficacy and safety of a malaria transmission blocking vaccine.

PubMed

Delrieu, Isabelle; Leboulleux, Didier; Ivinson, Karen; Gessner, Bradford D

2015-03-24

Vaccines interrupting Plasmodium falciparum malaria transmission targeting sexual, sporogonic, or mosquito-stage antigens (SSM-VIMT) are currently under development to reduce malaria transmission. An international group of malaria experts was established to evaluate the feasibility and optimal design of a Phase III cluster randomized trial (CRT) that could support regulatory review and approval of an SSM-VIMT. The consensus design is a CRT with a sentinel population randomly selected from defined inner and buffer zones in each cluster, a cluster size sufficient to assess true vaccine efficacy in the inner zone, and inclusion of ongoing assessment of vaccine impact stratified by distance of residence from the cluster edge. Trials should be conducted first in areas of moderate transmission, where SSM-VIMT impact should be greatest. Sample size estimates suggest that such a trial is feasible, and within the range of previously supported trials of malaria interventions, although substantial issues to implementation exist. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.

PubMed

Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark

2012-07-01

Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called 'clustering'. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure.

Restricted random search method based on taboo search in the multiple minima problem

NASA Astrophysics Data System (ADS)

Hong, Seung Do; Jhon, Mu Shik

1997-03-01

The restricted random search method is proposed as a simple Monte Carlo sampling method to search minima fast in the multiple minima problem. This method is based on taboo search applied recently to continuous test functions. The concept of the taboo region instead of the taboo list is used and therefore the sampling of a region near an old configuration is restricted in this method. This method is applied to 2-dimensional test functions and the argon clusters. This method is found to be a practical and efficient method to search near-global configurations of test functions and the argon clusters.

Predicting the random drift of MEMS gyroscope based on K-means clustering and OLS RBF Neural Network

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Zhang, Li-jie

2017-10-01

Measure error of the sensor can be effectively compensated with prediction. Aiming at large random drift error of MEMS(Micro Electro Mechanical System))gyroscope, an improved learning algorithm of Radial Basis Function(RBF) Neural Network(NN) based on K-means clustering and Orthogonal Least-Squares (OLS) is proposed in this paper. The algorithm selects the typical samples as the initial cluster centers of RBF NN firstly, candidates centers with K-means algorithm secondly, and optimizes the candidate centers with OLS algorithm thirdly, which makes the network structure simpler and makes the prediction performance better. Experimental results show that the proposed K-means clustering OLS learning algorithm can predict the random drift of MEMS gyroscope effectively, the prediction error of which is 9.8019e-007°/s and the prediction time of which is 2.4169e-006s

Sampling procedures for inventory of commercial volume tree species in Amazon Forest.

PubMed

Netto, Sylvio P; Pelissari, Allan L; Cysneiros, Vinicius C; Bonazza, Marcelo; Sanquetta, Carlos R

2017-01-01

The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

ADAPTIVE MATCHING IN RANDOMIZED TRIALS AND OBSERVATIONAL STUDIES

PubMed Central

van der Laan, Mark J.; Balzer, Laura B.; Petersen, Maya L.

2014-01-01

SUMMARY In many randomized and observational studies the allocation of treatment among a sample of n independent and identically distributed units is a function of the covariates of all sampled units. As a result, the treatment labels among the units are possibly dependent, complicating estimation and posing challenges for statistical inference. For example, cluster randomized trials frequently sample communities from some target population, construct matched pairs of communities from those included in the sample based on some metric of similarity in baseline community characteristics, and then randomly allocate a treatment and a control intervention within each matched pair. In this case, the observed data can neither be represented as the realization of n independent random variables, nor, contrary to current practice, as the realization of n/2 independent random variables (treating the matched pair as the independent sampling unit). In this paper we study estimation of the average causal effect of a treatment under experimental designs in which treatment allocation potentially depends on the pre-intervention covariates of all units included in the sample. We define efficient targeted minimum loss based estimators for this general design, present a theorem that establishes the desired asymptotic normality of these estimators and allows for asymptotically valid statistical inference, and discuss implementation of these estimators. We further investigate the relative asymptotic efficiency of this design compared with a design in which unit-specific treatment assignment depends only on the units’ covariates. Our findings have practical implications for the optimal design and analysis of pair matched cluster randomized trials, as well as for observational studies in which treatment decisions may depend on characteristics of the entire sample. PMID:25097298

Sampling methods for stellar masses and the mmax-Mecl relation in the starburst dwarf galaxy NGC 4214

NASA Astrophysics Data System (ADS)

Weidner, Carsten; Kroupa, Pavel; Pflamm-Altenburg, Jan

2014-07-01

It has been claimed in the recent literature that a non-trivial relation between the mass of the most-massive star, mmax, in a star cluster and its embedded star cluster mass (the mmax - Mecl relation) is falsified by observations of the most-massive stars and the Hα luminosity of young star clusters in the starburst dwarf galaxy NGC 4214. Here, it is shown by comparing the NGC 4214 results with observations from the Milky Way that NGC 4214 agrees very well with the predictions of the mmax - Mecl relation and with the integrated galactic stellar initial mass function theory. The difference in conclusions is based on a high degree of degeneracy between expectations from random sampling and those from the mmax - Mecl relation, but are also due to interpreting mmax as a truncation mass in a randomly sampled initial mass function. Additional analysis of galaxies with lower SFRs than those currently presented in the literature will be required to break this degeneracy.

SU-G-TeP3-14: Three-Dimensional Cluster Model in Inhomogeneous Dose Distribution

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

Wei, J; Penagaricano, J; Narayanasamy, G

2016-06-15

Purpose: We aim to investigate 3D cluster formation in inhomogeneous dose distribution to search for new models predicting radiation tissue damage and further leading to new optimization paradigm for radiotherapy planning. Methods: The aggregation of higher dose in the organ at risk (OAR) than a preset threshold was chosen as the cluster whose connectivity dictates the cluster structure. Upon the selection of the dose threshold, the fractional density defined as the fraction of voxels in the organ eligible to be part of the cluster was determined according to the dose volume histogram (DVH). A Monte Carlo method was implemented tomore » establish a case pertinent to the corresponding DVH. Ones and zeros were randomly assigned to each OAR voxel with the sampling probability equal to the fractional density. Ten thousand samples were randomly generated to ensure a sufficient number of cluster sets. A recursive cluster searching algorithm was developed to analyze the cluster with various connectivity choices like 1-, 2-, and 3-connectivity. The mean size of the largest cluster (MSLC) from the Monte Carlo samples was taken to be a function of the fractional density. Various OARs from clinical plans were included in the study. Results: Intensive Monte Carlo study demonstrates the inverse relationship between the MSLC and the cluster connectivity as anticipated and the cluster size does not change with fractional density linearly regardless of the connectivity types. An initially-slow-increase to exponential growth transition of the MSLC from low to high density was observed. The cluster sizes were found to vary within a large range and are relatively independent of the OARs. Conclusion: The Monte Carlo study revealed that the cluster size could serve as a suitable index of the tissue damage (percolation cluster) and the clinical outcome of the same DVH might be potentially different.« less

Confidence intervals for a difference between lognormal means in cluster randomization trials.

PubMed

Poirier, Julia; Zou, G Y; Koval, John

2017-04-01

Cluster randomization trials, in which intact social units are randomized to different interventions, have become popular in the last 25 years. Outcomes from these trials in many cases are positively skewed, following approximately lognormal distributions. When inference is focused on the difference between treatment arm arithmetic means, existent confidence interval procedures either make restricting assumptions or are complex to implement. We approach this problem by assuming log-transformed outcomes from each treatment arm follow a one-way random effects model. The treatment arm means are functions of multiple parameters for which separate confidence intervals are readily available, suggesting that the method of variance estimates recovery may be applied to obtain closed-form confidence intervals. A simulation study showed that this simple approach performs well in small sample sizes in terms of empirical coverage, relatively balanced tail errors, and interval widths as compared to existing methods. The methods are illustrated using data arising from a cluster randomization trial investigating a critical pathway for the treatment of community acquired pneumonia.

Creel survey sampling designs for estimating effort in short-duration Chinook salmon fisheries

USGS Publications Warehouse

McCormick, Joshua L.; Quist, Michael C.; Schill, Daniel J.

2013-01-01

Chinook Salmon Oncorhynchus tshawytscha sport fisheries in the Columbia River basin are commonly monitored using roving creel survey designs and require precise, unbiased catch estimates. The objective of this study was to examine the relative bias and precision of total catch estimates using various sampling designs to estimate angling effort under the assumption that mean catch rate was known. We obtained information on angling populations based on direct visual observations of portions of Chinook Salmon fisheries in three Idaho river systems over a 23-d period. Based on the angling population, Monte Carlo simulations were used to evaluate the properties of effort and catch estimates for each sampling design. All sampling designs evaluated were relatively unbiased. Systematic random sampling (SYS) resulted in the most precise estimates. The SYS and simple random sampling designs had mean square error (MSE) estimates that were generally half of those observed with cluster sampling designs. The SYS design was more efficient (i.e., higher accuracy per unit cost) than a two-cluster design. Increasing the number of clusters available for sampling within a day decreased the MSE of estimates of daily angling effort, but the MSE of total catch estimates was variable depending on the fishery. The results of our simulations provide guidelines on the relative influence of sample sizes and sampling designs on parameters of interest in short-duration Chinook Salmon fisheries.

A primer on stand and forest inventory designs

Treesearch

H. Gyde Lund; Charles E. Thomas

1989-01-01

Covers designs for the inventory of stands and forests in detail and with worked-out examples. For stands, random sampling, line transects, ricochet plot, systematic sampling, single plot, cluster, subjective sampling and complete enumeration are discussed. For forests inventory, the main categories are subjective sampling, inventories without prior stand mapping,...

A nonparametric method to generate synthetic populations to adjust for complex sampling design features.

PubMed

Dong, Qi; Elliott, Michael R; Raghunathan, Trivellore E

2014-06-01

Outside of the survey sampling literature, samples are often assumed to be generated by a simple random sampling process that produces independent and identically distributed (IID) samples. Many statistical methods are developed largely in this IID world. Application of these methods to data from complex sample surveys without making allowance for the survey design features can lead to erroneous inferences. Hence, much time and effort have been devoted to develop the statistical methods to analyze complex survey data and account for the sample design. This issue is particularly important when generating synthetic populations using finite population Bayesian inference, as is often done in missing data or disclosure risk settings, or when combining data from multiple surveys. By extending previous work in finite population Bayesian bootstrap literature, we propose a method to generate synthetic populations from a posterior predictive distribution in a fashion inverts the complex sampling design features and generates simple random samples from a superpopulation point of view, making adjustment on the complex data so that they can be analyzed as simple random samples. We consider a simulation study with a stratified, clustered unequal-probability of selection sample design, and use the proposed nonparametric method to generate synthetic populations for the 2006 National Health Interview Survey (NHIS), and the Medical Expenditure Panel Survey (MEPS), which are stratified, clustered unequal-probability of selection sample designs.

A nonparametric method to generate synthetic populations to adjust for complex sampling design features

PubMed Central

Dong, Qi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Outside of the survey sampling literature, samples are often assumed to be generated by a simple random sampling process that produces independent and identically distributed (IID) samples. Many statistical methods are developed largely in this IID world. Application of these methods to data from complex sample surveys without making allowance for the survey design features can lead to erroneous inferences. Hence, much time and effort have been devoted to develop the statistical methods to analyze complex survey data and account for the sample design. This issue is particularly important when generating synthetic populations using finite population Bayesian inference, as is often done in missing data or disclosure risk settings, or when combining data from multiple surveys. By extending previous work in finite population Bayesian bootstrap literature, we propose a method to generate synthetic populations from a posterior predictive distribution in a fashion inverts the complex sampling design features and generates simple random samples from a superpopulation point of view, making adjustment on the complex data so that they can be analyzed as simple random samples. We consider a simulation study with a stratified, clustered unequal-probability of selection sample design, and use the proposed nonparametric method to generate synthetic populations for the 2006 National Health Interview Survey (NHIS), and the Medical Expenditure Panel Survey (MEPS), which are stratified, clustered unequal-probability of selection sample designs. PMID:29200608

Applying the Anderson-Darling test to suicide clusters: evidence of contagion at U. S. universities?

PubMed

MacKenzie, Donald W

2013-01-01

Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. Suicide dates were collected for MIT and Cornell for 1990-2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.

Using Geographic Information Systems and Spatial Analysis Methods to Assess Household Water Access and Sanitation Coverage in the SHINE Trial.

PubMed

Ntozini, Robert; Marks, Sara J; Mangwadu, Goldberg; Mbuya, Mduduzi N N; Gerema, Grace; Mutasa, Batsirai; Julian, Timothy R; Schwab, Kellogg J; Humphrey, Jean H; Zungu, Lindiwe I

2015-12-15

Access to water and sanitation are important determinants of behavioral responses to hygiene and sanitation interventions. We estimated cluster-specific water access and sanitation coverage to inform a constrained randomization technique in the SHINE trial. Technicians and engineers inspected all public access water sources to ascertain seasonality, function, and geospatial coordinates. Households and water sources were mapped using open-source geospatial software. The distance from each household to the nearest perennial, functional, protected water source was calculated, and for each cluster, the median distance and the proportion of households within <500 m and >1500 m of such a water source. Cluster-specific sanitation coverage was ascertained using a random sample of 13 households per cluster. These parameters were included as covariates in randomization to optimize balance in water and sanitation access across treatment arms at the start of the trial. The observed high variability between clusters in both parameters suggests that constraining on these factors was needed to reduce risk of bias. © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America.

Optimal sampling design for estimating spatial distribution and abundance of a freshwater mussel population

USGS Publications Warehouse

Pooler, P.S.; Smith, D.R.

2005-01-01

We compared the ability of simple random sampling (SRS) and a variety of systematic sampling (SYS) designs to estimate abundance, quantify spatial clustering, and predict spatial distribution of freshwater mussels. Sampling simulations were conducted using data obtained from a census of freshwater mussels in a 40 X 33 m section of the Cacapon River near Capon Bridge, West Virginia, and from a simulated spatially random population generated to have the same abundance as the real population. Sampling units that were 0.25 m 2 gave more accurate and precise abundance estimates and generally better spatial predictions than 1-m2 sampling units. Systematic sampling with ???2 random starts was more efficient than SRS. Estimates of abundance based on SYS were more accurate when the distance between sampling units across the stream was less than or equal to the distance between sampling units along the stream. Three measures for quantifying spatial clustering were examined: Hopkins Statistic, the Clumping Index, and Morisita's Index. Morisita's Index was the most reliable, and the Hopkins Statistic was prone to false rejection of complete spatial randomness. SYS designs with units spaced equally across and up stream provided the most accurate predictions when estimating the spatial distribution by kriging. Our research indicates that SYS designs with sampling units equally spaced both across and along the stream would be appropriate for sampling freshwater mussels even if no information about the true underlying spatial distribution of the population were available to guide the design choice. ?? 2005 by The North American Benthological Society.

Topology in two dimensions. II - The Abell and ACO cluster catalogues

NASA Astrophysics Data System (ADS)

Plionis, Manolis; Valdarnini, Riccardo; Coles, Peter

1992-09-01

We apply a method for quantifying the topology of projected galaxy clustering to the Abell and ACO catalogues of rich clusters. We use numerical simulations to quantify the statistical bias involved in using high peaks to define the large-scale structure, and we use the results obtained to correct our observational determinations for this known selection effect and also for possible errors introduced by boundary effects. We find that the Abell cluster sample is consistent with clusters being identified with high peaks of a Gaussian random field, but that the ACO shows a slight meatball shift away from the Gaussian behavior over and above that expected purely from the high-peak selection. The most conservative explanation of this effect is that it is caused by some artefact of the procedure used to select the clusters in the two samples.

Assessing the feasibility of interrupting the transmission of soil-transmitted helminths through mass drug administration: The DeWorm3 cluster randomized trial protocol.

PubMed

Ásbjörnsdóttir, Kristjana Hrönn; Ajjampur, Sitara S Rao; Anderson, Roy M; Bailey, Robin; Gardiner, Iain; Halliday, Katherine E; Ibikounle, Moudachirou; Kalua, Khumbo; Kang, Gagandeep; Littlewood, D Timothy J; Luty, Adrian J F; Means, Arianna Rubin; Oswald, William; Pullan, Rachel L; Sarkar, Rajiv; Schär, Fabian; Szpiro, Adam; Truscott, James E; Werkman, Marleen; Yard, Elodie; Walson, Judd L

2018-01-01

Current control strategies for soil-transmitted helminths (STH) emphasize morbidity control through mass drug administration (MDA) targeting preschool- and school-age children, women of childbearing age and adults in certain high-risk occupations such as agricultural laborers or miners. This strategy is effective at reducing morbidity in those treated but, without massive economic development, it is unlikely it will interrupt transmission. MDA will therefore need to continue indefinitely to maintain benefit. Mathematical models suggest that transmission interruption may be achievable through MDA alone, provided that all age groups are targeted with high coverage. The DeWorm3 Project will test the feasibility of interrupting STH transmission using biannual MDA targeting all age groups. Study sites (population ≥80,000) have been identified in Benin, Malawi and India. Each site will be divided into 40 clusters, to be randomized 1:1 to three years of twice-annual community-wide MDA or standard-of-care MDA, typically annual school-based deworming. Community-wide MDA will be delivered door-to-door, while standard-of-care MDA will be delivered according to national guidelines. The primary outcome is transmission interruption of the STH species present at each site, defined as weighted cluster-level prevalence ≤2% by quantitative polymerase chain reaction (qPCR), 24 months after the final round of MDA. Secondary outcomes include the endline prevalence of STH, overall and by species, and the endline prevalence of STH among children under five as an indicator of incident infections. Secondary analyses will identify cluster-level factors associated with transmission interruption. Prevalence will be assessed using qPCR of stool samples collected from a random sample of cluster residents at baseline, six months after the final round of MDA and 24 months post-MDA. A smaller number of individuals in each cluster will be followed with annual sampling to monitor trends in prevalence and reinfection throughout the trial. ClinicalTrials.gov NCT03014167.

The Hubble Space Telescope Medium Deep Survey Cluster Sample: Methodology and Data

NASA Astrophysics Data System (ADS)

Ostrander, E. J.; Nichol, R. C.; Ratnatunga, K. U.; Griffiths, R. E.

1998-12-01

We present a new, objectively selected, sample of galaxy overdensities detected in the Hubble Space Telescope Medium Deep Survey (MDS). These clusters/groups were found using an automated procedure that involved searching for statistically significant galaxy overdensities. The contrast of the clusters against the field galaxy population is increased when morphological data are used to search around bulge-dominated galaxies. In total, we present 92 overdensities above a probability threshold of 99.5%. We show, via extensive Monte Carlo simulations, that at least 60% of these overdensities are likely to be real clusters and groups and not random line-of-sight superpositions of galaxies. For each overdensity in the MDS cluster sample, we provide a richness and the average of the bulge-to-total ratio of galaxies within each system. This MDS cluster sample potentially contains some of the most distant clusters/groups ever detected, with about 25% of the overdensities having estimated redshifts z > ~0.9. We have made this sample publicly available to facilitate spectroscopic confirmation of these clusters and help more detailed studies of cluster and galaxy evolution. We also report the serendipitous discovery of a new cluster close on the sky to the rich optical cluster Cl l0016+16 at z = 0.546. This new overdensity, HST 001831+16208, may be coincident with both an X-ray source and a radio source. HST 001831+16208 is the third cluster/group discovered near to Cl 0016+16 and appears to strengthen the claims of Connolly et al. of superclustering at high redshift.

A comparison of two sampling approaches for assessing the urban forest canopy cover from aerial photography.

Treesearch

Ucar Zennure; Pete Bettinger; Krista Merry; Jacek Siry; J.M. Bowker

2016-01-01

Two different sampling approaches for estimating urban tree canopy cover were applied to two medium-sized cities in the United States, in conjunction with two freely available remotely sensed imagery products. A random point-based sampling approach, which involved 1000 sample points, was compared against a plot/grid sampling (cluster sampling) approach that involved a...

Clues from Bent Jets

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2018-04-01

Powerful jets emitted from the centers of distant galaxies make for spectacular signposts in the radio sky. Can observations of these jets reveal information about the environments that surround them?Signposts in the SkyVLA FIRST images of seven bent double-lobed radio galaxies from the authors sample. [Adapted from Silverstein et al. 2018]An active supermassive black hole lurking in a galactic center can put on quite a show! These beasts fling out accreting material, often forming intense jets that punch their way out of their host galaxies. As the jets propagate, they expand into large lobes of radio emission that we can spot from Earth observable signs of the connection between distant supermassive black holes and the galaxies in which they live.These distinctive double-lobed radio galaxies (DLRGs) dont all look the same. In particular, though the jets are emitted from the black holes two poles, the lobes of DLRGs dont always extend perfectly in opposite directions; often, the jets become bent on larger scales, appearing to us to subtend angles of less than 180 degrees.Can we use our observations of DLRG shapes and distributions to learn about their surroundings? A new study led by Ezekiel Silverstein (University of Michigan) has addressed this question by exploring DLRGs living in dense galaxy-cluster environments.Projected density of DLRGcentral galaxy matches (black) compared to a control sample of random positionscentral galaxy matches (red) for different distances from acluster center. DLRGs have a higher likelihood of being located close to a cluster center. [Silverstein et al. 2018]Living Near the HubTo build a sample of DLRGs in dense environments, Silverstein and collaborators started from a large catalog of DLRGs in Sloan Digital Sky Survey quasars with radio lobes visible in Very Large Array data. They then cross-matched these against three galaxy catalogs to produce a sample of 44 DLRGs that are each paired to a nearby massive galaxy, galaxy group, or galaxy cluster.To determine if these DLRGs locations are unusual, the authors next constructed a control sample of random galaxies using the same selection biases as their DLRG sample.Silverstein and collaborators found that the density of DLRGs as a function of distance from a cluster center drops off more rapidly than the density of galaxies in a typical cluster. Observed DLRGs are therefore more likely than random galaxies to be found near galaxy groups and clusters. The authors speculate that this may be a selection effect: DLRGs further from cluster centers may be less bright, preventing their detection.Bent Under PressureThe angle subtended by the DLRG radio lobes, plotted against the distance of the DLRG to the cluster center. Central galaxies (red circle) experience different physics and are therefore excluded from the sample. In the remaining sample, bent DLRGs appear to favor cluster centers, compared to unbent DLRGs. [Silverstein et al. 2018]In addition, Silverstein and collaborators found that location appears to affect the shape of a DLRG. Bent DLRGs (those with a measured angle between their lobes of 170 or smaller) are more likely to be found near a cluster center than unbent DLRGs (those with angles of 170180). The fraction of bent DLRGs is 78% within 3 million light-years of the cluster center, and 56% within double that distance compared to a typical fraction of just 29% in the field.These results support the idea that ram pressure the pressure experienced by a galaxy as it moves through the higher density environment closer to the center of a cluster is what bends the DLRGs.Whats next to learn? This study relies on a fairly small sample, so Silverstein and collaborators hope that future deep optical surveys will increase the completeness of cluster catalogs, enabling further testing of these outcomes and the exploration of other physics of galaxy-cluster environments.CitationEzekiel M Silverstein et al 2018 AJ 155 14. doi:10.3847/1538-3881/aa9d2e

MCMC Sampling for a Multilevel Model with Nonindependent Residuals within and between Cluster Units

ERIC Educational Resources Information Center

Browne, William; Goldstein, Harvey

2010-01-01

In this article, we discuss the effect of removing the independence assumptions between the residuals in two-level random effect models. We first consider removing the independence between the Level 2 residuals and instead assume that the vector of all residuals at the cluster level follows a general multivariate normal distribution. We…

Learning Bayesian Networks from Correlated Data

NASA Astrophysics Data System (ADS)

Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola

2016-05-01

Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.

A Randomized Controlled Trial to Measure Spillover Effects of a Combined Water, Sanitation, and Handwashing Intervention in Rural Bangladesh.

PubMed

Benjamin-Chung, Jade; Amin, Nuhu; Ercumen, Ayse; Arnold, Benjamin F; Hubbard, Alan E; Unicomb, Leanne; Rahman, Mahbubur; Luby, Stephen P; Colford, John M

2018-03-27

Water, sanitation, and handwashing interventions may confer spillover effects on neighbors of intervention recipients by interrupting pathogen transmission. We measured geographically local spillovers in WASH Benefits, a cluster-randomized trial in rural Bangladesh, by comparing outcomes among neighbors of intervention vs. control participants. WASH Benefits randomly allocated geographically-defined clusters to a compound-level intervention (chlorinated drinking water, upgraded sanitation, and handwashing promotion) or control. From January to August 2015, in 180 clusters, we enrolled 1,799 neighboring children age-matched to trial participants that would have been eligible for WASH Benefits had they been conceived slightly earlier or later. After 28 months of intervention, we quantified fecal indicator bacteria in toy rinse and drinking water samples, measured soil-transmitted helminth infections, and recorded caregiver-reported diarrhea and respiratory illness. Neighbors' characteristics were balanced across arms. The prevalence of detectable E. coli in tubewell samples was lower for neighbors of intervention vs. control trial participants (prevalence ratio = 0.83; 0.73, 0.95). There was no difference in fecal indicator bacteria prevalence between arms for other environmental samples. Prevalence was similar in neighbors of intervention vs. control participants for soil-transmitted helminth infection, diarrhea, and respiratory illness. A compound-level water, sanitation, and handwashing intervention reduced neighbors' tubewell water contamination but did not impact neighboring children's health.

Vitamin A deficiency and xerophthalmia in western Yemen.

PubMed

Rosen, D S; al Sharif, Z; Bashir, M; al Shabooti, A; Pizzarello, L D

1996-01-01

To determine the prevalence of xerophthalmia and the extent of vitamin A deficiency in western Yemen. A stratified cluster sample of children aged 1-5 years with clinical examination for signs of xerophthalmia as well as blood serum survey. The 18 districts of western Yemen, of which 10 clusters were chosen at random. All children aged 1-5 years resident in the cluster sites (n = 2438). Clinical signs of xerophthalmia, a history of night blindness, serum retinol levels in a random sample of clinically normal children (n =338) in addition to all children with xerophthalmia. Night blindness was found in 0.5% of the children, Bitot's spots in 1.7%, corneal ulceration in 0.04% and corneal scars in 0.04% Of the subsample, 7.2% (95% confidence interval [c.i.] 4.4-10.0%) had serum retinol values below 10 micrograms/dl; 63.0% (95% c.i. 57.6- 68.4%) had values below 20 micrograms/dl. Xerophthalmia and vitamin A deficiency are public health problems in western Yemen.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

Computational lymphatic node models in pediatric and adult hybrid phantoms for radiation dosimetry

NASA Astrophysics Data System (ADS)

Lee, Choonsik; Lamart, Stephanie; Moroz, Brian E.

2013-03-01

We developed models of lymphatic nodes for six pediatric and two adult hybrid computational phantoms to calculate the lymphatic node dose estimates from external and internal radiation exposures. We derived the number of lymphatic nodes from the recommendations in International Commission on Radiological Protection (ICRP) Publications 23 and 89 at 16 cluster locations for the lymphatic nodes: extrathoracic, cervical, thoracic (upper and lower), breast (left and right), mesentery (left and right), axillary (left and right), cubital (left and right), inguinal (left and right) and popliteal (left and right), for different ages (newborn, 1-, 5-, 10-, 15-year-old and adult). We modeled each lymphatic node within the voxel format of the hybrid phantoms by assuming that all nodes have identical size derived from published data except narrow cluster sites. The lymph nodes were generated by the following algorithm: (1) selection of the lymph node site among the 16 cluster sites; (2) random sampling of the location of the lymph node within a spherical space centered at the chosen cluster site; (3) creation of the sphere or ovoid of tissue representing the node based on lymphatic node characteristics defined in ICRP Publications 23 and 89. We created lymph nodes until the pre-defined number of lymphatic nodes at the selected cluster site was reached. This algorithm was applied to pediatric (newborn, 1-, 5-and 10-year-old male, and 15-year-old males) and adult male and female ICRP-compliant hybrid phantoms after voxelization. To assess the performance of our models for internal dosimetry, we calculated dose conversion coefficients, called S values, for selected organs and tissues with Iodine-131 distributed in six lymphatic node cluster sites using MCNPX2.6, a well validated Monte Carlo radiation transport code. Our analysis of the calculations indicates that the S values were significantly affected by the location of the lymph node clusters and that the values increased for smaller phantoms due to the shorter inter-organ distances compared to the bigger phantoms. By testing sensitivity of S values to random sampling and voxel resolution, we confirmed that the lymph node model is reasonably stable and consistent for different random samplings and voxel resolutions.

Comparative study of feature selection with ensemble learning using SOM variants

NASA Astrophysics Data System (ADS)

Filali, Ameni; Jlassi, Chiraz; Arous, Najet

2017-03-01

Ensemble learning has succeeded in the growth of stability and clustering accuracy, but their runtime prohibits them from scaling up to real-world applications. This study deals the problem of selecting a subset of the most pertinent features for every cluster from a dataset. The proposed method is another extension of the Random Forests approach using self-organizing maps (SOM) variants to unlabeled data that estimates the out-of-bag feature importance from a set of partitions. Every partition is created using a various bootstrap sample and a random subset of the features. Then, we show that the process internal estimates are used to measure variable pertinence in Random Forests are also applicable to feature selection in unsupervised learning. This approach aims to the dimensionality reduction, visualization and cluster characterization at the same time. Hence, we provide empirical results on nineteen benchmark data sets indicating that RFS can lead to significant improvement in terms of clustering accuracy, over several state-of-the-art unsupervised methods, with a very limited subset of features. The approach proves promise to treat with very broad domains.

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

NASA Astrophysics Data System (ADS)

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.

Geographic Clustering of Underage Drinking and the Influence of Community Characteristics

PubMed Central

Reboussin, Beth A.; Preisser, John S.; Song, Eun-Young; Wolfson, Mark

2009-01-01

The aim of this paper was to examine the extent to which underage drinking clusters geographically in a sample of communities, and to investigate the manner in which community-level contexts are related to this process. We used data from a randomized community trial of underage drinking to provide the first quantitative estimates of the magnitude of the geographic clustering of underage drinking based upon pairwise odds ratios (PWORs). The Enforcing Underage Drinking Laws Randomized Community Trial provided data from repeated cross-sectional samples of youth aged 14-20 from 68 communities surveyed in 2004, 2006, and 2007 (n=18, 730). Past 30-day drinking, binge drinking, getting drunk, experiencing non-violent consequences as a result of drinking and making a purchase attempt all significantly clustered within-communities with PWORs ranging from 1.05 to 1.21. After adjustment for individual-level characteristics, results remained relatively unchanged. However, there was evidence that the magnitude of the clustering varied as a function of neighborhood disadvantage, neighborhood disorder, and family structure. Clustering of drunkenness and experiencing non-violent consequences as a result of drinking was greatest in the least economically disadvantaged and least disordered communities with the greatest percentage of married couple families. The clustering of making a purchase attempt, however, was greatest in more disordered communities, specifically the largest communities with the highest degree of residential mobility and housing density. These findings that clustering of underage drinking behaviors varies by community context has the potential for identifying the types of communities to target for underage drinking behavior-specific preventive interventions. PMID:19740611

Geographic clustering of underage drinking and the influence of community characteristics.

PubMed

Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark

2010-01-01

The aim of this paper was to examine the extent to which underage drinking clusters geographically in a sample of communities, and to investigate the manner in which community-level contexts are related to this process. We used data from a randomized community trial of underage drinking to provide the first quantitative estimates of the magnitude of the geographic clustering of underage drinking based upon pairwise odds ratios (PWORs). The Enforcing Underage Drinking Laws Randomized Community Trial provided data from repeated cross-sectional samples of youth aged 14-20 from 68 communities surveyed in 2004, 2006, and 2007 (n=18,730). Past 30-day drinking, binge drinking, getting drunk, experiencing non-violent consequences as a result of drinking and making a purchase attempt all significantly clustered within-communities with PWORs ranging from 1.05 to 1.21. After adjustment for individual-level characteristics, results remained relatively unchanged. However, there was evidence that the magnitude of the clustering varied as a function of neighborhood disadvantage, neighborhood disorder, and family structure. Clustering of drunkenness and experiencing non-violent consequences as a result of drinking was greatest in the least economically disadvantaged and least disordered communities with the greatest percentage of married-couple families. The clustering of making a purchase attempt, however, was greatest in more disordered communities, specifically the largest communities with the highest degree of residential mobility and housing density. These findings that clustering of underage drinking behaviors varies by community context has the potential for identifying the types of communities to target for underage drinking behavior-specific preventive interventions. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Intraclass Correlation Coefficients for Obesity Indicators and Energy Balance-Related Behaviors among New York City Public Elementary Schools

ERIC Educational Resources Information Center

Gray, Heewon Lee; Burgermaster, Marissa; Tipton, Elizabeth; Contento, Isobel R.; Koch, Pamela A.; Di Noia, Jennifer

2016-01-01

Objective: Sample size and statistical power calculation should consider clustering effects when schools are the unit of randomization in intervention studies. The objective of the current study was to investigate how student outcomes are clustered within schools in an obesity prevention trial. Method: Baseline data from the Food, Health &…

Unsupervised learning on scientific ocean drilling datasets from the South China Sea

NASA Astrophysics Data System (ADS)

Tse, Kevin C.; Chiu, Hon-Chim; Tsang, Man-Yin; Li, Yiliang; Lam, Edmund Y.

2018-06-01

Unsupervised learning methods were applied to explore data patterns in multivariate geophysical datasets collected from ocean floor sediment core samples coming from scientific ocean drilling in the South China Sea. Compared to studies on similar datasets, but using supervised learning methods which are designed to make predictions based on sample training data, unsupervised learning methods require no a priori information and focus only on the input data. In this study, popular unsupervised learning methods including K-means, self-organizing maps, hierarchical clustering and random forest were coupled with different distance metrics to form exploratory data clusters. The resulting data clusters were externally validated with lithologic units and geologic time scales assigned to the datasets by conventional methods. Compact and connected data clusters displayed varying degrees of correspondence with existing classification by lithologic units and geologic time scales. K-means and self-organizing maps were observed to perform better with lithologic units while random forest corresponded best with geologic time scales. This study sets a pioneering example of how unsupervised machine learning methods can be used as an automatic processing tool for the increasingly high volume of scientific ocean drilling data.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

U.S. consumer demand for restaurant calorie information: targeting demographic and behavioral segments in labeling initiatives.

PubMed

Kolodinsky, Jane; Reynolds, Travis William; Cannella, Mark; Timmons, David; Bromberg, Daniel

2009-01-01

To identify different segments of U.S. consumers based on food choices, exercise patterns, and desire for restaurant calorie labeling. Using a stratified (by region) random sample of the U.S. population, trained interviewers collected data for this cross-sectional study through telephone surveys. Center for Rural Studies U.S. national health survey. The final sample included 580 responses (22% response rate); data were weighted to be representative of age and gender characteristics of the U.S. population. Self-reported behaviors related to food choices, exercise patterns, desire for calorie information in restaurants, and sample demographics. Clusters were identified using Schwartz Bayesian criteria. Impacts of demographic characteristics on cluster membership were analyzed using bivariate tests of association and multinomial logit regression. Cluster analysis revealed three clusters based on respondents' food choices, activity levels, and desire for restaurant labeling. Two clusters, comprising three quarters of the sample, desired calorie labeling in restaurants. The remaining cluster opposed restaurant labeling. Demographic variables significantly predicting cluster membership included region of residence (p < .10), income (p < .05), gender (p < .01), and age (p < .10). Though limited by a low response and potential self-reporting bias in the phone survey, this study suggests that several groups are likely to benefit from restaurant calorie labeling. Specific demographic clusters could be targeted through labeling initiatives.

Descriptive epidemiology of typhoid fever during an epidemic in Harare, Zimbabwe, 2012.

PubMed

Polonsky, Jonathan A; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J

2014-01-01

Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range.

Descriptive Epidemiology of Typhoid Fever during an Epidemic in Harare, Zimbabwe, 2012

PubMed Central

Polonsky, Jonathan A.; Martínez-Pino, Isabel; Nackers, Fabienne; Chonzi, Prosper; Manangazira, Portia; Van Herp, Michel; Maes, Peter; Porten, Klaudia; Luquero, Francisco J.

2014-01-01

Background Typhoid fever remains a significant public health problem in developing countries. In October 2011, a typhoid fever epidemic was declared in Harare, Zimbabwe - the fourth enteric infection epidemic since 2008. To orient control activities, we described the epidemiology and spatiotemporal clustering of the epidemic in Dzivaresekwa and Kuwadzana, the two most affected suburbs of Harare. Methods A typhoid fever case-patient register was analysed to describe the epidemic. To explore clustering, we constructed a dataset comprising GPS coordinates of case-patient residences and randomly sampled residential locations (spatial controls). The scale and significance of clustering was explored with Ripley K functions. Cluster locations were determined by a random labelling technique and confirmed using Kulldorff's spatial scan statistic. Principal Findings We analysed data from 2570 confirmed and suspected case-patients, and found significant spatiotemporal clustering of typhoid fever in two non-overlapping areas, which appeared to be linked to environmental sources. Peak relative risk was more than six times greater than in areas lying outside the cluster ranges. Clusters were identified in similar geographical ranges by both random labelling and Kulldorff's spatial scan statistic. The spatial scale at which typhoid fever clustered was highly localised, with significant clustering at distances up to 4.5 km and peak levels at approximately 3.5 km. The epicentre of infection transmission shifted from one cluster to the other during the course of the epidemic. Conclusions This study demonstrated highly localised clustering of typhoid fever during an epidemic in an urban African setting, and highlights the importance of spatiotemporal analysis for making timely decisions about targetting prevention and control activities and reinforcing treatment during epidemics. This approach should be integrated into existing surveillance systems to facilitate early detection of epidemics and identify their spatial range. PMID:25486292

Serological Markers of Sand Fly Exposure to Evaluate Insecticidal Nets against Visceral Leishmaniasis in India and Nepal: A Cluster-Randomized Trial

PubMed Central

Gidwani, Kamlesh; Picado, Albert; Rijal, Suman; Singh, Shri Prakash; Roy, Lalita; Volfova, Vera; Andersen, Elisabeth Wreford; Uranw, Surendra; Ostyn, Bart; Sudarshan, Medhavi; Chakravarty, Jaya; Volf, Petr; Sundar, Shyam; Boelaert, Marleen; Rogers, Matthew Edward

2011-01-01

Background Visceral leishmaniasis is the world' second largest vector-borne parasitic killer and a neglected tropical disease, prevalent in poor communities. Long-lasting insecticidal nets (LNs) are a low cost proven vector intervention method for malaria control; however, their effectiveness against visceral leishmaniasis (VL) is unknown. This study quantified the effect of LNs on exposure to the sand fly vector of VL in India and Nepal during a two year community intervention trial. Methods As part of a paired-cluster randomized controlled clinical trial in VL-endemic regions of India and Nepal we tested the effect of LNs on sand fly biting by measuring the antibody response of subjects to the saliva of Leishmania donovani vector Phlebotomus argentipes and the sympatric (non-vector) Phlebotomus papatasi. Fifteen to 20 individuals above 15 years of age from 26 VL endemic clusters were asked to provide a blood sample at baseline, 12 and 24 months post-intervention. Results A total of 305 individuals were included in the study, 68 participants provided two blood samples and 237 gave three samples. A random effect linear regression model showed that cluster-wide distribution of LNs reduced exposure to P. argentipes by 12% at 12 months (effect 0.88; 95% CI 0.83–0.94) and 9% at 24 months (effect 0.91; 95% CI 0.80–1.02) in the intervention group compared to control adjusting for baseline values and pair. Similar results were obtained for P. papatasi. Conclusions This trial provides evidence that LNs have a limited effect on sand fly exposure in VL endemic communities in India and Nepal and supports the use of sand fly saliva antibodies as a marker to evaluate vector control interventions. PMID:21931871

Serological markers of sand fly exposure to evaluate insecticidal nets against visceral leishmaniasis in India and Nepal: a cluster-randomized trial.

PubMed

Gidwani, Kamlesh; Picado, Albert; Rijal, Suman; Singh, Shri Prakash; Roy, Lalita; Volfova, Vera; Andersen, Elisabeth Wreford; Uranw, Surendra; Ostyn, Bart; Sudarshan, Medhavi; Chakravarty, Jaya; Volf, Petr; Sundar, Shyam; Boelaert, Marleen; Rogers, Matthew Edward

2011-09-01

Visceral leishmaniasis is the world' second largest vector-borne parasitic killer and a neglected tropical disease, prevalent in poor communities. Long-lasting insecticidal nets (LNs) are a low cost proven vector intervention method for malaria control; however, their effectiveness against visceral leishmaniasis (VL) is unknown. This study quantified the effect of LNs on exposure to the sand fly vector of VL in India and Nepal during a two year community intervention trial. As part of a paired-cluster randomized controlled clinical trial in VL-endemic regions of India and Nepal we tested the effect of LNs on sand fly biting by measuring the antibody response of subjects to the saliva of Leishmania donovani vector Phlebotomus argentipes and the sympatric (non-vector) Phlebotomus papatasi. Fifteen to 20 individuals above 15 years of age from 26 VL endemic clusters were asked to provide a blood sample at baseline, 12 and 24 months post-intervention. A total of 305 individuals were included in the study, 68 participants provided two blood samples and 237 gave three samples. A random effect linear regression model showed that cluster-wide distribution of LNs reduced exposure to P. argentipes by 12% at 12 months (effect 0.88; 95% CI 0.83-0.94) and 9% at 24 months (effect 0.91; 95% CI 0.80-1.02) in the intervention group compared to control adjusting for baseline values and pair. Similar results were obtained for P. papatasi. This trial provides evidence that LNs have a limited effect on sand fly exposure in VL endemic communities in India and Nepal and supports the use of sand fly saliva antibodies as a marker to evaluate vector control interventions.

Task shifting of frontline community health workers for cardiovascular risk reduction: design and rationale of a cluster randomised controlled trial (DISHA study) in India.

PubMed

Jeemon, Panniyammakal; Narayanan, Gitanjali; Kondal, Dimple; Kahol, Kashvi; Bharadwaj, Ashok; Purty, Anil; Negi, Prakash; Ladhani, Sulaiman; Sanghvi, Jyoti; Singh, Kuldeep; Kapoor, Deksha; Sobti, Nidhi; Lall, Dorothy; Manimunda, Sathyaprakash; Dwivedi, Supriya; Toteja, Gurudyal; Prabhakaran, Dorairaj

2016-03-15

Effective task-shifting interventions targeted at reducing the global cardiovascular disease (CVD) epidemic in low and middle-income countries (LMICs) are urgently needed. DISHA is a cluster randomised controlled trial conducted across 10 sites (5 in phase 1 and 5 in phase 2) in India in 120 clusters. At each site, 12 clusters were randomly selected from a district. A cluster is defined as a small village with 250-300 households and well defined geographical boundaries. They were then randomly allocated to intervention and control clusters in a 1:1 allocation sequence. If any of the intervention and control clusters were <10 km apart, one was dropped and replaced with another randomly selected cluster from the same district. The study included a representative baseline cross-sectional survey, development of a structured intervention model, delivery of intervention for a minimum period of 18 months by trained frontline health workers (mainly Anganwadi workers and ASHA workers) and a post intervention survey in a representative sample. The study staff had no information on intervention allocation until the completion of the baseline survey. In order to ensure comparability of data across sites, the DISHA study follows a common protocol and manual of operation with standardized measurement techniques. Our study is the largest community based cluster randomised trial in low and middle-income country settings designed to test the effectiveness of 'task shifting' interventions involving frontline health workers for cardiovascular risk reduction. CTRI/2013/10/004049 . Registered 7 October 2013.

Relationships among Teachers' Self-Efficacy and Students' Motivation, Atmosphere, and Satisfaction in Physical Education

ERIC Educational Resources Information Center

Pan, Yi-Hsiang

2014-01-01

The purpose of this study was to confirm the relationships among teachers' self-efficacy, and students' learning motivation, learning atmosphere, and learning satisfaction in senior high school physical education (PE). A sample of 462 PE teachers and 2681 students was drawn using stratified random sampling and cluster sampling from high schools in…

Adaptive cluster sampling: An efficient method for assessing inconspicuous species

Treesearch

Andrea M. Silletti; Joan Walker

2003-01-01

Restorationistis typically evaluate the success of a project by estimating the population sizes of species that have been planted or seeded. Because total census is raely feasible, they must rely on sampling methods for population estimates. However, traditional random sampling designs may be inefficient for species that, for one reason or another, are challenging to...

A community-wide campaign to promote physical activity in middle-aged and elderly people: a cluster randomized controlled trial

PubMed Central

2013-01-01

Background We aimed to evaluate the effectiveness of a community-wide campaign (CWC) for promoting physical activity in middle-aged and elderly people. Methods A cluster randomized controlled trial (RCT) with a community as the unit of randomization was performed using a population-based random-sampled evaluation by self-administered questionnaires in the city of Unnan, Shimane Prefecture, Japan. The evaluation sample included 6000 residents aged 40 to 79 years. We randomly allocated nine communities to the intervention group and three to the control group. The intervention was a CWC from 2009 to 2010 to promote physical activity, and it comprised information, education, and support delivery. The primary outcome was a change in engaging in regular aerobic, flexibility, and/or muscle-strengthening activities evaluated at the individual level. Results In total, 4414 residents aged 40–79 years responded to a self-administered questionnaire (73.6% response rate). Awareness of the CWC was 79% in the intervention group. Awareness and knowledge were significantly different between the intervention and control groups, although there were no significant differences in belief and intention. The 1-year CWC did not significantly promote the recommended level of physical activity (adjusted odds ratio: 0.97; 95% confidence interval: 0.84–1.14). Conclusions This cluster RCT showed that the CWC did not promote physical activity in 1 year. Significant differences were observed in awareness and knowledge between intervention and control groups as short-term impacts of the campaign. Trial registration UMIN-CTR UMIN000002683 PMID:23570536

Forecasting the brittle failure of heterogeneous, porous geomaterials

NASA Astrophysics Data System (ADS)

Vasseur, Jérémie; Wadsworth, Fabian; Heap, Michael; Main, Ian; Lavallée, Yan; Dingwell, Donald

2017-04-01

Heterogeneity develops in magmas during ascent and is dominated by the development of crystal and importantly, bubble populations or pore-network clusters which grow, interact, localize, coalesce, outgas and resorb. Pore-scale heterogeneity is also ubiquitous in sedimentary basin fill during diagenesis. As a first step, we construct numerical simulations in 3D in which randomly generated heterogeneous and polydisperse spheres are placed in volumes and which are permitted to overlap with one another, designed to represent the random growth and interaction of bubbles in a liquid volume. We use these simulated geometries to show that statistical predictions of the inter-bubble lengthscales and evolving bubble surface area or cluster densities can be made based on fundamental percolation theory. As a second step, we take a range of well constrained random heterogeneous rock samples including sandstones, andesites, synthetic partially sintered glass bead samples, and intact glass samples and subject them to a variety of stress loading conditions at a range of temperatures until failure. We record in real time the evolution of the number of acoustic events that precede failure and show that in all scenarios, the acoustic event rate accelerates toward failure, consistent with previous findings. Applying tools designed to forecast the failure time based on these precursory signals, we constrain the absolute error on the forecast time. We find that for all sample types, the error associated with an accurate forecast of failure scales non-linearly with the lengthscale between the pore clusters in the material. Moreover, using a simple micromechanical model for the deformation of porous elastic bodies, we show that the ratio between the equilibrium sub-critical crack length emanating from the pore clusters relative to the inter-pore lengthscale, provides a scaling for the error on forecast accuracy. Thus for the first time we provide a potential quantitative correction for forecasting the failure of porous brittle solids that build the Earth's crust.

Assessing the feasibility of interrupting the transmission of soil-transmitted helminths through mass drug administration: The DeWorm3 cluster randomized trial protocol

PubMed Central

Ajjampur, Sitara S. Rao; Anderson, Roy M.; Bailey, Robin; Gardiner, Iain; Halliday, Katherine E.; Ibikounle, Moudachirou; Kalua, Khumbo; Kang, Gagandeep; Littlewood, D. Timothy J.; Luty, Adrian J. F.; Means, Arianna Rubin; Oswald, William; Pullan, Rachel L.; Sarkar, Rajiv; Schär, Fabian; Szpiro, Adam; Truscott, James E.; Werkman, Marleen; Yard, Elodie; Walson, Judd L.

2018-01-01

Current control strategies for soil-transmitted helminths (STH) emphasize morbidity control through mass drug administration (MDA) targeting preschool- and school-age children, women of childbearing age and adults in certain high-risk occupations such as agricultural laborers or miners. This strategy is effective at reducing morbidity in those treated but, without massive economic development, it is unlikely it will interrupt transmission. MDA will therefore need to continue indefinitely to maintain benefit. Mathematical models suggest that transmission interruption may be achievable through MDA alone, provided that all age groups are targeted with high coverage. The DeWorm3 Project will test the feasibility of interrupting STH transmission using biannual MDA targeting all age groups. Study sites (population ≥80,000) have been identified in Benin, Malawi and India. Each site will be divided into 40 clusters, to be randomized 1:1 to three years of twice-annual community-wide MDA or standard-of-care MDA, typically annual school-based deworming. Community-wide MDA will be delivered door-to-door, while standard-of-care MDA will be delivered according to national guidelines. The primary outcome is transmission interruption of the STH species present at each site, defined as weighted cluster-level prevalence ≤2% by quantitative polymerase chain reaction (qPCR), 24 months after the final round of MDA. Secondary outcomes include the endline prevalence of STH, overall and by species, and the endline prevalence of STH among children under five as an indicator of incident infections. Secondary analyses will identify cluster-level factors associated with transmission interruption. Prevalence will be assessed using qPCR of stool samples collected from a random sample of cluster residents at baseline, six months after the final round of MDA and 24 months post-MDA. A smaller number of individuals in each cluster will be followed with annual sampling to monitor trends in prevalence and reinfection throughout the trial. Trial registration ClinicalTrials.gov NCT03014167 PMID:29346377

ENHANCEMENT OF LEARNING ON SAMPLE SIZE CALCULATION WITH A SMARTPHONE APPLICATION: A CLUSTER-RANDOMIZED CONTROLLED TRIAL.

PubMed

Ngamjarus, Chetta; Chongsuvivatwong, Virasakdi; McNeil, Edward; Holling, Heinz

2017-01-01

Sample size determination usually is taught based on theory and is difficult to understand. Using a smartphone application to teach sample size calculation ought to be more attractive to students than using lectures only. This study compared levels of understanding of sample size calculations for research studies between participants attending a lecture only versus lecture combined with using a smartphone application to calculate sample sizes, to explore factors affecting level of post-test score after training sample size calculation, and to investigate participants’ attitude toward a sample size application. A cluster-randomized controlled trial involving a number of health institutes in Thailand was carried out from October 2014 to March 2015. A total of 673 professional participants were enrolled and randomly allocated to one of two groups, namely, 341 participants in 10 workshops to control group and 332 participants in 9 workshops to intervention group. Lectures on sample size calculation were given in the control group, while lectures using a smartphone application were supplied to the test group. Participants in the intervention group had better learning of sample size calculation (2.7 points out of maximnum 10 points, 95% CI: 24 - 2.9) than the participants in the control group (1.6 points, 95% CI: 1.4 - 1.8). Participants doing research projects had a higher post-test score than those who did not have a plan to conduct research projects (0.9 point, 95% CI: 0.5 - 1.4). The majority of the participants had a positive attitude towards the use of smartphone application for learning sample size calculation.

Actual distribution of Cronobacter spp. in industrial batches of powdered infant formula and consequences for performance of sampling strategies.

PubMed

Jongenburger, I; Reij, M W; Boer, E P J; Gorris, L G M; Zwietering, M H

2011-11-15

The actual spatial distribution of microorganisms within a batch of food influences the results of sampling for microbiological testing when this distribution is non-homogeneous. In the case of pathogens being non-homogeneously distributed, it markedly influences public health risk. This study investigated the spatial distribution of Cronobacter spp. in powdered infant formula (PIF) on industrial batch-scale for both a recalled batch as well a reference batch. Additionally, local spatial occurrence of clusters of Cronobacter cells was assessed, as well as the performance of typical sampling strategies to determine the presence of the microorganisms. The concentration of Cronobacter spp. was assessed in the course of the filling time of each batch, by taking samples of 333 g using the most probable number (MPN) enrichment technique. The occurrence of clusters of Cronobacter spp. cells was investigated by plate counting. From the recalled batch, 415 MPN samples were drawn. The expected heterogeneous distribution of Cronobacter spp. could be quantified from these samples, which showed no detectable level (detection limit of -2.52 log CFU/g) in 58% of samples, whilst in the remainder concentrations were found to be between -2.52 and 2.75 log CFU/g. The estimated average concentration in the recalled batch was -2.78 log CFU/g and a standard deviation of 1.10 log CFU/g. The estimated average concentration in the reference batch was -4.41 log CFU/g, with 99% of the 93 samples being below the detection limit. In the recalled batch, clusters of cells occurred sporadically in 8 out of 2290 samples of 1g taken. The two largest clusters contained 123 (2.09 log CFU/g) and 560 (2.75 log CFU/g) cells. Various sampling strategies were evaluated for the recalled batch. Taking more and smaller samples and keeping the total sampling weight constant, considerably improved the performance of the sampling plans to detect such a type of contaminated batch. Compared to random sampling, stratified random sampling improved the probability to detect the heterogeneous contamination. Copyright © 2011 Elsevier B.V. All rights reserved.

Epidemiology of bovine brucellosis in Costa Rica: Lessons learned from failures in the control of the disease

PubMed Central

Hernández-Mora, Gabriela; Ruiz-Villalobos, Nazareth; Bonilla-Montoya, Roberto; Romero-Zúniga, Juan-José; Jiménez-Arias, Julio; González-Barrientos, Rocío; Barquero-Calvo, Elías; Chacón-Díaz, Carlos; Rojas, Norman; Chaves-Olarte, Esteban; Guzmán-Verri, Caterina

2017-01-01

Brucellosis, caused by Brucella abortus is a major disease of cattle and a zoonosis. In order to estimate the bovine brucellosis prevalence in Costa Rica (CR), a total 765 herds (13078 bovines) from six regions of CR were randomly sampled during 2012–2013. A non-random sample of 7907 herds (532199 bovines) of the six regions, arriving for diagnoses during 2014–2016 to the Costa Rican Animal Health Service was also studied. The prevalence estimated by Rose Bengal test (RBT) ranged from 10.5%-11.4%; alternatively, the prevalence estimated by testing the RBT positives in iELISA, ranged from 4.1%-6.0%, respectively. However, cattle in CR are not vaccinated with B. abortus S19 but with RB51 (vaccination coverage close to 11%), and under these conditions the RBT displays 99% specificity and 99% sensitivity. Therefore, the RBT herd depicted in the random analysis stands as a feasible assessment and then, the recommended value in case of planning an eradication program in CR. Studies of three decades reveled that bovine brucellosis prevalence has increased in CR. B. abortus was identified by biochemical and molecular studies as the etiological agent of bovine brucellosis. Multiple locus variable-number tandem repeat analysis-16 revealed four B. abortus clusters. Cluster one and three are intertwined with isolates from other countries, while clusters two and four have only representatives from CR. Cluster one is widely distributed in all regions of the country and may be the primary B. abortus source. The other clusters seem to be restricted to specific areas in CR. The implications of our findings, in relation to the control of the disease in CR, are critically discussed. PMID:28797045

Epidemiology of bovine brucellosis in Costa Rica: Lessons learned from failures in the control of the disease.

PubMed

Hernández-Mora, Gabriela; Ruiz-Villalobos, Nazareth; Bonilla-Montoya, Roberto; Romero-Zúniga, Juan-José; Jiménez-Arias, Julio; González-Barrientos, Rocío; Barquero-Calvo, Elías; Chacón-Díaz, Carlos; Rojas, Norman; Chaves-Olarte, Esteban; Guzmán-Verri, Caterina; Moreno, Edgardo

2017-01-01

Brucellosis, caused by Brucella abortus is a major disease of cattle and a zoonosis. In order to estimate the bovine brucellosis prevalence in Costa Rica (CR), a total 765 herds (13078 bovines) from six regions of CR were randomly sampled during 2012-2013. A non-random sample of 7907 herds (532199 bovines) of the six regions, arriving for diagnoses during 2014-2016 to the Costa Rican Animal Health Service was also studied. The prevalence estimated by Rose Bengal test (RBT) ranged from 10.5%-11.4%; alternatively, the prevalence estimated by testing the RBT positives in iELISA, ranged from 4.1%-6.0%, respectively. However, cattle in CR are not vaccinated with B. abortus S19 but with RB51 (vaccination coverage close to 11%), and under these conditions the RBT displays 99% specificity and 99% sensitivity. Therefore, the RBT herd depicted in the random analysis stands as a feasible assessment and then, the recommended value in case of planning an eradication program in CR. Studies of three decades reveled that bovine brucellosis prevalence has increased in CR. B. abortus was identified by biochemical and molecular studies as the etiological agent of bovine brucellosis. Multiple locus variable-number tandem repeat analysis-16 revealed four B. abortus clusters. Cluster one and three are intertwined with isolates from other countries, while clusters two and four have only representatives from CR. Cluster one is widely distributed in all regions of the country and may be the primary B. abortus source. The other clusters seem to be restricted to specific areas in CR. The implications of our findings, in relation to the control of the disease in CR, are critically discussed.

Microfracture spacing distributions and the evolution of fracture patterns in sandstones

NASA Astrophysics Data System (ADS)

Hooker, J. N.; Laubach, S. E.; Marrett, R.

2018-03-01

Natural fracture patterns in sandstone were sampled using scanning electron microscope-based cathodoluminescence (SEM-CL) imaging. All fractures are opening-mode and are fully or partially sealed by quartz cement. Most sampled fractures are too small to be height-restricted by sedimentary layers. At very low strains (<∼0.001), fracture spatial distributions are indistinguishable from random, whereas at higher strains, fractures are generally statistically clustered. All 12 large (N > 100) datasets show spacings that are best fit by log-normal size distributions, compared to exponential, power law, or normal distributions. The clustering of fractures suggests that the locations of natural factures are not determined by a random process. To investigate natural fracture localization, we reconstructed the opening history of a cluster of fractures within the Huizachal Group in northeastern Mexico, using fluid inclusions from synkinematic cements and thermal-history constraints. The largest fracture, which is the only fracture in the cluster visible to the naked eye, among 101 present, opened relatively late in the sequence. This result suggests that the growth of sets of fractures is a self-organized process, in which small, initially isolated fractures grow and progressively interact, with preferential growth of a subset of fractures developing at the expense of growth of the rest. Size-dependent sealing of fractures within sets suggests that synkinematic cementation may contribute to fracture clustering.

Outcome-Driven Cluster Analysis with Application to Microarray Data.

PubMed

Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A

2015-01-01

One goal of cluster analysis is to sort characteristics into groups (clusters) so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes) into groups of highly correlated genes that have the same effect on the outcome (recovery). We propose a random effects model where the genes within each group (cluster) equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

Mathematics Skill of Fifteen Years Old Students in Yogyakarta in Solving Problems Like PISA

ERIC Educational Resources Information Center

Wulandari, Nidya Ferry; Jailani

2018-01-01

The aims of this research were to describe mathematics skill of 8th fifteen-year old students in Yogyakarta in solving problem of PISA. The sampling was combination of stratified and cluster random sampling. The sample consisting of 400 students was selected from fifteen schools. The data collection was by tests. The research finding revealed that…

Power Calculations for Moderators in Multi-Site Cluster Randomized Trials

ERIC Educational Resources Information Center

Spybrook, Jessaca; Kelcey, Ben; Dong, Nianbo

2016-01-01

Cluster randomized trials (CRTs), or studies in which intact groups of individuals are randomly assigned to a condition, are becoming more common in evaluation studies of educational programs. A specific type of CRT in which clusters are randomly assigned to treatment within blocks or sites, known as multisite cluster randomized trials (MSCRTs),…

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

PubMed

Smith, Jennifer L; Sturrock, Hugh J W; Olives, Casey; Solomon, Anthony W; Brooker, Simon J

2013-01-01

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 the use of a simulated approach in addressing operational research questions for trachoma but also other NTDs.

Universal-Based Prevention of Syndromal and Subsyndromal Social Anxiety: A Randomized Controlled Study

ERIC Educational Resources Information Center

Aune, Tore; Stiles, Tore C.

2009-01-01

This article reports results from a universal preventive program aimed at (a) reducing social anxiety and (b) preventing the development of syndromal social anxiety among a population-based sample of older children and young adolescents during a 1-year period. Pupils (N = 1,748) from 2 counties were cluster randomized to either an intervention or…

CLUSTERS OF TASKS PERFORMED BY WASHINGTON STATE FARM OPERATORS ENGAGED IN SEVEN TYPES OF AGRICULTURAL PRODUCTION--GRAIN, DAIRY, FORESTRY, LIVESTOCK, POULTRY, HORTICULTURE, AND GENERAL FARMING. REPORT NO. 27.

ERIC Educational Resources Information Center

LONG, GILBERT A.

THE OBJECTIVE OF THIS STUDY WAS TO OBTAIN UP-TO-DATE FACTS ABOUT CLUSTERS OF TASKS PERFORMED BY WASHINGTON STATE FARM OPERATORS ENGAGED PRIMARILY IN PRODUCING GRAIN, LIVESTOCK, DAIRY COMMODITIES, POULTRY, FOREST PRODUCTS, HORTICULTURAL COMMODITIES, AND GENERAL FARMING COMMODITIES. FROM A RANDOM SAMPLE OF 267 FARMERS REPRESENTING THOSE CATEGORIES…

[Design of the National Surveillance of Nutritional Indicators (MONIN), Peru 2007-2010].

PubMed

Campos-Sánchez, Miguel; Ricaldi-Sueldo, Rita; Miranda-Cuadros, Marianella

2011-06-01

To describe the design and methods of the national surveillance of nutritional indicators (MONIN) 2007-2010, carried out by INS/CENAN. MONIN was designed as a continuous (repeated cross-sectional) survey, with stratified multi-stage random sampling, considering the universe as all under five children and pregnant women residing in Peru, divided into 5 geographical strata and 6 trimesters (randomly permuted weeks, about 78% of the time between November 19, 2007 and April 2, 2010). The total sample was 3,827 children in 361 completed clusters. The dropout rate was 8.4% in clusters, 1.8% in houses, and 13.2% in households. Dropout was also 4.2, 13.3, 21.2, 55% and 29% in anthropometry, hemoglobin, food intake, retinol and ioduria measurements, respectively. The MONIN design is feasible and useful for the estimation of indicators of childhood malnutrition.

Impact of non-uniform correlation structure on sample size and power in multiple-period cluster randomised trials.

PubMed

Kasza, J; Hemming, K; Hooper, R; Matthews, Jns; Forbes, A B

2017-01-01

Stepped wedge and cluster randomised crossover trials are examples of cluster randomised designs conducted over multiple time periods that are being used with increasing frequency in health research. Recent systematic reviews of both of these designs indicate that the within-cluster correlation is typically taken account of in the analysis of data using a random intercept mixed model, implying a constant correlation between any two individuals in the same cluster no matter how far apart in time they are measured: within-period and between-period intra-cluster correlations are assumed to be identical. Recently proposed extensions allow the within- and between-period intra-cluster correlations to differ, although these methods require that all between-period intra-cluster correlations are identical, which may not be appropriate in all situations. Motivated by a proposed intensive care cluster randomised trial, we propose an alternative correlation structure for repeated cross-sectional multiple-period cluster randomised trials in which the between-period intra-cluster correlation is allowed to decay depending on the distance between measurements. We present results for the variance of treatment effect estimators for varying amounts of decay, investigating the consequences of the variation in decay on sample size planning for stepped wedge, cluster crossover and multiple-period parallel-arm cluster randomised trials. We also investigate the impact of assuming constant between-period intra-cluster correlations instead of decaying between-period intra-cluster correlations. Our results indicate that in certain design configurations, including the one corresponding to the proposed trial, a correlation decay can have an important impact on variances of treatment effect estimators, and hence on sample size and power. An R Shiny app allows readers to interactively explore the impact of correlation decay.

A critical analysis of high-redshift, massive, galaxy clusters. Part I

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

Hoyle, Ben; Jimenez, Raul; Verde, Licia

2012-02-01

We critically investigate current statistical tests applied to high redshift clusters of galaxies in order to test the standard cosmological model and describe their range of validity. We carefully compare a sample of high-redshift, massive, galaxy clusters with realistic Poisson sample simulations of the theoretical mass function, which include the effect of Eddington bias. We compare the observations and simulations using the following statistical tests: the distributions of ensemble and individual existence probabilities (in the > M, > z sense), the redshift distributions, and the 2d Kolmogorov-Smirnov test. Using seemingly rare clusters from Hoyle et al. (2011), and Jee etmore » al. (2011) and assuming the same survey geometry as in Jee et al. (2011, which is less conservative than Hoyle et al. 2011), we find that the ( > M, > z) existence probabilities of all clusters are fully consistent with ΛCDM. However assuming the same survey geometry, we use the 2d K-S test probability to show that the observed clusters are not consistent with being the least probable clusters from simulations at > 95% confidence, and are also not consistent with being a random selection of clusters, which may be caused by the non-trivial selection function and survey geometry. Tension can be removed if we examine only a X-ray selected sub sample, with simulations performed assuming a modified survey geometry.« less

On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

PubMed

Haneuse, Sebastien; Rivera-Rodriguez, Claudia

2018-01-01

In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

Unsupervised classification of multivariate geostatistical data: Two algorithms

NASA Astrophysics Data System (ADS)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

A Study of the Relationship between Demographic Factors and Elementary School Teacher Burnout: The Iranian Case

ERIC Educational Resources Information Center

Mazidi, Mohammad; Khoshbakht, Friba; Mahboobe, Alborzi

2017-01-01

The aim of the present study was to investigate the relationship between certain demographic factors and elementary school teachers' burnout. The sample consisted of 144 elementary school teachers (98 male and 76 women) selected through cluster random sampling. Data were collected by: (1) Personal Information Form developed by the researchers, and…

Implementation of Structured Inquiry Based Model Learning toward Students' Understanding of Geometry

ERIC Educational Resources Information Center

Salim, Kalbin; Tiawa, Dayang Hjh

2015-01-01

The purpose of this study is implementation of a structured inquiry learning model in instruction of geometry. The model used is a model with a quasi-experimental study amounted to two classes of samples selected from the population of the ten classes with cluster random sampling technique. Data collection tool consists of a test item…

A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

PubMed Central

Rolls, David A.; Wang, Peng; McBryde, Emma; Pattison, Philippa; Robins, Garry

2015-01-01

We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure. PMID:26555701

X-ray emission from a complete sample of Abell clusters of galaxies

NASA Astrophysics Data System (ADS)

Briel, Ulrich G.; Henry, J. Patrick

1993-11-01

The ROSAT All-Sky Survey (RASS) is used to investigate the X-ray properties of a complete sample of Abell clusters with measured redshifts and accurate positions. The sample comprises the 145 clusters within a 561 square degree region at high galactic latitude. The mean redshift is 0.17. This sample is especially well suited to be studied within the RASS since the mean exposure time is higher than average and the mean galactic column density is very low. These together produce a flux limit of about 4.2 x 10-13 erg/sq cm/s in the 0.5 to 2.5 keV energy band. Sixty-six (46%) individual clusters are detected at a significance level higher than 99.7% of which 7 could be chance coincidences of background or foreground sources. At redshifts greater than 0.3 six clusters out of seven (86%) are detected at the same significance level. The detected objects show a clear X-ray luminosity -- galaxy count relation with a dispersion consistent with other external estimates of the error in the counts. By analyzing the excess of positive fluctuations of the X-ray flux at the cluster positions, compared with the fluctuations of randomly drawn background fields, it is possible to extend these results below the nominal flux limit. We find 80% of richness R greater than or = 0 and 86% of R greater than or = 1 clusters are X-ray emitters with fluxes above 1 x 10-13 erg/sq cm/s. Nearly 90% of the clusters meeting the requirements to be in Abell's statistical sample emit above the same level. We therefore conclude that almost all Abell clusters are real clusters and the Abell catalog is not strongly contaminated by projection effects. We use the Kaplan-Meier product limit estimator to calculate the cumulative X-ray luminosity function. We show that the shape of the luminosity functions are similiar for different richness classes, but the characteristic luminosities of richness 2 clusters are about twice those of richness 1 clusters which are in turn about twice those of richness 0 clusters. This result is another manifestation of the luminosity -- richness elation for Abell clusters.

Analysis of genetic diversity and genome relationships of four eggplant species (Solanum melongena L) using RAPD markers

NASA Astrophysics Data System (ADS)

Susilo; Setyaningsih, M.

2018-01-01

Solanum melongena (eggplant) is one of the diversity of the Solanum family which is grown and widely spread in Indonesia and widely used by the community. This research explored the genetic diversity of four local Indonesian eggplant species namely leuca, tekokak, gelatik and kopek by using RAPD (Random Amplified Polymorphic DNA). The samples were obtained from Agricultural Technology Assessment Institute (BPTP) Bogor, Indonesia. The result of data observation was in the form of Solanum melongena plant’s DNA profile analyzed descriptively and quantitatively. 30 DNA bands (28 polymorphic and 2 monomorphic) were successfully scored by using four primers (OPF-01, OPF-02, OPF-03, and OPF-04). The Primers were used able to amplify all of the four eggplant samples. The result of PCR-RAPD visualization produces bands of 300-1500 bp. The result of cluster analysis showed the existence of three clusters (A, B, and C). Cluster A (coefficient of equal to 49%) consisted of a gelatik, cluster B (coefficient of 65% equilibrium) consisted of TPU (Kopek) and TK (Tekokak), and cluster C (55% equilibrium coefficient) consisted of LC (Leunca). These results indicated that the closest proximity is found in samples of TK (Tekokak) and TPU (Kopek).

Sampling Methods in Cardiovascular Nursing Research: An Overview.

PubMed

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.

Enumerative and binomial sequential sampling plans for the multicolored Asian lady beetle (Coleoptera: Coccinellidae) in wine grapes.

PubMed

Galvan, T L; Burkness, E C; Hutchison, W D

2007-06-01

To develop a practical integrated pest management (IPM) system for the multicolored Asian lady beetle, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), in wine grapes, we assessed the spatial distribution of H. axyridis and developed eight sampling plans to estimate adult density or infestation level in grape clusters. We used 49 data sets collected from commercial vineyards in 2004 and 2005, in Minnesota and Wisconsin. Enumerative plans were developed using two precision levels (0.10 and 0.25); the six binomial plans reflected six unique action thresholds (3, 7, 12, 18, 22, and 31% of cluster samples infested with at least one H. axyridis). The spatial distribution of H. axyridis in wine grapes was aggregated, independent of cultivar and year, but it was more randomly distributed as mean density declined. The average sample number (ASN) for each sampling plan was determined using resampling software. For research purposes, an enumerative plan with a precision level of 0.10 (SE/X) resulted in a mean ASN of 546 clusters. For IPM applications, the enumerative plan with a precision level of 0.25 resulted in a mean ASN of 180 clusters. In contrast, the binomial plans resulted in much lower ASNs and provided high probabilities of arriving at correct "treat or no-treat" decisions, making these plans more efficient for IPM applications. For a tally threshold of one adult per cluster, the operating characteristic curves for the six action thresholds provided binomial sequential sampling plans with mean ASNs of only 19-26 clusters, and probabilities of making correct decisions between 83 and 96%. The benefits of the binomial sampling plans are discussed within the context of improving IPM programs for wine grapes.

A cross-sectional, randomized cluster sample survey of household vulnerability to extreme heat among slum dwellers in ahmedabad, india.

PubMed

Tran, Kathy V; Azhar, Gulrez S; Nair, Rajesh; Knowlton, Kim; Jaiswal, Anjali; Sheffield, Perry; Mavalankar, Dileep; Hess, Jeremy

2013-06-18

Extreme heat is a significant public health concern in India; extreme heat hazards are projected to increase in frequency and severity with climate change. Few of the factors driving population heat vulnerability are documented, though poverty is a presumed risk factor. To facilitate public health preparedness, an assessment of factors affecting vulnerability among slum dwellers was conducted in summer 2011 in Ahmedabad, Gujarat, India. Indicators of heat exposure, susceptibility to heat illness, and adaptive capacity, all of which feed into heat vulnerability, was assessed through a cross-sectional household survey using randomized multistage cluster sampling. Associations between heat-related morbidity and vulnerability factors were identified using multivariate logistic regression with generalized estimating equations to account for clustering effects. Age, preexisting medical conditions, work location, and access to health information and resources were associated with self-reported heat illness. Several of these variables were unique to this study. As sociodemographics, occupational heat exposure, and access to resources were shown to increase vulnerability, future interventions (e.g., health education) might target specific populations among Ahmedabad urban slum dwellers to reduce vulnerability to extreme heat. Surveillance and evaluations of future interventions may also be worthwhile.

Cluster randomized trials utilizing primary care electronic health records: methodological issues in design, conduct, and analysis (eCRT Study).

PubMed

Gulliford, Martin C; van Staa, Tjeerd P; McDermott, Lisa; McCann, Gerard; Charlton, Judith; Dregan, Alex

2014-06-11

There is growing interest in conducting clinical and cluster randomized trials through electronic health records. This paper reports on the methodological issues identified during the implementation of two cluster randomized trials using the electronic health records of the Clinical Practice Research Datalink (CPRD). Two trials were completed in primary care: one aimed to reduce inappropriate antibiotic prescribing for acute respiratory infection; the other aimed to increase physician adherence with secondary prevention interventions after first stroke. The paper draws on documentary records and trial datasets to report on the methodological experience with respect to research ethics and research governance approval, general practice recruitment and allocation, sample size calculation and power, intervention implementation, and trial analysis. We obtained research governance approvals from more than 150 primary care organizations in England, Wales, and Scotland. There were 104 CPRD general practices recruited to the antibiotic trial and 106 to the stroke trial, with the target number of practices being recruited within six months. Interventions were installed into practice information systems remotely over the internet. The mean number of participants per practice was 5,588 in the antibiotic trial and 110 in the stroke trial, with the coefficient of variation of practice sizes being 0.53 and 0.56 respectively. Outcome measures showed substantial correlations between the 12 months before, and after intervention, with coefficients ranging from 0.42 for diastolic blood pressure to 0.91 for proportion of consultations with antibiotics prescribed, defining practice and participant eligibility for analysis requires careful consideration. Cluster randomized trials may be performed efficiently in large samples from UK general practices using the electronic health records of a primary care database. The geographical dispersal of trial sites presents a difficulty for research governance approval and intervention implementation. Pretrial data analyses should inform trial design and analysis plans. Current Controlled Trials ISRCTN 47558792 and ISRCTN 35701810 (both registered on 17 March 2010).

Cluster randomized trials utilizing primary care electronic health records: methodological issues in design, conduct, and analysis (eCRT Study)

PubMed Central

2014-01-01

Background There is growing interest in conducting clinical and cluster randomized trials through electronic health records. This paper reports on the methodological issues identified during the implementation of two cluster randomized trials using the electronic health records of the Clinical Practice Research Datalink (CPRD). Methods Two trials were completed in primary care: one aimed to reduce inappropriate antibiotic prescribing for acute respiratory infection; the other aimed to increase physician adherence with secondary prevention interventions after first stroke. The paper draws on documentary records and trial datasets to report on the methodological experience with respect to research ethics and research governance approval, general practice recruitment and allocation, sample size calculation and power, intervention implementation, and trial analysis. Results We obtained research governance approvals from more than 150 primary care organizations in England, Wales, and Scotland. There were 104 CPRD general practices recruited to the antibiotic trial and 106 to the stroke trial, with the target number of practices being recruited within six months. Interventions were installed into practice information systems remotely over the internet. The mean number of participants per practice was 5,588 in the antibiotic trial and 110 in the stroke trial, with the coefficient of variation of practice sizes being 0.53 and 0.56 respectively. Outcome measures showed substantial correlations between the 12 months before, and after intervention, with coefficients ranging from 0.42 for diastolic blood pressure to 0.91 for proportion of consultations with antibiotics prescribed, defining practice and participant eligibility for analysis requires careful consideration. Conclusions Cluster randomized trials may be performed efficiently in large samples from UK general practices using the electronic health records of a primary care database. The geographical dispersal of trial sites presents a difficulty for research governance approval and intervention implementation. Pretrial data analyses should inform trial design and analysis plans. Trial registration Current Controlled Trials ISRCTN 47558792 and ISRCTN 35701810 (both registered on 17 March 2010). PMID:24919485

The topology of large-scale structure. I - Topology and the random phase hypothesis. [galactic formation models

NASA Technical Reports Server (NTRS)

Weinberg, David H.; Gott, J. Richard, III; Melott, Adrian L.

1987-01-01

Many models for the formation of galaxies and large-scale structure assume a spectrum of random phase (Gaussian), small-amplitude density fluctuations as initial conditions. In such scenarios, the topology of the galaxy distribution on large scales relates directly to the topology of the initial density fluctuations. Here a quantitative measure of topology - the genus of contours in a smoothed density distribution - is described and applied to numerical simulations of galaxy clustering, to a variety of three-dimensional toy models, and to a volume-limited sample of the CfA redshift survey. For random phase distributions the genus of density contours exhibits a universal dependence on threshold density. The clustering simulations show that a smoothing length of 2-3 times the mass correlation length is sufficient to recover the topology of the initial fluctuations from the evolved galaxy distribution. Cold dark matter and white noise models retain a random phase topology at shorter smoothing lengths, but massive neutrino models develop a cellular topology.

Evidence based community mobilization for dengue prevention in Nicaragua and Mexico (Camino Verde, the Green Way): cluster randomized controlled trial

PubMed Central

Nava-Aguilera, Elizabeth; Arosteguí, Jorge; Morales-Perez, Arcadio; Suazo-Laguna, Harold; Legorreta-Soberanis, José; Hernandez-Alvarez, Carlos; Fernandez-Salas, Ildefonso; Paredes-Solís, Sergio; Balmaseda, Angel; Cortés-Guzmán, Antonio Juan; Serrano de los Santos, René; Coloma, Josefina; Ledogar, Robert J; Harris, Eva

2015-01-01

Objective To test whether community mobilization adds effectiveness to conventional dengue control. Design Pragmatic open label parallel group cluster randomized controlled trial. Those assessing the outcomes and analyzing the data were blinded to group assignment. Centralized computerized randomization after the baseline study allocated half the sites to intervention, stratified by country, evidence of recent dengue virus infection in children aged 3-9, and vector indices. Setting Random sample of communities in Managua, capital of Nicaragua, and three coastal regions in Guerrero State in the south of Mexico. Participants Residents in a random sample of census enumeration areas across both countries: 75 intervention and 75 control clusters (about 140 households each) were randomized and analyzed (60 clusters in Nicaragua and 90 in Mexico), including 85 182 residents in 18 838 households. Interventions A community mobilization protocol began with community discussion of baseline results. Each intervention cluster adapted the basic intervention—chemical-free prevention of mosquito reproduction—to its own circumstances. All clusters continued the government run dengue control program. Main outcome measures Primary outcomes per protocol were self reported cases of dengue, serological evidence of recent dengue virus infection, and conventional entomological indices (house index: households with larvae or pupae/households examined; container index: containers with larvae or pupae/containers examined; Breteau index: containers with larvae or pupae/households examined; and pupae per person: pupae found/number of residents). Per protocol secondary analysis examined the effect of Camino Verde in the context of temephos use. Results With cluster as the unit of analysis, serological evidence from intervention sites showed a lower risk of infection with dengue virus in children (relative risk reduction 29.5%, 95% confidence interval 3.8% to 55.3%), fewer reports of dengue illness (24.7%, 1.8% to 51.2%), fewer houses with larvae or pupae among houses visited (house index) (44.1%, 13.6% to 74.7%), fewer containers with larvae or pupae among containers examined (container index) (36.7%, 24.5% to 44.8%), fewer containers with larvae or pupae among houses visited (Breteau index) (35.1%, 16.7% to 55.5%), and fewer pupae per person (51.7%, 36.2% to 76.1%). The numbers needed to treat were 30 (95% confidence interval 20 to 59) for a lower risk of infection in children, 71 (48 to 143) for fewer reports of dengue illness, 17 (14 to 20) for the house index, 37 (35 to 67) for the container index, 10 (6 to 29) for the Breteau index, and 12 (7 to 31) for fewer pupae per person. Secondary per protocol analysis showed no serological evidence of a protective effect of temephos. Conclusions Evidence based community mobilization can add effectiveness to dengue vector control. Each site implementing the intervention in its own way has the advantage of local customization and strong community engagement. Trial registration ISRCTN27581154 PMID:26156323

Evidence based community mobilization for dengue prevention in Nicaragua and Mexico (Camino Verde, the Green Way): cluster randomized controlled trial.

PubMed

Andersson, Neil; Nava-Aguilera, Elizabeth; Arosteguí, Jorge; Morales-Perez, Arcadio; Suazo-Laguna, Harold; Legorreta-Soberanis, José; Hernandez-Alvarez, Carlos; Fernandez-Salas, Ildefonso; Paredes-Solís, Sergio; Balmaseda, Angel; Cortés-Guzmán, Antonio Juan; Serrano de Los Santos, René; Coloma, Josefina; Ledogar, Robert J; Harris, Eva

2015-07-08

To test whether community mobilization adds effectiveness to conventional dengue control. Pragmatic open label parallel group cluster randomized controlled trial. Those assessing the outcomes and analyzing the data were blinded to group assignment. Centralized computerized randomization after the baseline study allocated half the sites to intervention, stratified by country, evidence of recent dengue virus infection in children aged 3-9, and vector indices. Random sample of communities in Managua, capital of Nicaragua, and three coastal regions in Guerrero State in the south of Mexico. Residents in a random sample of census enumeration areas across both countries: 75 intervention and 75 control clusters (about 140 households each) were randomized and analyzed (60 clusters in Nicaragua and 90 in Mexico), including 85,182 residents in 18,838 households. A community mobilization protocol began with community discussion of baseline results. Each intervention cluster adapted the basic intervention-chemical-free prevention of mosquito reproduction-to its own circumstances. All clusters continued the government run dengue control program. Primary outcomes per protocol were self reported cases of dengue, serological evidence of recent dengue virus infection, and conventional entomological indices (house index: households with larvae or pupae/households examined; container index: containers with larvae or pupae/containers examined; Breteau index: containers with larvae or pupae/households examined; and pupae per person: pupae found/number of residents). Per protocol secondary analysis examined the effect of Camino Verde in the context of temephos use. With cluster as the unit of analysis, serological evidence from intervention sites showed a lower risk of infection with dengue virus in children (relative risk reduction 29.5%, 95% confidence interval 3.8% to 55.3%), fewer reports of dengue illness (24.7%, 1.8% to 51.2%), fewer houses with larvae or pupae among houses visited (house index) (44.1%, 13.6% to 74.7%), fewer containers with larvae or pupae among containers examined (container index) (36.7%, 24.5% to 44.8%), fewer containers with larvae or pupae among houses visited (Breteau index) (35.1%, 16.7% to 55.5%), and fewer pupae per person (51.7%, 36.2% to 76.1%). The numbers needed to treat were 30 (95% confidence interval 20 to 59) for a lower risk of infection in children, 71 (48 to 143) for fewer reports of dengue illness, 17 (14 to 20) for the house index, 37 (35 to 67) for the container index, 10 (6 to 29) for the Breteau index, and 12 (7 to 31) for fewer pupae per person. Secondary per protocol analysis showed no serological evidence of a protective effect of temephos. Evidence based community mobilization can add effectiveness to dengue vector control. Each site implementing the intervention in its own way has the advantage of local customization and strong community engagement. ISRCTN27581154. © Andersson et al 2015.

Use of LANDSAT imagery for wildlife habitat mapping in northeast and east central Alaska

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Two scenes were analyzed by applying an iterative cluster analysis to a 2% random data sample and then using the resulting clusters as a training set basis for maximum likelihood classification. Twenty-six and twenty-seven categorical classes, respectively resulted from this process. The majority of classes in each case were quite specific vegetation types; each of these types has specific value as moose habitat.

How Professionalized Is College Teaching? Norms and the Ideal of Service. ASHE Annual Meeting Paper.

ERIC Educational Resources Information Center

Braxton, John M.; Bayer, Alan E.

This study examined the behavioral expectations and norms for college and university faculty particularly whether they varied with respect to the level of commitment to teaching at different institutions and in different disciplines. A cluster sampling design was used to select a random sample of the population of faculty in biology, history,…

How Much Videos Win over Audios in Listening Instruction for EFL Learners

ERIC Educational Resources Information Center

Yasin, Burhanuddin; Mustafa, Faisal; Permatasari, Rizki

2017-01-01

This study aims at comparing the benefits of using videos instead of audios for improving students' listening skills. This experimental study used a pre-test and post-test control group design. The sample, selected by cluster random sampling resulted in the selection of 32 second year high school students for each group. The instruments used were…

The Role of Socio-Cognitive Variables in Predicting Learning Satisfaction in Smart Schools

ERIC Educational Resources Information Center

Firoozi, Mohammad Reza; Kazemi, Ali; Jokar, Maryam

2017-01-01

The present study aimed to investigate the role of Socio-Cognitive variables in predicting learning satisfaction in Smart Schools. The population was all the primary school students studying in smart schools in the city of Shiraz in the school year 2014-2015. The sample, randomly chosen through multi-stage cluster sampling, was 383 primary school…

Random whole metagenomic sequencing for forensic discrimination of soils.

PubMed

Khodakova, Anastasia S; Smith, Renee J; Burgoyne, Leigh; Abarno, Damien; Linacre, Adrian

2014-01-01

Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

Sampling procedures for throughfall monitoring: A simulation study

NASA Astrophysics Data System (ADS)

Zimmermann, Beate; Zimmermann, Alexander; Lark, Richard Murray; Elsenbeer, Helmut

2010-01-01

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.

Finding SDSS Galaxy Clusters in 4-dimensional Color Space Using the False Discovery Rate

NASA Astrophysics Data System (ADS)

Nichol, R. C.; Miller, C. J.; Reichart, D.; Wasserman, L.; Genovese, C.; SDSS Collaboration

2000-12-01

We describe a recently developed statistical technique that provides a meaningful cut-off in probability-based decision making. We are concerned with multiple testing, where each test produces a well-defined probability (or p-value). By well-known, we mean that the null hypothesis used to determine the p-value is fully understood and appropriate. The method is entitled False Discovery Rate (FDR) and its largest advantage over other measures is that it allows one to specify a maximal amount of acceptable error. As an example of this tool, we apply FDR to a four-dimensional clustering algorithm using SDSS data. For each galaxy (or test galaxy), we count the number of neighbors that fit within one standard deviation of a four dimensional Gaussian centered on that test galaxy. The mean and standard deviation of that Gaussian are determined from the colors and errors of the test galaxy. We then take that same Gaussian and place it on a random selection of n galaxies and make a similar count. In the limit of large n, we expect the median count around these random galaxies to represent a typical field galaxy. For every test galaxy we determine the probability (or p-value) that it is a field galaxy based on these counts. A low p-value implies that the test galaxy is in a cluster environment. Once we have a p-value for every galaxy, we use FDR to determine at what level we should make our probability cut-off. Once this cut-off is made, we have a final sample of galaxies that are cluster-like galaxies. Using FDR, we also know the maximum amount of field contamination in our cluster galaxy sample. We present our preliminary galaxy clustering results using these methods.

Study protocol for a cluster randomized trial of the Community of Voices choir intervention to promote the health and well-being of diverse older adults.

PubMed

Johnson, Julene K; Nápoles, Anna M; Stewart, Anita L; Max, Wendy B; Santoyo-Olsson, Jasmine; Freyre, Rachel; Allison, Theresa A; Gregorich, Steven E

2015-10-13

Older adults are the fastest growing segment of the United States population. There is an immediate need to identify novel, cost-effective community-based approaches that promote health and well-being for older adults, particularly those from diverse racial/ethnic and socioeconomic backgrounds. Because choral singing is multi-modal (requires cognitive, physical, and psychosocial engagement), it has the potential to improve health outcomes across several dimensions to help older adults remain active and independent. The purpose of this study is to examine the effect of a community choir program (Community of Voices) on health and well-being and to examine its costs and cost-effectiveness in a large sample of diverse, community-dwelling older adults. In this cluster randomized controlled trial, diverse adults age 60 and older were enrolled at Administration on Aging-supported senior centers and completed baseline assessments. The senior centers were randomly assigned to either start the choir immediately (intervention group) or wait 6 months to start (control). Community of Voices is a culturally tailored choir program delivered at the senior centers by professional music conductors that reflects three components of engagement (cognitive, physical, and psychosocial). We describe the nature of the study including the cluster randomized trial study design, sampling frame, sample size calculation, methods of recruitment and assessment, and primary and secondary outcomes. The study involves conducting a randomized trial of an intervention as delivered in "real-world" settings. The choir program was designed using a novel translational approach that integrated evidence-based research on the benefits of singing for older adults, community best practices related to community choirs for older adults, and the perspective of the participating communities. The practicality and relatively low cost of the choir intervention means it can be incorporated into a variety of community settings and adapted to diverse cultures and languages. If successful, this program will be a practical and acceptable community-based approach for promoting health and well-being of older adults. ClinicalTrials.gov NCT01869179 registered 9 January 2013.

A Comparison of Seventh Grade Thai Students' Reading Comprehension and Motivation to Read English through Applied Instruction Based on the Genre-Based Approach and the Teacher's Manual

ERIC Educational Resources Information Center

Sawangsamutchai, Yutthasak; Rattanavich, Saowalak

2016-01-01

The objective of this research is to compare the English reading comprehension and motivation to read of seventh grade Thai students taught with applied instruction through the genre-based approach and teachers' manual. A randomized pre-test post-test control group design was used through the cluster random sampling technique. The data were…

Effects of a Worksite Tobacco Control Intervention in India: The Mumbai Worksite Tobacco Control Study, a Cluster Randomized Trial

PubMed Central

Sorensen, Glorian; Pednekar, Mangesh; Cordeira, Laura Shulman; Pawar, Pratibha; Nagler, Eve; Stoddard, Anne M.; Kim, Hae-Young; Gupta, Prakash C.

2016-01-01

Objectives We assessed a worksite intervention designed to promote tobacco control among manufacturing workers in Greater Mumbai, India. Methods We used a cluster-randomized design to test an integrated health promotion/health protection intervention, which addressed changes at the management and worker levels. Between July 2012 and July 2013, we recruited 20 worksites on a rolling basis and randomly assigned them to intervention or delayed-intervention control conditions. The follow-up survey was conducted between December 2013 and November 2014. Results The difference in 30-day quit rates between intervention and control conditions was statistically significant for production workers (OR=2.25, P=0.03), although not for the overall sample (OR=1.70; P=0.12). The intervention resulted in a doubling of the 6-month cessation rates among workers in the intervention worksites compared to those in the control, for production workers (OR=2.29; P=0.07) and for the overall sample (OR=1.81; P=0.13), but the difference did not reach statistical significance. Conclusions These findings demonstrate the potential impact of a tobacco control intervention that combined tobacco control and health protection programming within Indian manufacturing worksites. PMID:26883793

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Coarse Point Cloud Registration by Egi Matching of Voxel Clusters

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Shen, Yueqian; Menenti, Massimo

2016-06-01

Laser scanning samples the surface geometry of objects efficiently and records versatile information as point clouds. However, often more scans are required to fully cover a scene. Therefore, a registration step is required that transforms the different scans into a common coordinate system. The registration of point clouds is usually conducted in two steps, i.e. coarse registration followed by fine registration. In this study an automatic marker-free coarse registration method for pair-wise scans is presented. First the two input point clouds are re-sampled as voxels and dimensionality features of the voxels are determined by principal component analysis (PCA). Then voxel cells with the same dimensionality are clustered. Next, the Extended Gaussian Image (EGI) descriptor of those voxel clusters are constructed using significant eigenvectors of each voxel in the cluster. Correspondences between clusters in source and target data are obtained according to the similarity between their EGI descriptors. The random sampling consensus (RANSAC) algorithm is employed to remove outlying correspondences until a coarse alignment is obtained. If necessary, a fine registration is performed in a final step. This new method is illustrated on scan data sampling two indoor scenarios. The results of the tests are evaluated by computing the point to point distance between the two input point clouds. The presented two tests resulted in mean distances of 7.6 mm and 9.5 mm respectively, which are adequate for fine registration.

Cluster glass induced exchange biaslike effect in the perovskite cobaltites

NASA Astrophysics Data System (ADS)

Luo, Wanju; Wang, Fangwei

2007-04-01

Exchange biaslike phenomenon is observed in the Ba doped perovskite polycrystalline LaCoO3. The magnetic hysteresis loop shifts in both horizontal and vertical directions at 5K when the samples are cooled down to 5K in a magnetic field. The nature of this magnetic anisotropy is ascribed to the freezing properties of the local anisotropy in the cluster glass system. The magnetic shifts in horizontal and vertical directions can be derived directly under the principle that the spins of a cluster are frozen in random orientations and aligned to the field direction upon zero field and field cooling, respectively.

Identifying seizure clusters in patients with psychogenic nonepileptic seizures.

PubMed

Baird, Grayson L; Harlow, Lisa L; Machan, Jason T; Thomas, Dave; LaFrance, W C

2017-08-01

The present study explored how seizure clusters may be defined for those with psychogenic nonepileptic seizures (PNES), a topic for which there is a paucity of literature. The sample was drawn from a multisite randomized clinical trial for PNES; seizure data are from participants' seizure diaries. Three possible cluster definitions were examined: 1) common clinical definition, where ≥3 seizures in a day is considered a cluster, along with two novel statistical definitions, where ≥3 seizures in a day are considered a cluster if the observed number of seizures statistically exceeds what would be expected relative to a patient's: 1) average seizure rate prior to the trial, 2) observed seizure rate for the previous seven days. Prevalence of clusters was 62-68% depending on cluster definition used, and occurrence rate of clusters was 6-19% depending on cluster definition. Based on these data, clusters seem to be common in patients with PNES, and more research is needed to identify if clusters are related to triggers and outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

CLUMP-3D: Testing ΛCDM with Galaxy Cluster Shapes

NASA Astrophysics Data System (ADS)

Sereno, Mauro; Umetsu, Keiichi; Ettori, Stefano; Sayers, Jack; Chiu, I.-Non; Meneghetti, Massimo; Vega-Ferrero, Jesús; Zitrin, Adi

2018-06-01

The ΛCDM model of structure formation makes strong predictions on the concentration and shape of dark matter (DM) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a geometric test of the ΛCDM model. Accurate and precise measurements needs a full three-dimensional (3D) analysis of the cluster mass distribution. We accomplish this with a multi-probe 3D analysis of the X-ray regular Cluster Lensing and Supernova survey with Hubble (CLASH) clusters combining strong and weak lensing, X-ray photometry and spectroscopy, and the Sunyaev–Zel’dovich effect (SZe). The cluster shapes and concentrations are consistent with ΛCDM predictions. The CLASH clusters are randomly oriented, as expected given the sample selection criteria. Shapes agree with numerical results for DM-only halos, which hints at baryonic physics being less effective in making halos rounder.

Biased phylodynamic inferences from analysing clusters of viral sequences

PubMed Central

Xiang, Fei; Frost, Simon D. W.

2017-01-01

Abstract Phylogenetic methods are being increasingly used to help understand the transmission dynamics of measurably evolving viruses, including HIV. Clusters of highly similar sequences are often observed, which appear to follow a ‘power law’ behaviour, with a small number of very large clusters. These clusters may help to identify subpopulations in an epidemic, and inform where intervention strategies should be implemented. However, clustering of samples does not necessarily imply the presence of a subpopulation with high transmission rates, as groups of closely related viruses can also occur due to non-epidemiological effects such as over-sampling. It is important to ensure that observed phylogenetic clustering reflects true heterogeneity in the transmitting population, and is not being driven by non-epidemiological effects. We qualify the effect of using a falsely identified ‘transmission cluster’ of sequences to estimate phylodynamic parameters including the effective population size and exponential growth rate under several demographic scenarios. Our simulation studies show that taking the maximum size cluster to re-estimate parameters from trees simulated under a randomly mixing, constant population size coalescent process systematically underestimates the overall effective population size. In addition, the transmission cluster wrongly resembles an exponential or logistic growth model 99% of the time. We also illustrate the consequences of false clusters in exponentially growing coalescent and birth-death trees, where again, the growth rate is skewed upwards. This has clear implications for identifying clusters in large viral databases, where a false cluster could result in wasted intervention resources. PMID:28852573

The need of adequate information to achieve total compliance of mass drug administration in Pekalongan

NASA Astrophysics Data System (ADS)

Ginandjar, Praba; Saraswati, Lintang Dian; Taufik, Opik; Nurjazuli; Widjanarko, Bagoes

2017-02-01

World Health Organization (WHO) initiated The Global Program to Eliminate Lymphatic Filariasis (LF) through mass drug administration (MDA). Pekalongan started MDA in 2011. Yet the LF prevalence in 2015 remained exceed the threshold (1%). This study aimed to describe the inhibiting factors related to the compliance of MDA in community level. This was a rapid survey with cross sectional approach. A two-stages random sampling was used in this study. In the first stage, 25 clusters were randomly selected from 27 villages with proportionate to population size (PPS) methods (C-Survey). In the second stage, 10 subjects were randomly selected from each cluster. Subject consisted of 250 respondents from 25 selected clusters. Variables consisted of MDA coverage, practice of taking medication during MDA, enabling and inhibiting factors to MDA in community level. The results showed most respondents had poor knowledge on filariasis, which influence awareness of the disease. Health-illness perception, did not receive the drugs, lactation, side effect, and size of the drugs were dominant factors of non-compliance to MDA. MDA information and community empowerment were needed to improve MDA coverage. Further study to explore the appropriate model of socialization will support the success of MDA program

Nanoclusters first: a hierarchical phase transformation in a novel Mg alloy

NASA Astrophysics Data System (ADS)

Okuda, Hiroshi; Yamasaki, Michiaki; Kawamura, Yoshihito; Tabuchi, Masao; Kimizuka, Hajime

2015-09-01

The Mg-Y-Zn ternary alloy system contains a series of novel structures known as long-period stacking ordered (LPSO) structures. The formation process and its key concept from a viewpoint of phase transition are not yet clear. The current study reveals that the phase transformation process is not a traditional spinodal decomposition or structural transformation but, rather a novel hierarchical phase transformation. In this transformation, clustering occurs first, and the spatial rearrangement of the clusters induce a secondary phase transformation that eventually lead to two-dimensional ordering of the clusters. The formation process was examined using in situ synchrotron radiation small-angle X-ray scattering (SAXS). Rapid quenching from liquid alloy into thin ribbons yielded strongly supersaturated amorphous samples. The samples were heated at a constant rate of 10 K/min. and the scattering patterns were acquired. The SAXS analysis indicated that small clusters grew to sizes of 0.2 nm after they crystallized. The clusters distributed randomly in space grew and eventually transformed into a microstructure with two well-defined cluster-cluster distances, one for the segregation periodicity of LPSO and the other for the in-plane ordering in segregated layer. This transformation into the LPSO structure concomitantly introduces the periodical stacking fault required for the 18R structures.

American Healthy Homes Survey: A National Study of Residential Phthalates Measured from Floor Wipes

EPA Science Inventory

The United States Environmental Protection Agency (U.S. EPA), in collaboration with the U.S. Department of Housing and Urban Development (HUD), conducted a survey measuring phthalates in randomly selected residential homes throughout the U.S. Multistage sampling with clustering w...

Measuring Clinical Decision Support Influence on Evidence-Based Nursing Practice.

PubMed

Cortez, Susan; Dietrich, Mary S; Wells, Nancy

2016-07-01

To measure the effect of clinical decision support (CDS) on oncology nurse evidence-based practice (EBP).
. Longitudinal cluster-randomized design.
. Four distinctly separate oncology clinics associated with an academic medical center.
. The study sample was comprised of randomly selected data elements from the nursing documentation software. The data elements were patient-reported symptoms and the associated nurse interventions. The total sample observations were 600, derived from a baseline, posteducation, and postintervention sample of 200 each (100 in the intervention group and 100 in the control group for each sample).
. The cluster design was used to support randomization of the study intervention at the clinic level rather than the individual participant level to reduce possible diffusion of the study intervention. An elongated data collection cycle (11 weeks) controlled for temporary increases in nurse EBP related to the education or CDS intervention.
. The dependent variable was the nurse evidence-based documentation rate, calculated from the nurse-documented interventions. The independent variable was the CDS added to the nursing documentation software.
. The average EBP rate at baseline for the control and intervention groups was 27%. After education, the average EBP rate increased to 37%, and then decreased to 26% in the postintervention sample. Mixed-model linear statistical analysis revealed no significant interaction of group by sample. The CDS intervention did not result in an increase in nurse EBP.
. EBP education increased nurse EBP documentation rates significantly but only temporarily. Nurses may have used evidence in practice but may not have documented their interventions.
. More research is needed to understand the complex relationship between CDS, nursing practice, and nursing EBP intervention documentation. CDS may have a different effect on nurse EBP, physician EBP, and other medical professional EBP.

Sample design effects in landscape genetics

USGS Publications Warehouse

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.

Cognitive-behavioral conjoint therapy for PTSD improves various PTSD symptoms and trauma-related cognitions: Results from a randomized controlled trial.

PubMed

Macdonald, Alexandra; Pukay-Martin, Nicole D; Wagner, Anne C; Fredman, Steffany J; Monson, Candice M

2016-02-01

Numerous studies document an association between posttraumatic stress disorder (PTSD) and impairments in intimate relationship functioning, and there is evidence that PTSD symptoms and associated impairments are improved by cognitive-behavioral conjoint therapy for PTSD (CBCT for PTSD; Monson & Fredman, 2012). The present study investigated changes across treatment in clinician-rated PTSD symptom clusters and patient-rated trauma-related cognitions in a randomized controlled trial comparing CBCT for PTSD with waitlist in a sample of 40 individuals with PTSD and their partners (N = 40; Monson et al., 2012). Compared with waitlist, patients who received CBCT for PTSD immediately demonstrated greater improvements in all PTSD symptom clusters, trauma-related beliefs, and guilt cognitions (Hedge's gs -.33 to -1.51). Results suggest that CBCT for PTSD improves all PTSD symptom clusters and trauma-related cognitions among individuals with PTSD and further supports the value of utilizing a couple-based approach to the treatment of PTSD. (c) 2016 APA, all rights reserved).

Percolation of the site random-cluster model by Monte Carlo method

NASA Astrophysics Data System (ADS)

Wang, Songsong; Zhang, Wanzhou; Ding, Chengxiang

2015-08-01

We propose a site random-cluster model by introducing an additional cluster weight in the partition function of the traditional site percolation. To simulate the model on a square lattice, we combine the color-assignation and the Swendsen-Wang methods to design a highly efficient cluster algorithm with a small critical slowing-down phenomenon. To verify whether or not it is consistent with the bond random-cluster model, we measure several quantities, such as the wrapping probability Re, the percolating cluster density P∞, and the magnetic susceptibility per site χp, as well as two exponents, such as the thermal exponent yt and the fractal dimension yh of the percolating cluster. We find that for different exponents of cluster weight q =1.5 , 2, 2.5 , 3, 3.5 , and 4, the numerical estimation of the exponents yt and yh are consistent with the theoretical values. The universalities of the site random-cluster model and the bond random-cluster model are completely identical. For larger values of q , we find obvious signatures of the first-order percolation transition by the histograms and the hysteresis loops of percolating cluster density and the energy per site. Our results are helpful for the understanding of the percolation of traditional statistical models.

Effect Sizes in Cluster-Randomized Designs

ERIC Educational Resources Information Center

Hedges, Larry V.

2007-01-01

Multisite research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Researchers would like to compute effect size indexes based on the standardized mean difference to compare the results of cluster-randomized studies (and corresponding quasi-experiments) with other studies and to…

Point process statistics in atom probe tomography.

PubMed

Philippe, T; Duguay, S; Grancher, G; Blavette, D

2013-09-01

We present a review of spatial point processes as statistical models that we have designed for the analysis and treatment of atom probe tomography (APT) data. As a major advantage, these methods do not require sampling. The mean distance to nearest neighbour is an attractive approach to exhibit a non-random atomic distribution. A χ(2) test based on distance distributions to nearest neighbour has been developed to detect deviation from randomness. Best-fit methods based on first nearest neighbour distance (1 NN method) and pair correlation function are presented and compared to assess the chemical composition of tiny clusters. Delaunay tessellation for cluster selection has been also illustrated. These statistical tools have been applied to APT experiments on microelectronics materials. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed

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.

The Co-Occurrence of Childhood Sexual Abuse, Adult Sexual Assault, Intimate Partner Violence, and Sexual Harassment: A Mediational Model of Posttraumatic Stress Disorder and Physical Health Outcomes

ERIC Educational Resources Information Center

Campbell, Rebecca; Greeson, Megan R.; Bybee, Deborah; Raja, Sheela

2008-01-01

This study examined the co-occurrence of childhood sexual abuse, adult sexual assault, intimate partner violence, and sexual harassment in a predominantly African American sample of 268 female veterans, randomly sampled from an urban Veterans Affairs hospital women's clinic. A combination of hierarchical and iterative cluster analysis was used to…

Physical Activity among Older People Living Alone in Shanghai, China

ERIC Educational Resources Information Center

Chen, Yu; While, Alison E; Hicks, Allan

2015-01-01

Objective: To investigate physical activity among older people living alone in Shanghai, People's Republic of China, and key factors contributing to their physical activity. Methods: A cross-sectional questionnaire survey was administered in nine communities in Shanghai, using a stratified random cluster sample: 521 community-dwelling older people…

Mathematical Intelligence and Mathematical Creativity: A Causal Relationship

ERIC Educational Resources Information Center

Tyagi, Tarun Kumar

2017-01-01

This study investigated the causal relationship between mathematical creativity and mathematical intelligence. Four hundred thirty-nine 8th-grade students, age ranged from 11 to 14 years, were included in the sample of this study by random cluster technique on which mathematical creativity and Hindi adaptation of mathematical intelligence test…

Multimorbidity and patterns of chronic conditions in a primary care population in Switzerland: a cross-sectional study

PubMed Central

Déruaz-Luyet, Anouk; N'Goran, A Alexandra; Senn, Nicolas; Bodenmann, Patrick; Pasquier, Jérôme; Widmer, Daniel; Tandjung, Ryan; Rosemann, Thomas; Frey, Peter; Streit, Sven; Zeller, Andreas; Excoffier, Sophie; Burnand, Bernard; Herzig, Lilli

2017-01-01

Objective To characterise in details a random sample of multimorbid patients in Switzerland and to evaluate the clustering of chronic conditions in that sample. Methods 100 general practitioners (GPs) each enrolled 10 randomly selected multimorbid patients aged ≥18 years old and suffering from at least three chronic conditions. The prevalence of 75 separate chronic conditions from the International Classification of Primary Care-2 (ICPC-2) was evaluated in these patients. Clusters of chronic conditions were studied in parallel. Results The final database included 888 patients. Mean (SD) patient age was 73.0 (12.0) years old. They suffered from 5.5 (2.2) chronic conditions and were prescribed 7.7 (3.5) drugs; 25.7% suffered from depression. Psychological conditions were more prevalent among younger individuals (≤66 years old). Cluster analysis of chronic conditions with a prevalence ≥5% in the sample revealed four main groups of conditions: (1) cardiovascular risk factors and conditions, (2) general age-related and metabolic conditions, (3) tobacco and alcohol dependencies, and (4) pain, musculoskeletal and psychological conditions. Conclusion Given the emerging epidemic of multimorbidity in industrialised countries, accurately depicting the multiple expressions of multimorbidity in family practices’ patients is a high priority. Indeed, even in a setting where patients have direct access to medical specialists, GPs nevertheless retain a key role as coordinators and often as the sole medical reference for multimorbid patients. PMID:28674127

Multilevel covariance regression with correlated random effects in the mean and variance structure.

PubMed

Quintero, Adrian; Lesaffre, Emmanuel

2017-09-01

Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design and simulation study of the immunization Data Quality Audit (DQA).

PubMed

Woodard, Stacy; Archer, Linda; Zell, Elizabeth; Ronveaux, Olivier; Birmingham, Maureen

2007-08-01

The goal of the Data Quality Audit (DQA) is to assess whether the Global Alliance for Vaccines and Immunization-funded countries are adequately reporting the number of diphtheria-tetanus-pertussis immunizations given, on which the "shares" are awarded. Given that this sampling design is a modified two-stage cluster sample (modified because a stratified, rather than a simple, random sample of health facilities is obtained from the selected clusters); the formula for the calculation of the standard error for the estimate is unknown. An approximated standard error has been proposed, and the first goal of this simulation is to assess the accuracy of the standard error. Results from the simulations based on hypothetical populations were found not to be representative of the actual DQAs that were conducted. Additional simulations were then conducted on the actual DQA data to better access the precision of the DQ with both the original and the increased sample sizes.

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes.

PubMed

Chang, Max W; Belew, Richard K; Carroll, Kate S; Olson, Arthur J; Goodsell, David S

2008-08-01

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments. 2008 Wiley Periodicals, Inc.

Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

NASA Astrophysics Data System (ADS)

Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

2017-04-01

The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE <0.020 m3 m-3) than these based on EFs (-PCA) and Theta (-PCA). The sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K-means method (EFsTheta-PCA). Overall, TS required only one site, but its accuracy was limited. The best K-means method required <8 sites and yielded high accuracy, but extra soil and terrain information is necessary when using this method. The stratified sampling strategy can only be used if no pre-knowledge about soil moisture variation is available. This information will help in selecting the optimal methods for estimation the area mean soil moisture.

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

PubMed

Schramm, Catherine; Vial, Céline; Bachoud-Lévi, Anne-Catherine; Katsahian, Sandrine

2018-01-01

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials

ERIC Educational Resources Information Center

Sanders, Elizabeth A.

2011-01-01

This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…

On the limiting characteristics of quantum random number generators at various clusterings of photocounts

NASA Astrophysics Data System (ADS)

Molotkov, S. N.

2017-03-01

Various methods for the clustering of photocounts constituting a sequence of random numbers are considered. It is shown that the clustering of photocounts resulting in the Fermi-Dirac distribution makes it possible to achieve the theoretical limit of the random number generation rate.

Cluster randomization and political philosophy.

PubMed

Chwang, Eric

2012-11-01

In this paper, I will argue that, while the ethical issues raised by cluster randomization can be challenging, they are not new. My thesis divides neatly into two parts. In the first, easier part I argue that many of the ethical challenges posed by cluster randomized human subjects research are clearly present in other types of human subjects research, and so are not novel. In the second, more difficult part I discuss the thorniest ethical challenge for cluster randomized research--cases where consent is genuinely impractical to obtain. I argue that once again these cases require no new analytic insight; instead, we should look to political philosophy for guidance. In other words, the most serious ethical problem that arises in cluster randomized research also arises in political philosophy. © 2011 Blackwell Publishing Ltd.

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.

Social network recruitment for Yo Puedo: an innovative sexual health intervention in an underserved urban neighborhood—sample and design implications.

PubMed

Minnis, Alexandra M; vanDommelen-Gonzalez, Evan; Luecke, Ellen; Cheng, Helen; Dow, William; Bautista-Arredondo, Sergio; Padian, Nancy S

2015-02-01

Most existing evidence-based sexual health interventions focus on individual-level behavior, even though there is substantial evidence that highlights the influential role of social environments in shaping adolescents' behaviors and reproductive health outcomes. We developed Yo Puedo, a combined conditional cash transfer and life skills intervention for youth to promote educational attainment, job training, and reproductive health wellness that we then evaluated for feasibility among 162 youth aged 16-21 years in a predominantly Latino community in San Francisco, CA. The intervention targeted youth's social networks and involved recruitment and randomization of small social network clusters. In this paper we describe the design of the feasibility study and report participants' baseline characteristics. Furthermore, we examined the sample and design implications of recruiting social network clusters as the unit of randomization. Baseline data provide evidence that we successfully enrolled high risk youth using a social network recruitment approach in community and school-based settings. Nearly all participants (95%) were high risk for adverse educational and reproductive health outcomes based on multiple measures of low socioeconomic status (81%) and/or reported high risk behaviors (e.g., gang affiliation, past pregnancy, recent unprotected sex, frequent substance use; 62%). We achieved variability in the study sample through heterogeneity in recruitment of the index participants, whereas the individuals within the small social networks of close friends demonstrated substantial homogeneity across sociodemographic and risk profile characteristics. Social networks recruitment was feasible and yielded a sample of high risk youth willing to enroll in a randomized study to evaluate a novel sexual health intervention.

Isonymy structure of four Venezuelan states.

PubMed

Rodríguez-Larralde, A; Barrai, I; Alfonzo, J C

1993-01-01

The isonymy structure of four Venezuelan States-Falcón, Mérida, Nueva Esparta and Yaracuy-was studied using the surnames of the Venezuelan register of electors updated in 1984. The surname distributions of 155 counties were obtained and, for each county, estimates of consanguinity due to random isonymy and Fisher's alpha were calculated. It was shown that for large sample sizes the inverse of Fisher's alpha is identical to the unbiased estimate of within-population random isonymy. A three-dimensional isometric surface plot was obtained for each State, based on the counties' random isonymy estimates. The highest estimates of random consanguinity were found in the States of Nueva Esparta and Mérida, while the lowest were found in Yaracuy. Other microdifferentiation indicators from the same data gave similar results, and an interpretation was attempted, based on the particular economic and geographic characteristics of each State. Four different genetic distances between all possible pairs of counties were calculated within States; geographic distance shows the highest correlations with random isonymy and Euclidean distance, with the exception of the State of Nueva Esparta, where there is no correlation between geographic distance and random isonymy. It was possible to group counties in clusters, from dendrograms based on Euclidean distance. Isonymy clustering was also consistent with socioeconomic and geographic characteristics of the counties.

A Clustered Randomized Controlled Trial of the Positive Prevention PLUS Adolescent Pregnancy Prevention Program.

PubMed

LaChausse, Robert G

2016-09-01

To determine the impact of Positive Prevention PLUS, a school-based adolescent pregnancy prevention program on delaying sexual intercourse, birth control use, and pregnancy. I randomly assigned a diverse sample of ninth grade students in 21 suburban public high schools in California into treatment (n = 2483) and control (n = 1784) groups that participated in a clustered randomized controlled trial. Between October 2013 and May 2014, participants completed baseline and 6-month follow-up surveys regarding sexual behavior and pregnancy. Participants in the treatment group were offered Positive Prevention PLUS, an 11-lesson adolescent pregnancy prevention program. The program had statistically significant impacts on delaying sexual intercourse and increasing the use of birth control. However, I detected no program effect on pregnancy rates at 6-month follow-up. The Positive Prevention PLUS program demonstrated positive impacts on adolescent sexual behavior. This suggests that programs that focus on having students practice risk reduction skills may delay sexual activity and increase birth control use.

Coalescence of silver clusters by immersion in diluted HF solution

NASA Astrophysics Data System (ADS)

Milazzo, R. G.; Mio, A. M.; D'Arrigo, G.; Grimaldi, M. G.; Spinella, C.; Rimini, E.

2015-07-01

The galvanic displacement deposition of silver on H-terminated Si (100) in the time scale of seconds is instantaneous and characterized by a cluster density of 1011-1012 cm-2. The amount of deposited Ag follows a t1/2 dependence in agreement with a Cottrell diffusion limited mechanism. At the same time, during the deposition, the cluster density reduces by a factor 5. This behavior is in contrast with the assumption of immobile clusters. We show in the present work that coalescence and aggregation occur also in the samples immersed in the diluted hydrofluoric acid (HF) solution without the presence of Ag+. Clusters agglomerate according to a process of dynamic coalescence, typical of colloids, followed by atomic redistribution at the contact regions with the generation of multiple internal twins and stacking-faults. The normalized size distributions in terms of r/rmean follow also the prediction of the Smoluchowski ripening mechanism. No variation of the cluster density occurs for samples immersed in pure H2O solution. The different behavior might be associated to the strong attraction of clusters to oxide-terminated Si surface in presence of water. The silver clusters are instead weakly bound to hydrophobic H-terminated Si in presence of HF. HF causes then the detachment of clusters and a random movement on the silicon surface with mobility of about 10-13 cm2/s. Attractive interaction (probably van der Waals) among particles promotes coarsening.

Supercluster simulations: impact of baryons on the matter power spectrum and weak lensing forecasts for Super-CLASS

NASA Astrophysics Data System (ADS)

Peters, Aaron; Brown, Michael L.; Kay, Scott T.; Barnes, David J.

2018-03-01

We use a combination of full hydrodynamic and dark matter only simulations to investigate the effect that supercluster environments and baryonic physics have on the matter power spectrum, by re-simulating a sample of supercluster sub-volumes. On large scales we find that the matter power spectrum measured from our supercluster sample has at least twice as much power as that measured from our random sample. Our investigation of the effect of baryonic physics on the matter power spectrum is found to be in agreement with previous studies and is weaker than the selection effect over the majority of scales. In addition, we investigate the effect of targeting a cosmologically non-representative, supercluster region of the sky on the weak lensing shear power spectrum. We do this by generating shear and convergence maps using a line-of-sight integration technique, which intercepts our random and supercluster sub-volumes. We find the convergence power spectrum measured from our supercluster sample has a larger amplitude than that measured from the random sample at all scales. We frame our results within the context of the Super-CLuster Assisted Shear Survey (Super-CLASS), which aims to measure the cosmic shear signal in the radio band by targeting a region of the sky that contains five Abell clusters. Assuming the Super-CLASS survey will have a source density of 1.5 galaxies arcmin-2, we forecast a detection significance of 2.7^{+1.5}_{-1.2}, which indicates that in the absence of systematics the Super-CLASS project could make a cosmic shear detection with radio data alone.

Continuous representation of tumor microvessel density and detection of angiogenic hotspots in histological whole-slide images.

PubMed

Kather, Jakob Nikolas; Marx, Alexander; Reyes-Aldasoro, Constantino Carlos; Schad, Lothar R; Zöllner, Frank Gerrit; Weis, Cleo-Aron

2015-08-07

Blood vessels in solid tumors are not randomly distributed, but are clustered in angiogenic hotspots. Tumor microvessel density (MVD) within these hotspots correlates with patient survival and is widely used both in diagnostic routine and in clinical trials. Still, these hotspots are usually subjectively defined. There is no unbiased, continuous and explicit representation of tumor vessel distribution in histological whole slide images. This shortcoming distorts angiogenesis measurements and may account for ambiguous results in the literature. In the present study, we describe and evaluate a new method that eliminates this bias and makes angiogenesis quantification more objective and more efficient. Our approach involves automatic slide scanning, automatic image analysis and spatial statistical analysis. By comparing a continuous MVD function of the actual sample to random point patterns, we introduce an objective criterion for hotspot detection: An angiogenic hotspot is defined as a clustering of blood vessels that is very unlikely to occur randomly. We evaluate the proposed method in N=11 images of human colorectal carcinoma samples and compare the results to a blinded human observer. For the first time, we demonstrate the existence of statistically significant hotspots in tumor images and provide a tool to accurately detect these hotspots.

Bayesian network meta-analysis for cluster randomized trials with binary outcomes.

PubMed

Uhlmann, Lorenz; Jensen, Katrin; Kieser, Meinhard

2017-06-01

Network meta-analysis is becoming a common approach to combine direct and indirect comparisons of several treatment arms. In recent research, there have been various developments and extensions of the standard methodology. Simultaneously, cluster randomized trials are experiencing an increased popularity, especially in the field of health services research, where, for example, medical practices are the units of randomization but the outcome is measured at the patient level. Combination of the results of cluster randomized trials is challenging. In this tutorial, we examine and compare different approaches for the incorporation of cluster randomized trials in a (network) meta-analysis. Furthermore, we provide practical insight on the implementation of the models. In simulation studies, it is shown that some of the examined approaches lead to unsatisfying results. However, there are alternatives which are suitable to combine cluster randomized trials in a network meta-analysis as they are unbiased and reach accurate coverage rates. In conclusion, the methodology can be extended in such a way that an adequate inclusion of the results obtained in cluster randomized trials becomes feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Percolation and epidemics in random clustered networks

NASA Astrophysics Data System (ADS)

Miller, Joel C.

2009-08-01

The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied percolation or epidemics in clustered networks, but the networks often contain preferential contacts in high degree nodes. We introduce a class of random clustered networks and a class of random unclustered networks with the same preferential mixing. Percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks.

On the coherent rotation of diffuse matter in numerical simulations of clusters of galaxies

NASA Astrophysics Data System (ADS)

Baldi, Anna Silvia; De Petris, Marco; Sembolini, Federico; Yepes, Gustavo; Lamagna, Luca; Rasia, Elena

2017-03-01

We present a study on the coherent rotation of the intracluster medium and dark matter components of simulated galaxy clusters extracted from a volume-limited sample of the MUSIC project. The set is re-simulated with three different recipes for the gas physics: (I) non-radiative, (II) radiative without active galactic nuclei (AGN) feedback and (III) radiative with AGN feedback. Our analysis is based on the 146 most massive clusters identified as relaxed, 57 per cent of the total sample. We classify these objects as rotating and non-rotating according to the gas spin parameter, a quantity that can be related to cluster observations. We find that 4 per cent of the relaxed sample is rotating according to our criterion. By looking at the radial profiles of their specific angular momentum vector, we find that the solid body model is not a suitable description of rotational motions. The radial profiles of the velocity of the dark matter show a prevalence of the random velocity dispersion. Instead, the intracluster medium profiles are characterized by a comparable contribution from the tangential velocity and the dispersion. In general, the dark matter component dominates the dynamics of the clusters, as suggested by the correlation between its angular momentum and the gas one, and by the lack of relevant differences among the three sets of simulations.

Using Cluster Bootstrapping to Analyze Nested Data with a Few Clusters

ERIC Educational Resources Information Center

Huang, Francis L.

2018-01-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials…

Intraclass Correlations for Three-Level Multi-Site Cluster-Randomized Trials of Science Achievement

ERIC Educational Resources Information Center

Westine, Carl D.

2015-01-01

A cluster-randomized trial (CRT) relies on random assignment of intact clusters to treatment conditions, such as classrooms or schools (Raudenbush & Bryk, 2002). One specific type of CRT, a multi-site CRT (MSCRT), is commonly employed in educational research and evaluation studies (Spybrook & Raudenbush, 2009; Spybrook, 2014; Bloom,…

Sydney Playground Project: A Cluster-Randomized Trial to Increase Physical Activity, Play, and Social Skills

ERIC Educational Resources Information Center

Bundy, Anita; Engelen, Lina; Wyver, Shirley; Tranter, Paul; Ragen, Jo; Bauman, Adrian; Baur, Louise; Schiller, Wendy; Simpson, Judy M.; Niehues, Anita N.; Perry, Gabrielle; Jessup, Glenda; Naughton, Geraldine

2017-01-01

Background: We assessed the effectiveness of a simple intervention for increasing children's physical activity, play, perceived competence/social acceptance, and social skills. Methods: A cluster-randomized controlled trial was conducted, in which schools were the clusters. Twelve Sydney (Australia) primary schools were randomly allocated to…

Prediction models for clustered data: comparison of a random intercept and standard regression model

PubMed Central

2013-01-01

Background When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Methods Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. Results The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. Conclusion The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters. PMID:23414436

Prediction models for clustered data: comparison of a random intercept and standard regression model.

PubMed

Bouwmeester, Walter; Twisk, Jos W R; Kappen, Teus H; van Klei, Wilton A; Moons, Karel G M; Vergouwe, Yvonne

2013-02-15

When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Duration of Sleep and ADHD Tendency among Adolescents in China

ERIC Educational Resources Information Center

Lam, Lawrence T.; Yang, L.

2008-01-01

Objective: This study investigates the association between duration of sleep and ADHD tendency among adolescents. Method: This population-based health survey uses a two-stage random cluster sampling design. Participants ages 13 to 17 are recruited from the total population of adolescents attending high school in one city of China. Duration of…

Linking Teacher Competences to Organizational Citizenship Behaviour: The Role of Empowerment

ERIC Educational Resources Information Center

Kasekende, Francis; Munene, John C.; Otengei, Samson Omuudu; Ntayi, Joseph Mpeera

2016-01-01

Purpose: The purpose of this paper is to examine relationship between teacher competences and organizational citizenship behavior (OCB) with empowerment as a mediating factor. Design/methodology/approach: The study took a cross-sectional descriptive and analytical design. Using cluster and random sampling procedures, data were obtained from 383…

Efficacy of the Social Skills Improvement System Classwide Intervention Program (SSIS-CIP) Primary Version

ERIC Educational Resources Information Center

DiPerna, James Clyde; Lei, Puiwa; Bellinger, Jillian; Cheng, Weiyi

2015-01-01

A multisite cluster randomized trial was conducted to examine the effects of the Social Skills Improvement System Classwide Intervention Program (SSIS-CIP; Elliott & Gresham, 2007) on students' classroom social behavior. The final sample included 432 students across 38 second grade classrooms. Social skills and problem behaviors were measured…

A field test of three LQAS designs to assess the prevalence of acute malnutrition.

PubMed

Deitchler, Megan; Valadez, Joseph J; Egge, Kari; Fernandez, Soledad; Hennigan, Mary

2007-08-01

The conventional method for assessing the prevalence of Global Acute Malnutrition (GAM) in emergency settings is the 30 x 30 cluster-survey. This study describes alternative approaches: three Lot Quality Assurance Sampling (LQAS) designs to assess GAM. The LQAS designs were field-tested and their results compared with those from a 30 x 30 cluster-survey. Computer simulations confirmed that small clusters instead of a simple random sample could be used for LQAS assessments of GAM. Three LQAS designs were developed (33 x 6, 67 x 3, Sequential design) to assess GAM thresholds of 10, 15 and 20%. The designs were field-tested simultaneously with a 30 x 30 cluster-survey in Siraro, Ethiopia during June 2003. Using a nested study design, anthropometric, morbidity and vaccination data were collected on all children 6-59 months in sampled households. Hypothesis tests about GAM thresholds were conducted for each LQAS design. Point estimates were obtained for the 30 x 30 cluster-survey and the 33 x 6 and 67 x 3 LQAS designs. Hypothesis tests showed GAM as <10% for the 33 x 6 design and GAM as > or =10% for the 67 x 3 and Sequential designs. Point estimates for the 33 x 6 and 67 x 3 designs were similar to those of the 30 x 30 cluster-survey for GAM (6.7%, CI = 3.2-10.2%; 8.2%, CI = 4.3-12.1%, 7.4%, CI = 4.8-9.9%) and all other indicators. The CIs for the LQAS designs were only slightly wider than the CIs for the 30 x 30 cluster-survey; yet the LQAS designs required substantially less time to administer. The LQAS designs provide statistically appropriate alternatives to the more time-consuming 30 x 30 cluster-survey. However, additional field-testing is needed using independent samples rather than a nested study design.

Effectiveness of a virtual intervention for primary healthcare professionals aimed at improving attitudes towards the empowerment of patients with chronic diseases: study protocol for a cluster randomized controlled trial (e-MPODERA project).

PubMed

González-González, Ana Isabel; Orrego, Carola; Perestelo-Perez, Lilisbeth; Bermejo-Caja, Carlos Jesús; Mora, Nuria; Koatz, Débora; Ballester, Marta; Del Pino, Tasmania; Pérez-Ramos, Jeannet; Toledo-Chavarri, Ana; Robles, Noemí; Pérez-Rivas, Francisco Javier; Ramírez-Puerta, Ana Belén; Canellas-Criado, Yolanda; Del Rey-Granado, Yolanda; Muñoz-Balsa, Marcos José; Becerril-Rojas, Beatriz; Rodríguez-Morales, David; Sánchez-Perruca, Luis; Vázquez, José Ramón; Aguirre, Armando

2017-10-30

Communities of practice are based on the idea that learning involves a group of people exchanging experiences and knowledge. The e-MPODERA project aims to assess the effectiveness of a virtual community of practice aimed at improving primary healthcare professional attitudes to the empowerment of patients with chronic diseases. This paper describes the protocol for a cluster randomized controlled trial. We will randomly assign 18 primary-care practices per participating region of Spain (Catalonia, Madrid and Canary Islands) to a virtual community of practice or to usual training. The primary-care practice will be the randomization unit and the primary healthcare professional will be the unit of analysis. We will need a sample of 270 primary healthcare professionals (general practitioners and nurses) and 1382 patients. We will perform randomization after professionals and patients are selected. We will ask the intervention group to participate for 12 months in a virtual community of practice based on a web 2.0 platform. We will measure the primary outcome using the Patient-Provider Orientation Scale questionnaire administered at baseline and after 12 months. Secondary outcomes will be the sociodemographic characteristics of health professionals, sociodemographic and clinical characteristics of patients, the Patient Activation Measure questionnaire for patient activation and outcomes regarding use of the virtual community of practice. We will calculate a linear mixed-effects regression to estimate the effect of participating in the virtual community of practice. This cluster randomized controlled trial will show whether a virtual intervention for primary healthcare professionals improves attitudes to the empowerment of patients with chronic diseases. ClicalTrials.gov, NCT02757781 . Registered on 25 April 2016. Protocol Version. PI15.01 22 January 2016.

A quantitative approach to the topology of large-scale structure. [for galactic clustering computation

NASA Technical Reports Server (NTRS)

Gott, J. Richard, III; Weinberg, David H.; Melott, Adrian L.

1987-01-01

A quantitative measure of the topology of large-scale structure: the genus of density contours in a smoothed density distribution, is described and applied. For random phase (Gaussian) density fields, the mean genus per unit volume exhibits a universal dependence on threshold density, with a normalizing factor that can be calculated from the power spectrum. If large-scale structure formed from the gravitational instability of small-amplitude density fluctuations, the topology observed today on suitable scales should follow the topology in the initial conditions. The technique is illustrated by applying it to simulations of galaxy clustering in a flat universe dominated by cold dark matter. The technique is also applied to a volume-limited sample of the CfA redshift survey and to a model in which galaxies reside on the surfaces of polyhedral 'bubbles'. The topology of the evolved mass distribution and 'biased' galaxy distribution in the cold dark matter models closely matches the topology of the density fluctuations in the initial conditions. The topology of the observational sample is consistent with the random phase, cold dark matter model.

Coma cluster ultradiffuse galaxies are not standard radio galaxies

NASA Astrophysics Data System (ADS)

Struble, Mitchell F.

2018-02-01

Matching members in the Coma cluster catalogue of ultradiffuse galaxies (UDGs) from SUBARU imaging with a very deep radio continuum survey source catalogue of the cluster using the Karl G. Jansky Very Large Array (VLA) within a rectangular region of ∼1.19 deg2 centred on the cluster core reveals matches consistent with random. An overlapping set of 470 UDGs and 696 VLA radio sources in this rectangular area finds 33 matches within a separation of 25 arcsec; dividing the sample into bins with separations bounded by 5, 10, 20 and 25 arcsec finds 1, 4, 17 and 11 matches. An analytical model estimate, based on the Poisson probability distribution, of the number of randomly expected matches within these same separation bounds is 1.7, 4.9, 19.4 and 14.2, each, respectively, consistent with the 95 per cent Poisson confidence intervals of the observed values. Dividing the data into five clustercentric annuli of 0.1° and into the four separation bins, finds the same result. This random match of UDGs with VLA sources implies that UDGs are not radio galaxies by the standard definition. Those VLA sources having integrated flux >1 mJy at 1.4 GHz in Miller, Hornschemeier and Mobasher without SDSS galaxy matches are consistent with the known surface density of background radio sources. We briefly explore the possibility that some unresolved VLA sources near UDGs could be young, compact, bright, supernova remnants of Type Ia events, possibly in the intracluster volume.

Subtyping adolescents with bulimia nervosa.

PubMed

Chen, Eunice Y; Le Grange, Daniel

2007-12-01

Cluster analyses of eating disorder patients have yielded a "dietary-depressive" subtype, typified by greater negative affect, and a "dietary" subtype, typified by dietary restraint. This study aimed to replicate these findings in an adolescent sample with bulimia nervosa (BN) from a randomized controlled trial and to examine the validity and reliability of this methodology. In the sample of BN adolescents (N=80), cluster analysis revealed a "dietary-depressive" subtype (37.5%) and a "dietary" subtype (62.5%) using the Beck Depression Inventory, Rosenberg Self-Esteem Scale and Eating Disorder Examination Restraint subscale. The "dietary-depressive" subtype compared to the "dietary" subtype was significantly more likely to: (1) report co-occurring disorders, (2) greater eating and weight concerns, and (3) less vomiting abstinence at post-treatment (all p's<.05). The cluster analysis based on "dietary" and "dietary-depressive" subtypes appeared to have concurrent validity, yielding more distinct groups than subtyping by vomiting frequency. In order to assess the reliability of the subtyping scheme, a larger sample of adolescents with mixed eating and weight disorders in an outpatient eating disorder clinic (N=149) was subtyped, yielding similar subtypes. These results support the validity and reliability of the subtyping strategy in two adolescent samples.

Methods of developing core collections based on the predicted genotypic value of rice ( Oryza sativa L.).

PubMed

Li, C T; Shi, C H; Wu, J G; Xu, H M; Zhang, H Z; Ren, Y L

2004-04-01

The selection of an appropriate sampling strategy and a clustering method is important in the construction of core collections based on predicted genotypic values in order to retain the greatest degree of genetic diversity of the initial collection. In this study, methods of developing rice core collections were evaluated based on the predicted genotypic values for 992 rice varieties with 13 quantitative traits. The genotypic values of the traits were predicted by the adjusted unbiased prediction (AUP) method. Based on the predicted genotypic values, Mahalanobis distances were calculated and employed to measure the genetic similarities among the rice varieties. Six hierarchical clustering methods, including the single linkage, median linkage, centroid, unweighted pair-group average, weighted pair-group average and flexible-beta methods, were combined with random, preferred and deviation sampling to develop 18 core collections of rice germplasm. The results show that the deviation sampling strategy in combination with the unweighted pair-group average method of hierarchical clustering retains the greatest degree of genetic diversities of the initial collection. The core collections sampled using predicted genotypic values had more genetic diversity than those based on phenotypic values.

Sub-grouping patients with non-specific low back pain based on cluster analysis of discriminatory clinical items.

PubMed

Billis, Evdokia; McCarthy, Christopher J; Roberts, Chris; Gliatis, John; Papandreou, Maria; Gioftsos, George; Oldham, Jacqueline A

2013-02-01

To identify potential subgroups amongst patients with non-specific low back pain based on a consensus list of potentially discriminatory examination items. Exploratory study. A convenience sample of 106 patients with non-specific low back pain (43 males, 63 females, mean age 36 years, standard deviation 15.9 years) and 7 physiotherapists. Based on 3 focus groups and a two-round Delphi involving 23 health professionals and a random stratified sample of 150 physiotherapists, respectively, a comprehensive examination list comprising the most "discriminatory" items was compiled. Following reliability analysis, the most reliable clinical items were assessed with a sample of patients with non-specific low back pain. K-means cluster analysis was conducted for 2-, 3- and 4-cluster options to explore for meaningful homogenous subgroups. The most clinically meaningful cluster was a two-subgroup option, comprising a small group (n = 24) with more severe clinical presentation (i.e. more widespread pain, functional and sleeping problems, other symptoms, increased investigations undertaken, more severe clinical signs, etc.) and a larger less dysfunctional group (n = 80). A number of potentially discriminatory clinical items were identified by health professionals and sub-classified, based on a sample of patients with non-specific low back pain, into two subgroups. However, further work is needed to validate this classification process.

Line-of-sight structure toward strong lensing galaxy clusters

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

Bayliss, Matthew B.; Johnson, Traci; Sharon, Keren

2014-03-01

We present an analysis of the line-of-sight structure toward a sample of 10 strong lensing cluster cores. Structure is traced by groups that are identified spectroscopically in the redshift range, 0.1 ≤ z ≤ 0.9, and we measure the projected angular and comoving separations between each group and the primary strong lensing clusters in each corresponding line of sight. From these data we measure the distribution of projected angular separations between the primary strong lensing clusters and uncorrelated large-scale structure as traced by groups. We then compare the observed distribution of angular separations for our strong lensing selected lines ofmore » sight against the distribution of groups that is predicted for clusters lying along random lines of sight. There is clear evidence for an excess of structure along the line of sight at small angular separations (θ ≤ 6') along the strong lensing selected lines of sight, indicating that uncorrelated structure is a significant systematic that contributes to producing galaxy clusters with large cross sections for strong lensing. The prevalence of line-of-sight structure is one of several biases in strong lensing clusters that can potentially be folded into cosmological measurements using galaxy cluster samples. These results also have implications for current and future studies—such as the Hubble Space Telescope Frontier Fields—that make use of massive galaxy cluster lenses as precision cosmological telescopes; it is essential that the contribution of line-of-sight structure be carefully accounted for in the strong lens modeling of the cluster lenses.« less

Ferromagnetic clusters induced by a nonmagnetic random disorder in diluted magnetic semiconductors

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

Bui, Dinh-Hoi; Physics Department, Hue University’s College of Education, 34 Le Loi, Hue; Phan, Van-Nham, E-mail: phanvannham@dtu.edu.vn

In this work, we analyze the nonmagnetic random disorder leading to a formation of ferromagnetic clusters in diluted magnetic semiconductors. The nonmagnetic random disorder arises from randomness in the host lattice. Including the disorder to the Kondo lattice model with random distribution of magnetic dopants, the ferromagnetic–paramagnetic transition in the system is investigated in the framework of dynamical mean-field theory. At a certain low temperature one finds a fraction of ferromagnetic sites transiting to the paramagnetic state. Enlarging the nonmagnetic random disorder strength, the paramagnetic regimes expand resulting in the formation of the ferromagnetic clusters.

Under What Circumstances Does External Knowledge about the Correlation Structure Improve Power in Cluster Randomized Designs?

ERIC Educational Resources Information Center

Rhoads, Christopher

2014-01-01

Recent publications have drawn attention to the idea of utilizing prior information about the correlation structure to improve statistical power in cluster randomized experiments. Because power in cluster randomized designs is a function of many different parameters, it has been difficult for applied researchers to discern a simple rule explaining…

Radiative Feedback of Forming Star Clusters on Their GMC Environments: Theory and Simulation

NASA Astrophysics Data System (ADS)

Howard, C. S.; Pudritz, R. E.; Harris, W. E.

2013-07-01

Star clusters form from dense clumps within a molecular cloud. Radiation from these newly formed clusters feeds back on their natal molecular cloud through heating and ionization which ultimately stops gas accretion into the cluster. Recent studies suggest that radiative feedback effects from a single cluster may be sufficient to disrupt an entire cloud over a short timescale. Simulating cluster formation on a large scale, however, is computationally demanding due to the high number of stars involved. For this reason, we present a model for representing the radiative output of an entire cluster which involves randomly sampling an initial mass function (IMF) as the cluster accretes mass. We show that this model is able to reproduce the star formation histories of observed clusters. To examine the degree to which radiative feedback shapes the evolution of a molecular cloud, we use the FLASH adaptive-mesh refinement hydrodynamics code to simulate cluster formation in a turbulent cloud. Unlike previous studies, sink particles are used to represent a forming cluster rather than individual stars. Our cluster model is then coupled with a raytracing scheme to treat radiative transfer as the clusters grow in mass. This poster will outline the details of our model and present preliminary results from our 3D hydrodynamical simulations.

K-Means Algorithm Performance Analysis With Determining The Value Of Starting Centroid With Random And KD-Tree Method

NASA Astrophysics Data System (ADS)

Sirait, Kamson; Tulus; Budhiarti Nababan, Erna

2017-12-01

Clustering methods that have high accuracy and time efficiency are necessary for the filtering process. One method that has been known and applied in clustering is K-Means Clustering. In its application, the determination of the begining value of the cluster center greatly affects the results of the K-Means algorithm. This research discusses the results of K-Means Clustering with starting centroid determination with a random and KD-Tree method. The initial determination of random centroid on the data set of 1000 student academic data to classify the potentially dropout has a sse value of 952972 for the quality variable and 232.48 for the GPA, whereas the initial centroid determination by KD-Tree has a sse value of 504302 for the quality variable and 214,37 for the GPA variable. The smaller sse values indicate that the result of K-Means Clustering with initial KD-Tree centroid selection have better accuracy than K-Means Clustering method with random initial centorid selection.

A Framework for Designing Cluster Randomized Trials with Binary Outcomes

ERIC Educational Resources Information Center

Spybrook, Jessaca; Martinez, Andres

2011-01-01

The purpose of this paper is to provide a frame work for approaching a power analysis for a CRT (cluster randomized trial) with a binary outcome. The authors suggest a framework in the context of a simple CRT and then extend it to a blocked design, or a multi-site cluster randomized trial (MSCRT). The framework is based on proportions, an…

Understanding Statistical Power in Cluster Randomized Trials: Challenges Posed by Differences in Notation and Terminology

ERIC Educational Resources Information Center

Spybrook, Jessaca; Hedges, Larry; Borenstein, Michael

2014-01-01

Research designs in which clusters are the unit of randomization are quite common in the social sciences. Given the multilevel nature of these studies, the power analyses for these studies are more complex than in a simple individually randomized trial. Tools are now available to help researchers conduct power analyses for cluster randomized…

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design

PubMed Central

Lu, Tsui-Shan; Longnecker, Matthew P.; Zhou, Haibo

2016-01-01

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data and the general ODS design for a continuous response. While substantial work has been done for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome dependent sampling (Multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the Multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the Multivariate-ODS or the estimator from a simple random sample with the same sample size. The Multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of PCB exposure to hearing loss in children born to the Collaborative Perinatal Study. PMID:27966260

Co-occurring substance-related and behavioral addiction problems: A person-centered, lay epidemiology approach.

PubMed

Konkolÿ Thege, Barna; Hodgins, David C; Wild, T Cameron

2016-12-01

Background and aims The aims of this study were (a) to describe the prevalence of single versus multiple addiction problems in a large representative sample and (b) to identify distinct subgroups of people experiencing substance-related and behavioral addiction problems. Methods A random sample of 6,000 respondents from Alberta, Canada, completed survey items assessing self-attributed problems experienced in the past year with four substances (alcohol, tobacco, marijuana, and cocaine) and six behaviors (gambling, eating, shopping, sex, video gaming, and work). Hierarchical cluster analyses were used to classify patterns of co-occurring addiction problems on an analytic subsample of 2,728 respondents (1,696 women and 1032 men; M age  = 45.1 years, SD age  = 13.5 years) who reported problems with one or more of the addictive behaviors in the previous year. Results In the total sample, 49.2% of the respondents reported zero, 29.8% reported one, 13.1% reported two, and 7.9% reported three or more addiction problems in the previous year. Cluster-analytic results suggested a 7-group solution. Members of most clusters were characterized by multiple addiction problems; the average number of past year addictive behaviors in cluster members ranged between 1 (Cluster II: excessive eating only) and 2.5 (Cluster VII: excessive video game playing with the frequent co-occurrence of smoking, excessive eating and work). Discussion and conclusions Our findings replicate previous results indicating that about half of the adult population struggles with at least one excessive behavior in a given year; however, our analyses revealed a higher number of co-occurring addiction clusters than typically found in previous studies.

Co-occurring substance-related and behavioral addiction problems: A person-centered, lay epidemiology approach

PubMed Central

Konkolÿ Thege, Barna; Hodgins, David C.; Wild, T. Cameron

2016-01-01

Background and aims The aims of this study were (a) to describe the prevalence of single versus multiple addiction problems in a large representative sample and (b) to identify distinct subgroups of people experiencing substance-related and behavioral addiction problems. Methods A random sample of 6,000 respondents from Alberta, Canada, completed survey items assessing self-attributed problems experienced in the past year with four substances (alcohol, tobacco, marijuana, and cocaine) and six behaviors (gambling, eating, shopping, sex, video gaming, and work). Hierarchical cluster analyses were used to classify patterns of co-occurring addiction problems on an analytic subsample of 2,728 respondents (1,696 women and 1032 men; Mage = 45.1 years, SDage = 13.5 years) who reported problems with one or more of the addictive behaviors in the previous year. Results In the total sample, 49.2% of the respondents reported zero, 29.8% reported one, 13.1% reported two, and 7.9% reported three or more addiction problems in the previous year. Cluster-analytic results suggested a 7-group solution. Members of most clusters were characterized by multiple addiction problems; the average number of past year addictive behaviors in cluster members ranged between 1 (Cluster II: excessive eating only) and 2.5 (Cluster VII: excessive video game playing with the frequent co-occurrence of smoking, excessive eating and work). Discussion and conclusions Our findings replicate previous results indicating that about half of the adult population struggles with at least one excessive behavior in a given year; however, our analyses revealed a higher number of co-occurring addiction clusters than typically found in previous studies. PMID:27829288

The Influence of Social Network Characteristics on Peer Clustering in Smoking: A Two-Wave Panel Study of 19- and 23-Year-Old Swedes.

PubMed

Miething, Alexander; Rostila, Mikael; Edling, Christofer; Rydgren, Jens

2016-01-01

The present study examines how the composition of social networks and perceived relationship content influence peer clustering in smoking, and how the association changes during the transition from late adolescence to early adulthood. The analysis was based on a Swedish two-wave survey sample comprising ego-centric network data. Respondents were 19 years old in the initial wave, and 23 when the follow-up sample was conducted. 17,227 ego-alter dyads were included in the analyses, which corresponds to an average response rate of 48.7 percent. Random effects logistic regression models were performed to calculate gender-specific average marginal effects of social network characteristics on smoking. The association of egos' and alters' smoking behavior was confirmed and found to be stronger when correlated in the female sample. For females, the associations decreased between age 19 and 23. Interactions between network characteristics and peer clustering in smoking showed that intense social interactions with smokers increase egos' smoking probability. The influence of network structures on peer clustering in smoking decreased during the transition from late adolescence to early adulthood. The study confirmed peer clustering in smoking and revealed that females' smoking behavior in particular is determined by social interactions. Female smokers' propensity to interact with other smokers was found to be associated with the quality of peer relationships, frequent social interactions, and network density. The influence of social networks on peer clustering in smoking decreased during the transition from late adolescence to early adulthood.

The Influence of Social Network Characteristics on Peer Clustering in Smoking: A Two-Wave Panel Study of 19- and 23-Year-Old Swedes

PubMed Central

Rostila, Mikael; Edling, Christofer; Rydgren, Jens

2016-01-01

Objectives The present study examines how the composition of social networks and perceived relationship content influence peer clustering in smoking, and how the association changes during the transition from late adolescence to early adulthood. Methods The analysis was based on a Swedish two-wave survey sample comprising ego-centric network data. Respondents were 19 years old in the initial wave, and 23 when the follow-up sample was conducted. 17,227 ego-alter dyads were included in the analyses, which corresponds to an average response rate of 48.7 percent. Random effects logistic regression models were performed to calculate gender-specific average marginal effects of social network characteristics on smoking. Results The association of egos’ and alters’ smoking behavior was confirmed and found to be stronger when correlated in the female sample. For females, the associations decreased between age 19 and 23. Interactions between network characteristics and peer clustering in smoking showed that intense social interactions with smokers increase egos’ smoking probability. The influence of network structures on peer clustering in smoking decreased during the transition from late adolescence to early adulthood. Conclusions The study confirmed peer clustering in smoking and revealed that females’ smoking behavior in particular is determined by social interactions. Female smokers’ propensity to interact with other smokers was found to be associated with the quality of peer relationships, frequent social interactions, and network density. The influence of social networks on peer clustering in smoking decreased during the transition from late adolescence to early adulthood. PMID:27727314

Social network recruitment for Yo Puedo - an innovative sexual health intervention in an underserved urban neighborhood: sample and design implications

PubMed Central

Minnis, Alexandra M.; vanDommelen-Gonzalez, Evan; Luecke, Ellen; Cheng, Helen; Dow, William; Bautista-Arredondo, Sergio; Padian, Nancy S.

2016-01-01

Most existing evidence-based sexual health interventions focus on individual-level behavior, even though there is substantial evidence that highlights the influential role of social environments in shaping adolescents’ behaviors and reproductive health outcomes. We developed Yo Puedo, a combined conditional cash transfer (CCT) and life skills intervention for youth to promote educational attainment, job training, and reproductive health wellness that we then evaluated for feasibility among 162 youth aged 16–21 years in a predominantly Latino community in San Francisco, CA. The intervention targeted youth’s social networks and involved recruitment and randomization of small social network clusters. In this paper we describe the design of the feasibility study and report participants’ baseline characteristics. Furthermore, we examined the sample and design implications of recruiting social network clusters as the unit of randomization. Baseline data provide evidence that we successfully enrolled high risk youth using a social network recruitment approach in community and school-based settings. Nearly all participants (95%) were high risk for adverse educational and reproductive health outcomes based on multiple measures of low socioeconomic status (81%) and/or reported high risk behaviors (e.g., gang affiliation, past pregnancy, recent unprotected sex, frequent substance use) (62%). We achieved variability in the study sample through heterogeneity in recruitment of the index participants, whereas the individuals within the small social networks of close friends demonstrated substantial homogeneity across sociodemographic and risk profile characteristics. Social networks recruitment was feasible and yielded a sample of high risk youth willing to enroll in a randomized study to evaluate a novel sexual health intervention. PMID:25358834

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.

PubMed

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.

An Association between Bullying Behaviors and Alcohol Use among Middle School Students

ERIC Educational Resources Information Center

Peleg-Oren, Neta; Cardenas, Gabriel A.; Comerford, Mary; Galea, Sandro

2012-01-01

Although a high prevalence of bullying behaviors among adolescents has been documented, little is known about the association between bullying behaviors and alcohol use among perpetrators or victims. This study used data from a representative two-stage cluster random sample of 44, 532 middle school adolescents in Florida. We found a high…

Psychometric Testing of the Chinese Version of the Decisional Balance Scale (CDBS)

ERIC Educational Resources Information Center

Chen, Huey-Shys; Sheu, Jiunn-Jye; Chen, W. William

2006-01-01

The purpose of this study was to conduct psychometric testing on the Chinese version of the decisional balance scale (CDBS) with Taiwanese seventh, eighth, and ninth graders who were recruited from the Taipei metropolitan area. A random cluster sampling method was used with 554 adolescents between the ages of 13 and 17 years. Factor analysis…

Marital and Procreative Projections of Rural Louisiana Youth: A Historical Comparison.

ERIC Educational Resources Information Center

Smith, Kevin B.; Ohlendorf, George W.

Changes in marital and procreative projections among rural Louisiana high school youth between 1968 and 1972 were examined. In 1968 a proportionate, stratified, random cluster sampling technique was employed to secure data on seniors from 13 white and 7 black high schools. In 1972 public school integration and the establishment of private schools…

Short Intervention, Sustained Effects: Promoting Students' Math Competence Beliefs, Effort, and Achievement

ERIC Educational Resources Information Center

Brisson, Brigitte Maria; Dicke, Anna-Lena; Gaspard, Hanna; Häfner, Isabelle; Flunger, Barbara; Nagengast, Benjamin; Trautwein, Ulrich

2017-01-01

The present study investigated the effectiveness of two short relevance interventions (writing a text or evaluating quotations about the utility of mathematics) using a sample of 1,916 students in 82 math classrooms in a cluster randomized controlled experiment. Short-term and sustained effects (6 weeks and 5 months after the intervention) of the…

Parental and School Bonding in Iranian Adolescent Perpetrators and Victims of Bullying

ERIC Educational Resources Information Center

Mohebbi, Mina; Mirnasab, Mirmahmoud; Wiener, Judith

2016-01-01

This study compared parental and school bonding in adolescents in Iran who are perpetrators of bullying, victims of bullying and not-involved in bullying. Secondary school students (N = 240) were selected by cluster random sampling and screening, and categorized as perpetrators of bullying (N = 80), victims of bullying (N = 80) and non-involved (N…

Acculturation Stress, Drinking, and Intimate Partner Violence among Hispanic Couples in the U.S

ERIC Educational Resources Information Center

Caetano, Raul; Ramisetty-Mikler, Suhasini; Caetano Vaeth, Patrice A.; Harris, T. Robert

2007-01-01

This article examines the cross-sectional association between acculturation, acculturation stress, drinking, and intimate partner violence (IPV) among Hispanic couples in the U.S. The data being analyzed come from a multi-cluster random household sample of couples interviewed as part of the second wave of a 5-year national longitudinal study. The…

Effects of the "Positive Action" Program on Indicators of Positive Youth Development among Urban Youth

ERIC Educational Resources Information Center

Lewis, Kendra M.; Vuchinich, Samuel; Ji, Peter; DuBois, David L.; Acock, Alan; Bavarian, Niloofar; Day, Joseph; Silverthorn, Naida; Flay, Brian R.

2016-01-01

This study evaluated effects of "Positive Action," a school-based social-emotional and character development intervention, on indicators of positive youth development (PYD) among a sample of low-income, ethnic minority youth attending 14 urban schools. The study used a matched-pair, cluster-randomized controlled design at the school…

Identity Styles and Academic Achievement: Mediating Role of Academic Self-Efficacy

ERIC Educational Resources Information Center

Hejazi, Elaheh; Shahraray, Mehrnaz; Farsinejad, Masomeh; Asgary, Ali

2009-01-01

The purpose of this study was to assess the mediating effect of self-efficacy on the relationship between identity styles and academic achievement. Four-hundred high school students (200 male, 200 female) who were selected through cluster random sampling, completed the Revised Identity Styles Inventory (ISI, 6G) and Morgan-Jink Student Efficacy…

Date Fighting Experiences among College Students: Are They Associated with Other Health-Risk Behaviors?

ERIC Educational Resources Information Center

DuRant, Robert; Champion, Heather; Wolfson, Mark; Omli, Morrow; McCoy, Thomas; D'Agostino, Ralph B., Jr.; Wagoner, Kim; Mitra, Ananda

2007-01-01

Objective: The authors examined the clustering of health-risk behaviors among college students who reported date fight involvement. Participants and Methods: The authors administered a Web-based survey to a stratified random sample of 3,920 college students from 10 universities in North Carolina. Results: Among men, 5.6% reported date fight…

Readers, Players, and Watchers: EFL Students' Vocabulary Acquisition through Digital Video Games

ERIC Educational Resources Information Center

Ebrahimzadeh, Mohsen

2017-01-01

The present study investigated vocabulary acquisition through a commercial digital video game compared to a traditional pencil-and-paper treatment. Chosen through cluster sampling, 241 male high school students (age 12-18) participated in the study. They were randomly assigned to one of the following groups. The first group, called Readers,…

Implementation of Possession Laws and the Social Ecology of Tobacco Control

ERIC Educational Resources Information Center

Livingood, William C.; Woodhouse, Lynn D.; Wludyka, Peter

2009-01-01

The objective of this evaluation research was to assess the impact of programs intended to support the enforcement component of a comprehensive youth tobacco control. The research method was a survey of a randomly stratified cluster sample of law enforcement officers. Results of the evaluation showed that the enforcement behaviors of officers were…

Patterns and Impact of Comorbidity and Multimorbidity among Community-Resident American Indian Elders

ERIC Educational Resources Information Center

John, Robert; Kerby, Dave S.; Hennessy, Catherine Hagan

2003-01-01

Purpose: The purpose of this study is to suggest a new approach to identifying patterns of comorbidity and multimorbidity. Design and Methods: A random sample of 1,039 rural community-resident American Indian elders aged 60 years and older was surveyed. Comorbidity was investigated with four standard approaches, and with cluster analysis. Results:…

Circular single domains in hemispherical Permalloy nanoclusters

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

Araujo, Clodoaldo I. L de, E-mail: dearaujo@ufv.br; Fonseca, Jakson M.; Sinnecker, João P.

2014-11-14

We have studied ferromagnetic Permalloy clusters obtained by electrodeposition on n-type silicon. Magnetization measurements reveal hysteresis loops almost independent on temperature and very similar in shape to those obtained in nanodisks with diameter bigger than 150 nm. The spin configuration for the ground state, obtained by micromagnetic simulation, shows topological vortices with random chirality and polarization. This behavior in the small diameter clusters (∼80 nm) is attributed to the Dzyaloshinskii-Moriya interaction that arises in its hemispherical geometries. This magnetization behavior can be utilized to explain the magnetoresistance measured with magnetic field in plane and out of sample plane.

New Estimates of Design Parameters for Clustered Randomization Studies: Findings from North Carolina and Florida. Working Paper 43

ERIC Educational Resources Information Center

Xu, Zeyu; Nichols, Austin

2010-01-01

The gold standard in making causal inference on program effects is a randomized trial. Most randomization designs in education randomize classrooms or schools rather than individual students. Such "clustered randomization" designs have one principal drawback: They tend to have limited statistical power or precision. This study aims to…

When is informed consent required in cluster randomized trials in health research?

PubMed Central

2011-01-01

This article is part of a series of papers examining ethical issues in cluster randomized trials (CRTs) in health research. In the introductory paper in this series, we set out six areas of inquiry that must be addressed if the cluster trial is to be set on a firm ethical foundation. This paper addresses the second of the questions posed, namely, from whom, when, and how must informed consent be obtained in CRTs in health research? The ethical principle of respect for persons implies that researchers are generally obligated to obtain the informed consent of research subjects. Aspects of CRT design, including cluster randomization, cluster level interventions, and cluster size, present challenges to obtaining informed consent. Here we address five questions related to consent and CRTs: How can a study proceed if informed consent is not possible? Is consent to randomization always required? What information must be disclosed to potential subjects if their cluster has already been randomized? Is passive consent a valid substitute for informed consent? Do health professionals have a moral obligation to participate as subjects in CRTs designed to improve professional practice? We set out a framework based on the moral foundations of informed consent and international regulatory provisions to address each of these questions. First, when informed consent is not possible, a study may proceed if a research ethics committee is satisfied that conditions for a waiver of consent are satisfied. Second, informed consent to randomization may not be required if it is not possible to approach subjects at the time of randomization. Third, when potential subjects are approached after cluster randomization, they must be provided with a detailed description of the interventions in the trial arm to which their cluster has been randomized; detailed information on interventions in other trial arms need not be provided. Fourth, while passive consent may serve a variety of practical ends, it is not a substitute for valid informed consent. Fifth, while health professionals may have a moral obligation to participate as subjects in research, this does not diminish the necessity of informed consent to study participation. PMID:21906277

A Gender Bias Habit-Breaking Intervention Led to Increased Hiring of Female Faculty in STEMM Departments.

PubMed

Devine, Patricia G; Forscher, Patrick S; Cox, William T L; Kaatz, Anna; Sheridan, Jennifer; Carnes, Molly

2017-11-01

Addressing the underrepresentation of women in science is a top priority for many institutions, but the majority of efforts to increase representation of women are neither evidence-based nor rigorously assessed. One exception is the gender bias habit-breaking intervention (Carnes et al., 2015), which, in a cluster-randomized trial involving all but two departmental clusters ( N = 92) in the 6 STEMM focused schools/colleges at the University of Wisconsin - Madison, led to increases in gender bias awareness and self-efficacy to promote gender equity in academic science departments. Following this initial success, the present study compares, in a preregistered analysis, hiring rates of new female faculty pre- and post-manipulation. Whereas the proportion of women hired by control departments remained stable over time, the proportion of women hired by intervention departments increased by an estimated 18 percentage points ( OR = 2.23, d OR = 0.34). Though the preregistered analysis did not achieve conventional levels of statistical significance ( p < 0.07), our study has a hard upper limit on statistical power, as the cluster-randomized trial has a maximum sample size of 92 departmental clusters. These patterns have undeniable practical significance for the advancement of women in science, and provide promising evidence that psychological interventions can facilitate gender equity and diversity.

Measurement Error Correction Formula for Cluster-Level Group Differences in Cluster Randomized and Observational Studies

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.

2016-01-01

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

Handling Correlations between Covariates and Random Slopes in Multilevel Models

ERIC Educational Resources Information Center

Bates, Michael David; Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders

2014-01-01

This article discusses estimation of multilevel/hierarchical linear models that include cluster-level random intercepts and random slopes. Viewing the models as structural, the random intercepts and slopes represent the effects of omitted cluster-level covariates that may be correlated with included covariates. The resulting correlations between…

A pattern-mixture model approach for handling missing continuous outcome data in longitudinal cluster randomized trials.

PubMed

Fiero, Mallorie H; Hsu, Chiu-Hsieh; Bell, Melanie L

2017-11-20

We extend the pattern-mixture approach to handle missing continuous outcome data in longitudinal cluster randomized trials, which randomize groups of individuals to treatment arms, rather than the individuals themselves. Individuals who drop out at the same time point are grouped into the same dropout pattern. We approach extrapolation of the pattern-mixture model by applying multilevel multiple imputation, which imputes missing values while appropriately accounting for the hierarchical data structure found in cluster randomized trials. To assess parameters of interest under various missing data assumptions, imputed values are multiplied by a sensitivity parameter, k, which increases or decreases imputed values. Using simulated data, we show that estimates of parameters of interest can vary widely under differing missing data assumptions. We conduct a sensitivity analysis using real data from a cluster randomized trial by increasing k until the treatment effect inference changes. By performing a sensitivity analysis for missing data, researchers can assess whether certain missing data assumptions are reasonable for their cluster randomized trial. Copyright © 2017 John Wiley & Sons, Ltd.

On the Structure of Cortical Microcircuits Inferred from Small Sample Sizes.

PubMed

Vegué, Marina; Perin, Rodrigo; Roxin, Alex

2017-08-30

The structure in cortical microcircuits deviates from what would be expected in a purely random network, which has been seen as evidence of clustering. To address this issue, we sought to reproduce the nonrandom features of cortical circuits by considering several distinct classes of network topology, including clustered networks, networks with distance-dependent connectivity, and those with broad degree distributions. To our surprise, we found that all of these qualitatively distinct topologies could account equally well for all reported nonrandom features despite being easily distinguishable from one another at the network level. This apparent paradox was a consequence of estimating network properties given only small sample sizes. In other words, networks that differ markedly in their global structure can look quite similar locally. This makes inferring network structure from small sample sizes, a necessity given the technical difficulty inherent in simultaneous intracellular recordings, problematic. We found that a network statistic called the sample degree correlation (SDC) overcomes this difficulty. The SDC depends only on parameters that can be estimated reliably given small sample sizes and is an accurate fingerprint of every topological family. We applied the SDC criterion to data from rat visual and somatosensory cortex and discovered that the connectivity was not consistent with any of these main topological classes. However, we were able to fit the experimental data with a more general network class, of which all previous topologies were special cases. The resulting network topology could be interpreted as a combination of physical spatial dependence and nonspatial, hierarchical clustering. SIGNIFICANCE STATEMENT The connectivity of cortical microcircuits exhibits features that are inconsistent with a simple random network. Here, we show that several classes of network models can account for this nonrandom structure despite qualitative differences in their global properties. This apparent paradox is a consequence of the small numbers of simultaneously recorded neurons in experiment: when inferred via small sample sizes, many networks may be indistinguishable despite being globally distinct. We develop a connectivity measure that successfully classifies networks even when estimated locally with a few neurons at a time. We show that data from rat cortex is consistent with a network in which the likelihood of a connection between neurons depends on spatial distance and on nonspatial, asymmetric clustering. Copyright © 2017 the authors 0270-6474/17/378498-13$15.00/0.

Citywide cluster randomized trial to restore blighted vacant land and its effects on violence, crime, and fear

PubMed Central

Branas, Charles C.; South, Eugenia; Kondo, Michelle C.; Hohl, Bernadette C.; Bourgois, Philippe; Wiebe, Douglas J.; MacDonald, John M.

2018-01-01

Vacant and blighted urban land is a widespread and potentially risky environmental condition encountered by millions of people on a daily basis. About 15% of the land in US cities is deemed vacant or abandoned, an area roughly the size of Switzerland. In a citywide cluster randomized controlled trial, we investigated the effects of standardized, reproducible interventions that restore vacant land on the commission of violence, crime, and the perceptions of fear and safety. Quantitative and ethnographic analyses were included in a mixed-methods approach to more fully test and explicate our findings. A total of 541 randomly sampled vacant lots were randomly assigned into treatment and control study arms; outcomes from police and 445 randomly sampled participants were analyzed over a 38-month study period. Participants living near treated vacant lots reported significantly reduced perceptions of crime (−36.8%, P < 0.05), vandalism (−39.3%, P < 0.05), and safety concerns when going outside their homes (−57.8%, P < 0.05), as well as significantly increased use of outside spaces for relaxing and socializing (75.7%, P < 0.01). Significant reductions in crime overall (−13.3%, P < 0.01), gun violence (−29.1%, P < 0.001), burglary (−21.9%, P < 0.001), and nuisances (−30.3%, P < 0.05) were also found after the treatment of vacant lots in neighborhoods below the poverty line. Blighted and vacant urban land affects people’s perceptions of safety, and their actual, physical safety. Restoration of this land can be an effective and scalable infrastructure intervention for gun violence, crime, and fear in urban neighborhoods. PMID:29483246

Preparation and characterization of chemically defined oligomers of rabbit immunoglobulin G molecules for the complement binding studies.

PubMed Central

Wright, J K; Tschopp, J; Jaton, J C

1980-01-01

Pure dimers, trimers, tetramers and pentamers of rabbit non-immune IgG (immunoglobulin G) or antibody IgG were prepared by polymerization in the presence of the bifunctional cross-linking reagent dithiobis (succinimidylpropionate). Oligomerization was performed either in the presence of polysaccharide antigen and specific monomeric antibody (method A) or by random cross-linking of non-immune rabbit IgG in the absence of antigen (method B). By repeated gel-filtration chromatography, samples prepared by both methods exhibited a single band in analytical sodium dodecyl sulphate/polyacrylamide-gel electrophoresis. The electrophoretic mobilities of samples prepared by method A were slightly greater than those for the corresponding samples prepared by method B. This might suggest a role played by antigen in the orientation of IgG molecules within the clusters, which may be more compact than those formed by random cross-linking. The average numbers of cross-linker molecules per oligomer varied between 3 and 6 for clusters made by method A and between 1 and 3 for clusters made by method B. Ultracentrifugal analyses of the oligomers yielded sedimentation coefficients (S20,w) of 9.6S for the dimer, 11.2S for the trimer, 13.6S for the tetramer and 16.1S for the pentamer. Comparison of the observed sedimentation coefficients with those predicted by various hydrodynamic models suggested these oligomers possessed open and linear structures. Reduction of the cross-linking molecules converted oligomers into monomeric species of IgG. C.d. spectra of some oligomers studied in the range 200-250 nm were essentially the same as that of monomeric IgG molecules, thus strongly suggesting no major conformation changes in IgG molecules within clusters. These oligomers were found to be stable for up to 2 months when stored at -70 degrees C. Images Fig. 1. Fig. 4. PMID:7188424

Exploring Relations Between BCG & Cluster Properties in the SPectroscopic IDentification of eROSITA Sources Survey from 0.05 < z < 0.3

NASA Astrophysics Data System (ADS)

Furnell, Kate E.; Collins, Chris A.; Kelvin, Lee S.; Clerc, Nicolas; Baldry, Ivan K.; Finoguenov, Alexis; Erfanianfar, Ghazaleh; Comparat, Johan; Schneider, Donald P.

2018-04-01

We present a sample of 329 low to intermediate redshift (0.05 < z < 0.3) brightest cluster galaxies (BCGs) in X-ray selected clusters from the SPectroscopic IDentification of eRosita Sources (SPIDERS) survey, a spectroscopic survey within Sloan Digital Sky Survey-IV (SDSS-IV). We define our BCGs by simultaneous consideration of legacy X-ray data from ROSAT, maximum likelihood outputs from an optical cluster-finder algorithm and visual inspection. Using SDSS imaging data, we fit Sérsic profiles to our BCGs in three bands (g, r, i) with SIGMA, a GALFIT-based software wrapper. We examine the reliability of our fits by running our pipeline on ˜104 psf-convolved model profiles injected into 8 random cluster fields; we then use the results of this analysis to create a robust subsample of 198 BCGs. We outline three cluster properties of interest: overall cluster X-ray luminosity (LX), cluster richness as estimated by REDMAPPER (λ) and cluster halo mass (M200), which is estimated via velocity dispersion. In general, there are significant correlations with BCG stellar mass between all three environmental properties, but no significant trends arise with either Sérsic index or effective radius. There is no major environmental dependence on the strength of the relation between effective radius and BCG stellar mass. Stellar mass therefore arises as the most important factor governing BCG morphology. Our results indicate that our sample consists of a large number of relaxed, mature clusters containing broadly homogeneous BCGs up to z ˜ 0.3, suggesting that there is little evidence for much ongoing structural evolution for BCGs in these systems.

Search for Directed Networks by Different Random Walk Strategies

NASA Astrophysics Data System (ADS)

Zhu, Zi-Qi; Jin, Xiao-Ling; Huang, Zhi-Long

2012-03-01

A comparative study is carried out on the efficiency of five different random walk strategies searching on directed networks constructed based on several typical complex networks. Due to the difference in search efficiency of the strategies rooted in network clustering, the clustering coefficient in a random walker's eye on directed networks is defined and computed to be half of the corresponding undirected networks. The search processes are performed on the directed networks based on Erdös—Rényi model, Watts—Strogatz model, Barabási—Albert model and clustered scale-free network model. It is found that self-avoiding random walk strategy is the best search strategy for such directed networks. Compared to unrestricted random walk strategy, path-iteration-avoiding random walks can also make the search process much more efficient. However, no-triangle-loop and no-quadrangle-loop random walks do not improve the search efficiency as expected, which is different from those on undirected networks since the clustering coefficient of directed networks are smaller than that of undirected networks.

Who are the healthy active seniors? A cluster analysis.

PubMed

Lai, Claudia K Y; Chan, Engle Angela; Chin, Kenny C W

2014-12-01

This paper reports a cluster analysis of a sample recruited from a randomized controlled trial that explored the effect of using a life story work approach to improve the psychological outcomes of older people in the community. 238 subjects from community centers were included in this analysis. After statistical testing, 169 seniors were assigned to the active ageing (AG) cluster and 69 to the inactive ageing (IG) cluster. Those in the AG were younger and healthier, with fewer chronic diseases and fewer depressive symptoms than those in the IG. They were more satisfied with their lives, and had higher self-esteem. They met with their family members more frequently, they engaged in more leisure activities and were more likely to have the ability to move freely. In summary, active ageing was observed in people with better health and functional performance. Our results echoed the limited findings reported in the literature.

Cluster Tails for Critical Power-Law Inhomogeneous Random Graphs

NASA Astrophysics Data System (ADS)

van der Hofstad, Remco; Kliem, Sandra; van Leeuwaarden, Johan S. H.

2018-04-01

Recently, the scaling limit of cluster sizes for critical inhomogeneous random graphs of rank-1 type having finite variance but infinite third moment degrees was obtained in Bhamidi et al. (Ann Probab 40:2299-2361, 2012). It was proved that when the degrees obey a power law with exponent τ \\in (3,4), the sequence of clusters ordered in decreasing size and multiplied through by n^{-(τ -2)/(τ -1)} converges as n→ ∞ to a sequence of decreasing non-degenerate random variables. Here, we study the tails of the limit of the rescaled largest cluster, i.e., the probability that the scaling limit of the largest cluster takes a large value u, as a function of u. This extends a related result of Pittel (J Combin Theory Ser B 82(2):237-269, 2001) for the Erdős-Rényi random graph to the setting of rank-1 inhomogeneous random graphs with infinite third moment degrees. We make use of delicate large deviations and weak convergence arguments.

A comparison of adaptive sampling designs and binary spatial models: A simulation study using a census of Bromus inermis

USGS Publications Warehouse

Irvine, Kathryn M.; Thornton, Jamie; Backus, Vickie M.; Hohmann, Matthew G.; Lehnhoff, Erik A.; Maxwell, Bruce D.; Michels, Kurt; Rew, Lisa

2013-01-01

Commonly in environmental and ecological studies, species distribution data are recorded as presence or absence throughout a spatial domain of interest. Field based studies typically collect observations by sampling a subset of the spatial domain. We consider the effects of six different adaptive and two non-adaptive sampling designs and choice of three binary models on both predictions to unsampled locations and parameter estimation of the regression coefficients (species–environment relationships). Our simulation study is unique compared to others to date in that we virtually sample a true known spatial distribution of a nonindigenous plant species, Bromus inermis. The census of B. inermis provides a good example of a species distribution that is both sparsely (1.9 % prevalence) and patchily distributed. We find that modeling the spatial correlation using a random effect with an intrinsic Gaussian conditionally autoregressive prior distribution was equivalent or superior to Bayesian autologistic regression in terms of predicting to un-sampled areas when strip adaptive cluster sampling was used to survey B. inermis. However, inferences about the relationships between B. inermis presence and environmental predictors differed between the two spatial binary models. The strip adaptive cluster designs we investigate provided a significant advantage in terms of Markov chain Monte Carlo chain convergence when trying to model a sparsely distributed species across a large area. In general, there was little difference in the choice of neighborhood, although the adaptive king was preferred when transects were randomly placed throughout the spatial domain.

Genarris: Random generation of molecular crystal structures and fast screening with a Harris approximation

NASA Astrophysics Data System (ADS)

Li, Xiayue; Curtis, Farren S.; Rose, Timothy; Schober, Christoph; Vazquez-Mayagoitia, Alvaro; Reuter, Karsten; Oberhofer, Harald; Marom, Noa

2018-06-01

We present Genarris, a Python package that performs configuration space screening for molecular crystals of rigid molecules by random sampling with physical constraints. For fast energy evaluations, Genarris employs a Harris approximation, whereby the total density of a molecular crystal is constructed via superposition of single molecule densities. Dispersion-inclusive density functional theory is then used for the Harris density without performing a self-consistency cycle. Genarris uses machine learning for clustering, based on a relative coordinate descriptor developed specifically for molecular crystals, which is shown to be robust in identifying packing motif similarity. In addition to random structure generation, Genarris offers three workflows based on different sequences of successive clustering and selection steps: the "Rigorous" workflow is an exhaustive exploration of the potential energy landscape, the "Energy" workflow produces a set of low energy structures, and the "Diverse" workflow produces a maximally diverse set of structures. The latter is recommended for generating initial populations for genetic algorithms. Here, the implementation of Genarris is reported and its application is demonstrated for three test cases.

Propensity score to detect baseline imbalance in cluster randomized trials: the role of the c-statistic.

PubMed

Leyrat, Clémence; Caille, Agnès; Foucher, Yohann; Giraudeau, Bruno

2016-01-22

Despite randomization, baseline imbalance and confounding bias may occur in cluster randomized trials (CRTs). Covariate imbalance may jeopardize the validity of statistical inferences if they occur on prognostic factors. Thus, the diagnosis of a such imbalance is essential to adjust statistical analysis if required. We developed a tool based on the c-statistic of the propensity score (PS) model to detect global baseline covariate imbalance in CRTs and assess the risk of confounding bias. We performed a simulation study to assess the performance of the proposed tool and applied this method to analyze the data from 2 published CRTs. The proposed method had good performance for large sample sizes (n =500 per arm) and when the number of unbalanced covariates was not too small as compared with the total number of baseline covariates (≥40% of unbalanced covariates). We also provide a strategy for pre selection of the covariates needed to be included in the PS model to enhance imbalance detection. The proposed tool could be useful in deciding whether covariate adjustment is required before performing statistical analyses of CRTs.

Adaptive sampling in research on risk-related behaviors.

PubMed

Thompson, Steven K; Collins, Linda M

2002-11-01

This article introduces adaptive sampling designs to substance use researchers. Adaptive sampling is particularly useful when the population of interest is rare, unevenly distributed, hidden, or hard to reach. Examples of such populations are injection drug users, individuals at high risk for HIV/AIDS, and young adolescents who are nicotine dependent. In conventional sampling, the sampling design is based entirely on a priori information, and is fixed before the study begins. By contrast, in adaptive sampling, the sampling design adapts based on observations made during the survey; for example, drug users may be asked to refer other drug users to the researcher. In the present article several adaptive sampling designs are discussed. Link-tracing designs such as snowball sampling, random walk methods, and network sampling are described, along with adaptive allocation and adaptive cluster sampling. It is stressed that special estimation procedures taking the sampling design into account are needed when adaptive sampling has been used. These procedures yield estimates that are considerably better than conventional estimates. For rare and clustered populations adaptive designs can give substantial gains in efficiency over conventional designs, and for hidden populations link-tracing and other adaptive procedures may provide the only practical way to obtain a sample large enough for the study objectives.

Person mobility in the design and analysis of cluster-randomized cohort prevention trials.

PubMed

Vuchinich, Sam; Flay, Brian R; Aber, Lawrence; Bickman, Leonard

2012-06-01

Person mobility is an inescapable fact of life for most cluster-randomized (e.g., schools, hospitals, clinic, cities, state) cohort prevention trials. Mobility rates are an important substantive consideration in estimating the effects of an intervention. In cluster-randomized trials, mobility rates are often correlated with ethnicity, poverty and other variables associated with disparity. This raises the possibility that estimated intervention effects may generalize to only the least mobile segments of a population and, thus, create a threat to external validity. Such mobility can also create threats to the internal validity of conclusions from randomized trials. Researchers must decide how to deal with persons who leave study clusters during a trial (dropouts), persons and clusters that do not comply with an assigned intervention, and persons who enter clusters during a trial (late entrants), in addition to the persons who remain for the duration of a trial (stayers). Statistical techniques alone cannot solve the key issues of internal and external validity raised by the phenomenon of person mobility. This commentary presents a systematic, Campbellian-type analysis of person mobility in cluster-randomized cohort prevention trials. It describes four approaches for dealing with dropouts, late entrants and stayers with respect to data collection, analysis and generalizability. The questions at issue are: 1) From whom should data be collected at each wave of data collection? 2) Which cases should be included in the analyses of an intervention effect? and 3) To what populations can trial results be generalized? The conclusions lead to recommendations for the design and analysis of future cluster-randomized cohort prevention trials.

Toward cost-efficient sampling methods

NASA Astrophysics Data System (ADS)

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.

Inferring Viral Dynamics in Chronically HCV Infected Patients from the Spatial Distribution of Infected Hepatocytes

DOE PAGES

Graw, Frederik; Balagopal, Ashwin; Kandathil, Abraham J.; ...

2014-11-13

Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, wemore » are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from 4-50 infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Lastly, our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.« less

Inferring Viral Dynamics in Chronically HCV Infected Patients from the Spatial Distribution of Infected Hepatocytes

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

Graw, Frederik; Balagopal, Ashwin; Kandathil, Abraham J.

Chronic liver infection by hepatitis C virus (HCV) is a major public health concern. Despite partly successful treatment options, several aspects of intrahepatic HCV infection dynamics are still poorly understood, including the preferred mode of viral propagation, as well as the proportion of infected hepatocytes. Answers to these questions have important implications for the development of therapeutic interventions. In this study, we present methods to analyze the spatial distribution of infected hepatocytes obtained by single cell laser capture microdissection from liver biopsy samples of patients chronically infected with HCV. By characterizing the internal structure of clusters of infected cells, wemore » are able to evaluate hypotheses about intrahepatic infection dynamics. We found that individual clusters on biopsy samples range in size from 4-50 infected cells. In addition, the HCV RNA content in a cluster declines from the cell that presumably founded the cluster to cells at the maximal cluster extension. These observations support the idea that HCV infection in the liver is seeded randomly (e.g. from the blood) and then spreads locally. Assuming that the amount of intracellular HCV RNA is a proxy for how long a cell has been infected, we estimate based on models of intracellular HCV RNA replication and accumulation that cells in clusters have been infected on average for less than a week. Further, we do not find a relationship between the cluster size and the estimated cluster expansion time. Lastly, our method represents a novel approach to make inferences about infection dynamics in solid tissues from static spatial data.« less

Fluorescent Random Amplified Microsatellites (F-RAMS) analysis of mushrooms as a forensic investigative tool.

PubMed

Kallifatidis, Beatrice; Borovička, Jan; Stránská, Jana; Drábek, Jiří; Mills, Deetta K

2014-03-01

The capability of Fluorescent Random Amplified Microsatellites (F-RAMS) to profile hallucinogenic mushrooms to species and sub-species level was assessed. Fifteen samples of Amanita rubescens and 22 samples of other hallucinogenic and non-hallucinogenic mushrooms of the genera Amanita and Psilocybe were profiled using two fluorescently-labeled, 5'degenerate primers, 5'-6FAM-SpC3-DD (CCA)5 and 5'-6FAM-SpC3-DHB (CGA)5, which target different microsatellite repeat regions. Among the two primers, 5'-6FAM-SpC3-DHB (CGA)5 provided more reliable data for identification purposes, by grouping samples of the same species and clustering closely related species together in a dendrogram based on amplicon similarities. A high degree of intra-specific variation between the 15 A. rubescens samples was shown with both primers and the amplicons generated for all A. rubescens samples were organized into three classes of amplicons (discriminant, private, and marker) based on their individualizing potential. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Patterns of Childhood Abuse and Neglect in a Representative German Population Sample

PubMed Central

Schilling, Christoph; Weidner, Kerstin; Brähler, Elmar; Glaesmer, Heide; Häuser, Winfried; Pöhlmann, Karin

2016-01-01

Background Different types of childhood maltreatment, like emotional abuse, emotional neglect, physical abuse, physical neglect and sexual abuse are interrelated because of their co-occurrence. Different patterns of childhood abuse and neglect are associated with the degree of severity of mental disorders in adulthood. The purpose of this study was (a) to identify different patterns of childhood maltreatment in a representative German community sample, (b) to replicate the patterns of childhood neglect and abuse recently found in a clinical German sample, (c) to examine whether participants reporting exposure to specific patterns of child maltreatment would report different levels of psychological distress, and (d) to compare the results of the typological approach and the results of a cumulative risk model based on our data set. Methods In a cross-sectional survey conducted in 2010, a representative random sample of 2504 German participants aged between 14 and 92 years completed the Childhood Trauma Questionnaire (CTQ). General anxiety and depression were assessed by standardized questionnaires (GAD-2, PHQ-2). Cluster analysis was conducted with the CTQ-subscales to identify different patterns of childhood maltreatment. Results Three different patterns of childhood abuse and neglect could be identified by cluster analysis. Cluster one showed low values on all CTQ-scales. Cluster two showed high values in emotional and physical neglect. Only cluster three showed high values in physical and sexual abuse. The three patterns of childhood maltreatment showed different degrees of depression (PHQ-2) and anxiety (GAD-2). Cluster one showed lowest levels of psychological distress, cluster three showed highest levels of mental distress. Conclusion The results show that different types of childhood maltreatment are interrelated and can be grouped into specific patterns of childhood abuse and neglect, which are associated with differing severity of psychological distress in adulthood. The results correspond to those recently found in a German clinical sample and support a typological approach in the research of maltreatment. While cumulative risk models focus on the number of maltreatment types, the typological approach takes the number as well as the severity of the maltreatment types into account. Thus, specific patterns of maltreatment can be examined with regard to specific long-term psychological consequences. PMID:27442446

Colonoscopy screening for colorectal cancer: the outcomes of two recruitment methods.

PubMed

Corbett, Mike; Chambers, Sharon L; Shadbolt, Bruce; Hillman, Lybus C; Taupin, Doug

2004-10-18

To determine the response to colorectal cancer (CRC) screening by colonoscopy, through direct invitation or through invitation by general practitioners. Two-way comparison of randomised population sampling versus cluster sampling of a representative general practice population in the Australian Capital Territory, May 2002 to January 2004. Invitation to screen, assessment for eligibility, interview, and colonoscopy. 881 subjects aged 55-74 years were invited to screen: 520 from the electoral roll (ER) sample and 361 from the general practice (GP) cluster sample. Response rate, participation rate, and rate of adenomatous polyps in the screened group. Participation was similar in the ER arm (35.1%; 95% CI, 30.2%-40.3%) and the GP arm (40.1%; 95% CI, 29.2%-51.0%) after correcting for ineligibility, which was higher in the ER arm. Superior eligibility in the GP arm was offset by the labour of manual record review. Response rates after two invitations were similar for the two groups (ER arm: 78.8%; 95% CI, 75.1%-82.1%; GP arm: 81.7%; 95% CI, 73.8%-89.6%). Overall, 53.4% ineligibility arose from having a colonoscopy in the past 10 years (ER arm, 98/178; GP arm, 42/84). Of 231 colonoscopies performed, 229 were complete, with 32% of subjects screened having adenomatous polyps. Colonoscopy-based CRC screening yields similar response and participation rates with either random population sampling or general practice cluster sampling, with population sampling through the electoral roll providing greater ease of recruitment.

NEAR-INFRARED ADAPTIVE OPTICS IMAGING OF INFRARED LUMINOUS GALAXIES: THE BRIGHTEST CLUSTER MAGNITUDE-STAR FORMATION RATE RELATION

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

Randriamanakoto, Z.; Väisänen, P.; Escala, A.

2013-10-01

We have established a relation between the brightest super star cluster (SSC) magnitude in a galaxy and the host star formation rate (SFR) for the first time in the near-infrared (NIR). The data come from a statistical sample of ∼40 luminous IR galaxies (LIRGs) and starbursts utilizing K-band adaptive optics imaging. While expanding the observed relation to longer wavelengths, less affected by extinction effects, it also pushes to higher SFRs. The relation we find, M{sub K} ∼ –2.6log SFR, is similar to that derived previously in the optical and at lower SFRs. It does not, however, fit the optical relationmore » with a single optical to NIR color conversion, suggesting systematic extinction and/or age effects. While the relation is broadly consistent with a size-of-sample explanation, we argue physical reasons for the relation are likely as well. In particular, the scatter in the relation is smaller than expected from pure random sampling strongly suggesting physical constraints. We also derive a quantifiable relation tying together cluster-internal effects and host SFR properties to possibly explain the observed brightest SSC magnitude versus SFR dependency.« less

Distribution of Escherichia coli O157:H7 in ground beef: Assessing the clustering intensity for an industrial-scale grinder and a low and localized initial contamination.

PubMed

Loukiadis, Estelle; Bièche-Terrier, Clémence; Malayrat, Catherine; Ferré, Franck; Cartier, Philippe; Augustin, Jean-Christophe

2017-06-05

Undercooked ground beef is regularly implicated in food-borne outbreaks involving pathogenic Shiga toxin-producing Escherichia coli. The dispersion of bacteria during mixing processes is of major concern for quantitative microbiological risk assessment since clustering will influence the number of bacteria the consumers might get exposed to as well as the performance of sampling plans used to detect contaminated ground beef batches. In this study, batches of 25kg of ground beef were manufactured according to a process mimicking an industrial-scale grinding with three successive steps: primary grinding, mixing and final grinding. The ground beef batches were made with 100% of chilled trims or with 2/3 of chilled trims and 1/3 of frozen trims. Prior grinding, one beef trim was contaminated with approximately 10 6 -10 7 CFU of E. coli O157:H7 on a surface of 0.5cm 2 to reach a concentration of 10-100cells/g in ground beef. The E. coli O157:H7 distribution in ground beef was characterized by enumerating 60 samples (20 samples of 5g, 20 samples of 25g and 20 samples of 100g) and fitting a Poisson-gamma model to describe the variability of bacterial counts. The shape parameter of the gamma distribution, also known as the dispersion parameter reflecting the amount of clustering, was estimated between 1.0 and 1.6. This k-value of approximately 1 expresses a moderate level of clustering of bacterial cells in the ground beef. The impact of this clustering on the performance of sampling strategies was relatively limited in comparison to the classical hypothesis of a random repartition of pathogenic cells in mixed materials (purely Poisson distribution instead of Poisson-gamma distribution). Copyright © 2017 Elsevier B.V. All rights reserved.

Effect Sizes in Three-Level Cluster-Randomized Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.

2011-01-01

Research designs involving cluster randomization are becoming increasingly important in educational and behavioral research. Many of these designs involve two levels of clustering or nesting (students within classes and classes within schools). Researchers would like to compute effect size indexes based on the standardized mean difference to…

The Role of School Culture and Basic Psychological Needs on Iranian Adolescents' Academic Alienation: A Multi-Level Examination

ERIC Educational Resources Information Center

Mahmoudi, Hojjat; Brown, Monica R.; Amani Saribagloo, Javad; Dadashzadeh, Shiva

2018-01-01

This aim of this current research was a multi-level analysis of the relationship between school culture, basic psychological needs, and adolescents' academic alienation. One thousand twenty-nine (N = 1,029) high school students from Qom City were randomly selected through a multi-phase cluster sampling method and answered questions regarding…

Individual and Familial Correlates of Career Salience among Upwardly Mobile College Women. Final Report.

ERIC Educational Resources Information Center

Guttmacher, Mary Johnson

A case study was conducted using a sample of 271 women selected from a state college by a stratified random cluster technique that approximates proportional representation of women in all four classes and all college majors. The data source was an extensive questionnaire designed to measure the attitudes and behavior of interest. The major…

Establishing the Baseline Height and Weight Status of New Hampshire Head Start Children, 2007-2008

ERIC Educational Resources Information Center

Blaney, David D.; Flynn, Regina T.; Martin, Nancy R.; Anderson, Ludmila

2010-01-01

We report on a standardized survey of height and weight status of children attending the New Hampshire Head Start Program during the 2007-2008 school year. Baseline prevalence estimates of overweight and obesity are needed for obesity prevention activities and intervention. We selected a random one-stage cluster sample and screened 629 children…

The Effect of School Bureaucracy on the Relationship between Principals' Leadership Practices and Teacher Commitment in Malaysia Secondary Schools

ERIC Educational Resources Information Center

Kean, Teoh Hong; Kannan, Sathiamoorthy; Piaw, Chua Yan

2017-01-01

The main aim of this research paper was to ascertain the relationship between principal leadership practices and teacher commitment. The study was conducted using quantitative survey questionnaire to 384 secondary school teachers, ranging from band 1 to band 6 in Malaysia using multi stage stratified cluster random sampling. This study was using…

Intraclass Correlation Coefficients for Obesity Indicators and Energy Balance-Related Behaviors Among New York City Public Elementary Schools.

PubMed

Gray, Heewon Lee; Burgermaster, Marissa; Tipton, Elizabeth; Contento, Isobel R; Koch, Pamela A; Di Noia, Jennifer

2016-04-01

Sample size and statistical power calculation should consider clustering effects when schools are the unit of randomization in intervention studies. The objective of the current study was to investigate how student outcomes are clustered within schools in an obesity prevention trial. Baseline data from the Food, Health & Choices project were used. Participants were 9- to 13-year-old students enrolled in 20 New York City public schools (n= 1,387). Body mass index (BMI) was calculated based on measures of height and weight, and body fat percentage was measured with a Tanita® body composition analyzer (Model SC-331s). Energy balance-related behaviors were self-reported with a frequency questionnaire. To examine the cluster effects, intraclass correlation coefficients (ICCs) were calculated as school variance over total variance for outcome variables. School-level covariates, percentage students eligible for free and reduced-price lunch, percentage Black or Hispanic, and English language learners were added in the model to examine ICC changes. The ICCs for obesity indicators are: .026 for BMI-percentile, .031 for BMIz-score, .035 for percentage of overweight students, .037 for body fat percentage, and .041 for absolute BMI. The ICC range for the six energy balance-related behaviors are .008 to .044 for fruit and vegetables, .013 to .055 for physical activity, .031 to .052 for recreational screen time, .013 to .091 for sweetened beverages, .033 to .121 for processed packaged snacks, and .020 to .083 for fast food. When school-level covariates were included in the model, ICC changes varied from -95% to 85%. This is the first study reporting ICCs for obesity-related anthropometric and behavioral outcomes among New York City public schools. The results of the study may aid sample size estimation for future school-based cluster randomized controlled trials in similar urban setting and population. Additionally, identifying school-level covariates that can reduce cluster effects is important when analyzing data. © 2015 Society for Public Health Education.

Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata

PubMed Central

Diniz, Daniel G.; Silva, Geane O.; Naves, Thaís B.; Fernandes, Taiany N.; Araújo, Sanderson C.; Diniz, José A. P.; de Farias, Luis H. S.; Sosthenes, Marcia C. K.; Diniz, Cristovam G.; Anthony, Daniel C.; da Costa Vasconcelos, Pedro F.; Picanço Diniz, Cristovam W.

2016-01-01

It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous. PMID:27047345

Hierarchical Cluster Analysis of Three-Dimensional Reconstructions of Unbiased Sampled Microglia Shows not Continuous Morphological Changes from Stage 1 to 2 after Multiple Dengue Infections in Callithrix penicillata.

PubMed

Diniz, Daniel G; Silva, Geane O; Naves, Thaís B; Fernandes, Taiany N; Araújo, Sanderson C; Diniz, José A P; de Farias, Luis H S; Sosthenes, Marcia C K; Diniz, Cristovam G; Anthony, Daniel C; da Costa Vasconcelos, Pedro F; Picanço Diniz, Cristovam W

2016-01-01

It is known that microglial morphology and function are related, but few studies have explored the subtleties of microglial morphological changes in response to specific pathogens. In the present report we quantitated microglia morphological changes in a monkey model of dengue disease with virus CNS invasion. To mimic multiple infections that usually occur in endemic areas, where higher dengue infection incidence and abundant mosquito vectors carrying different serotypes coexist, subjects received once a week subcutaneous injections of DENV3 (genotype III)-infected culture supernatant followed 24 h later by an injection of anti-DENV2 antibody. Control animals received either weekly anti-DENV2 antibodies, or no injections. Brain sections were immunolabeled for DENV3 antigens and IBA-1. Random and systematic microglial samples were taken from the polymorphic layer of dentate gyrus for 3-D reconstructions, where we found intense immunostaining for TNFα and DENV3 virus antigens. We submitted all bi- or multimodal morphological parameters of microglia to hierarchical cluster analysis and found two major morphological phenotypes designated types I and II. Compared to type I (stage 1), type II microglia were more complex; displaying higher number of nodes, processes and trees and larger surface area and volumes (stage 2). Type II microglia were found only in infected monkeys, whereas type I microglia was found in both control and infected subjects. Hierarchical cluster analysis of morphological parameters of 3-D reconstructions of random and systematic selected samples in control and ADE dengue infected monkeys suggests that microglia morphological changes from stage 1 to stage 2 may not be continuous.

The Effects of Including Observed Means or Latent Means as Covariates in Multilevel Models for Cluster Randomized Trials

ERIC Educational Resources Information Center

Aydin, Burak; Leite, Walter L.; Algina, James

2016-01-01

We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design.

PubMed

Lu, Tsui-Shan; Longnecker, Matthew P; Zhou, Haibo

2017-03-15

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data, and the general ODS design for a continuous response. While substantial work has been carried out for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome-dependent sampling (multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the multivariate-ODS or the estimator from a simple random sample with the same sample size. The multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of polychlorinated biphenyl exposure to hearing loss in children born to the Collaborative Perinatal Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Design of Cluster Randomized Trials with Random Cross-Classifications

ERIC Educational Resources Information Center

Moerbeek, Mirjam; Safarkhani, Maryam

2018-01-01

Data from cluster randomized trials do not always have a pure hierarchical structure. For instance, students are nested within schools that may be crossed by neighborhoods, and soldiers are nested within army units that may be crossed by mental health-care professionals. It is important that the random cross-classification is taken into account…

Factors that affect self-care behaviour of female high school students with dysmenorrhoea: a cluster sampling study.

PubMed

Chang, Shu-Fang; Chuang, Mei-hua

2012-04-01

The purpose of this study was to identify factors that affect the self-care behaviour of female high school students with dysmenorrhoea. This cross-sectional study utilized a questionnaire-based survey to understand the self-care behaviour of female high school students dysmenorrhoeal, along with the factors that affect this behaviour. A cluster random sampling method was adopted and questionnaires were used for data collection. Study participants experienced a moderate level of discomfort from dysmenorrhoea, and perceived dysmenorrhoea as serious. This investigation finds that cues to action raised perceived susceptibility to dysmenorrhoea and the perceived effectiveness of self-care behaviour and, therefore, increased the adoption of self-care behaviour. Hence, school nurses should offer female high school students numerous resources to apply correct self-care behaviour. © 2012 Blackwell Publishing Asia Pty Ltd.

Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases.

PubMed

Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M

2018-06-01

Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

An Observational Study of Blended Young Stellar Clusters in the Galactic Plane - Do Massive Stars form First?

NASA Astrophysics Data System (ADS)

Martínez-Galarza, Rafael; Protopapas, Pavlos; Smith, Howard A.; Morales, Esteban

2018-01-01

From an observational point of view, the early life of massive stars is difficult to understand partly because star formation occurs in crowded clusters where individual stars often appear blended together in the beams of infrared telescopes. This renders the characterization of the physical properties of young embedded clusters via spectral energy distribution (SED) fitting a challenging task. Of particular relevance for the testing of star formation models is the question of whether the claimed universality of the IMF (references) is reflected in an equally universal integrated galactic initial mass function (IGIMF) of stars. In other words, is the set of all stellar masses in the galaxy sampled from a single universal IMF, or does the distribution of masses depend on the environment, making the IGIMF different from the canonical IMF? If the latter is true, how different are the two? We present a infrared SED analysis of ~70 Spitzer-selected, low mass ($<100~\\rm{M}_{\\odot}$), galactic blended clusters. For all of the clusters we obtain the most probable individual SED of each member and derive their physical properties, effectively deblending the confused emission from individual YSOs. Our algorithm incorporates a combined probabilistic model of the blended SEDs and the unresolved images in the long-wavelength end. We find that our results are compatible with competitive accretion in the central regions of young clusters, with the most massive stars forming early on in the process and less massive stars forming about 1Myr later. We also find evidence for a relationship between the total stellar mass of the cluster and the mass of the most massive member that favors optimal sampling in the cluster and disfavors random sampling for the canonical IMF, implying that star formation is self-regulated, and that the mass of the most massive star in a cluster depends on the available resources. The method presented here is easily adapted to future observations of clustered regions of star formation with JWST and other high resolution facilities.

The Effect of Single or Repeated Home Visits on the Hanging and Use of Insecticide-Treated Mosquito Nets following a Mass Distribution Campaign - A Cluster Randomized, Controlled Trial

PubMed Central

Kilian, Albert; Balayo, Connie; Feldman, Mitra; Koenker, Hannah; Lokko, Kojo; Ashton, Ruth A.; Bruce, Jane; Lynch, Matthew; Boulay, Marc

2015-01-01

Background Study objective was to evaluate the effectiveness of commonly used post-campaign hang-up visits on the hanging and use of campaign nets. Methods A cluster-randomized trial was carried out in Uganda following an ITN distribution campaign. Five clusters (parishes, consisting of ∼11 villages each) were randomly selected for each of the three study arms with between 7,534 and 9,401 households per arm. Arm 1 received one hang-up visit, while Arm 2 received two visits by volunteers four and seven months after the campaign. Visits consisted of assistance hanging the net and education on net use. The control arm was only exposed to messages during the campaign itself. Three cross-sectional surveys with a two-stage cluster sampling design, representative of the study populations, were carried out to capture the two key outcome variables of net hanging and ITN use. Sample size was calculated to detect at least a 15 percentage-points change in net use, and was 1811 at endline. The analysis used an intention-to-treat approach. Findings Both hanging and use of ITN increased during follow-up in a similar way in all three study arms. The proportion of the population using an ITN the previous night was 64.0% (95% CI 60.8, 67.2), for one additional visit, 68.2% (63.8, 72.2) for two visits and 64.0% (59.4, 68.5) for the control. The proportion of households with all campaign nets hanging increased from 55.7% to 72.5% at endline (p<0.0005 for trend), with no difference between study arms. Financial cost per household visited was estimated as USD 2.33 for the first visit and USD 2.24 for the second. Conclusions Behavior change communication provided during the campaign or through other channels was sufficient to induce high levels of net hanging and use and additional “hang-up” activities were not cost-effective. PMID:25774676

Effectiveness of a self-management program for dual sensory impaired seniors in aged care settings: study protocol for a cluster randomized controlled trial.

PubMed

Roets-Merken, Lieve M; Graff, Maud J L; Zuidema, Sytse U; Hermsen, Pieter G J M; Teerenstra, Steven; Kempen, Gertrudis I J M; Vernooij-Dassen, Myrra J F J

2013-10-07

Five to 25 percent of residents in aged care settings have a combined hearing and visual sensory impairment. Usual care is generally restricted to single sensory impairment, neglecting the consequences of dual sensory impairment on social participation and autonomy. The aim of this study is to evaluate the effectiveness of a self-management program for seniors who acquired dual sensory impairment at old age. In a cluster randomized, single-blind controlled trial, with aged care settings as the unit of randomization, the effectiveness of a self-management program will be compared to usual care. A minimum of 14 and maximum of 20 settings will be randomized to either the intervention cluster or the control cluster, aiming to include a total of 132 seniors with dual sensory impairment. Each senior will be linked to a licensed practical nurse working at the setting. During a five to six month intervention period, nurses at the intervention clusters will be trained in a self-management program to support and empower seniors to use self-management strategies. In two separate diaries, nurses keep track of the interviews with the seniors and their reflections on their own learning process. Nurses of the control clusters offer care as usual. At senior level, the primary outcome is the social participation of the seniors measured using the Hearing Handicap Questionnaire and the Activity Card Sort, and secondary outcomes are mood, autonomy and quality of life. At nurse level, the outcome is job satisfaction. Effectiveness will be evaluated using linear mixed model analysis. The results of this study will provide evidence for the effectiveness of the Self-Management Program for seniors with dual sensory impairment living in aged care settings. The findings are expected to contribute to the knowledge on the program's potential to enhance social participation and autonomy of the seniors, as well as increasing the job satisfaction of the licensed practical nurses. Furthermore, an extensive process evaluation will take place which will offer insight in the quality and feasibility of the sampling and intervention process. If it is shown to be effective and feasible, this Self-Management Program could be widely disseminated. ClinicalTrials.gov, NCT01217502.

Effectiveness of a self-management program for dual sensory impaired seniors in aged care settings: study protocol for a cluster randomized controlled trial

PubMed Central

2013-01-01

Background Five to 25 percent of residents in aged care settings have a combined hearing and visual sensory impairment. Usual care is generally restricted to single sensory impairment, neglecting the consequences of dual sensory impairment on social participation and autonomy. The aim of this study is to evaluate the effectiveness of a self-management program for seniors who acquired dual sensory impairment at old age. Methods/Design In a cluster randomized, single-blind controlled trial, with aged care settings as the unit of randomization, the effectiveness of a self-management program will be compared to usual care. A minimum of 14 and maximum of 20 settings will be randomized to either the intervention cluster or the control cluster, aiming to include a total of 132 seniors with dual sensory impairment. Each senior will be linked to a licensed practical nurse working at the setting. During a five to six month intervention period, nurses at the intervention clusters will be trained in a self-management program to support and empower seniors to use self-management strategies. In two separate diaries, nurses keep track of the interviews with the seniors and their reflections on their own learning process. Nurses of the control clusters offer care as usual. At senior level, the primary outcome is the social participation of the seniors measured using the Hearing Handicap Questionnaire and the Activity Card Sort, and secondary outcomes are mood, autonomy and quality of life. At nurse level, the outcome is job satisfaction. Effectiveness will be evaluated using linear mixed model analysis. Discussion The results of this study will provide evidence for the effectiveness of the Self-Management Program for seniors with dual sensory impairment living in aged care settings. The findings are expected to contribute to the knowledge on the program’s potential to enhance social participation and autonomy of the seniors, as well as increasing the job satisfaction of the licensed practical nurses. Furthermore, an extensive process evaluation will take place which will offer insight in the quality and feasibility of the sampling and intervention process. If it is shown to be effective and feasible, this Self-Management Program could be widely disseminated. Clinical trials registration ClinicalTrials.gov, NCT01217502. PMID:24099315

Statistical design and analysis plan for an impact evaluation of an HIV treatment and prevention intervention for female sex workers in Zimbabwe: a study protocol for a cluster randomised controlled trial.

PubMed

Hargreaves, James R; Fearon, Elizabeth; Davey, Calum; Phillips, Andrew; Cambiano, Valentina; Cowan, Frances M

2016-01-05

Pragmatic cluster-randomised trials should seek to make unbiased estimates of effect and be reported according to CONSORT principles, and the study population should be representative of the target population. This is challenging when conducting trials amongst 'hidden' populations without a sample frame. We describe a pair-matched cluster-randomised trial of a combination HIV-prevention intervention to reduce the proportion of female sex workers (FSW) with a detectable HIV viral load in Zimbabwe, recruiting via respondent driven sampling (RDS). We will cross-sectionally survey approximately 200 FSW at baseline and at endline to characterise each of 14 sites. RDS is a variant of chain referral sampling and has been adapted to approximate random sampling. Primary analysis will use the 'RDS-2' method to estimate cluster summaries and will adapt Hayes and Moulton's '2-step' method to adjust effect estimates for individual-level confounders and further adjust for cluster baseline prevalence. We will adapt CONSORT to accommodate RDS. In the absence of observable refusal rates, we will compare the recruitment process between matched pairs. We will need to investigate whether cluster-specific recruitment or the intervention itself affects the accuracy of the RDS estimation process, potentially causing differential biases. To do this, we will calculate RDS-diagnostic statistics for each cluster at each time point and compare these statistics within matched pairs and time points. Sensitivity analyses will assess the impact of potential biases arising from assumptions made by the RDS-2 estimation. We are not aware of any other completed pragmatic cluster RCTs that are recruiting participants using RDS. Our statistical design and analysis approach seeks to transparently document participant recruitment and allow an assessment of the representativeness of the study to the target population, a key aspect of pragmatic trials. The challenges we have faced in the design of this trial are likely to be shared in other contexts aiming to serve the needs of legally and/or socially marginalised populations for which no sampling frame exists and especially when the social networks of participants are both the target of intervention and the means of recruitment. The trial was registered at Pan African Clinical Trials Registry (PACTR201312000722390) on 9 December 2013.

Non-Random Spatial Distribution of Impacts in the Stardust Cometary Collector

NASA Technical Reports Server (NTRS)

Westphal, Andrew J.; Bastien, Ronald K.; Borg, Janet; Bridges, John; Brownlee, Donald E.; Burchell, Mark J.; Cheng, Andrew F.; Clark, Benton C.; Djouadi, Zahia; Floss, Christine

2007-01-01

In January 2004, the Stardust spacecraft flew through the coma of comet P81/Wild2 at a relative speed of 6.1 km/sec. Cometary dust was collected at in a 0.1 sq m collector consisting of aerogel tiles and aluminum foils. Two years later, the samples successfully returned to earth and were recovered. We report the discovery that impacts in the Stardust cometary collector are not distributed randomly in the collecting media, but appear to be clustered on scales smaller than approx.10 cm. We also report the discovery of at least two populations of oblique tracks. We evaluated several hypotheses that could explain the observations. No hypothesis was consistent with all the observations, but the preponderance of evidence points toward at least one impact on the central Whipple shield of the spacecraft as the origin of both clustering and low-angle oblique tracks. High-angle oblique tracks unambiguously originate from a noncometary impact on the spacecraft bus just forward of the collector. Here we summarize the observations, and review the evidence for and against three scenarios that we have considered for explaining the impact clustering found on the Stardust aerogel and foil collectors.

Clustering behavior of hermit crabs (Decapoda, Anomura) in an intertidal rocky shore at São Sebastião, southeastern Brazil.

PubMed

Turra, A; Leite, F P

2000-02-01

The clustering behavior and cluster composition of hermit crabs as well as the patterns of shell utilization of clustered and scattered individuals were studied. This study was conducted in the intertidal region of Grande Beach, São Sebastião, southeastern Brazil. Samples were taken both in randomized transects and 1 m2 quadrats during low tide periods. Crabs were counted, measured (shield length), and sexed. Shells were identified and had their adequacy and condition (physical damage and incrustation) recorded. Clusters occurred mainly in air exposed areas and were dominated or composed only by Clibanarius antillensis. Other species like Paguristes tortugae, Pagurus criniticornis, and Calcinus tibicen were also present in these clusters, but in small numbers. Only one monospecific aggregation composed by individuals of P. criniticornis was recorded in tide pools. Almost all crabs were inactive, despite some that were submerged in tide pools. Most of the individuals of C. antillensis were clustered (70.88%). Scattered individuals were larger than clustered ones and occupied mainly shells of Tegula viridula, which seemed to be the most adequate shell to the crabs. Clustered individuals used less incrusted shells than isolated ones. In general, clustering in Grande Beach presented the same patterns of size and sex distribution, and shell utilization than others already studied, with the exception of the smaller cluster size registered in this area.

Textures in spinel peridotite mantle xenoliths using micro-CT scanning: Examples from Canary Islands and France

NASA Astrophysics Data System (ADS)

Bhanot, K. K.; Downes, H.; Petrone, C. M.; Humphreys-Williams, E.

2017-04-01

Spinel pyroxene-clusters, which are intergrowths of spinel, orthopyroxene and clinopyroxene in mantle xenoliths, have been investigated through the use of micro-CT (μ-CT) in this study. Samples have been studied from two different tectonic settings: (1) the northern Massif Central, France, an uplifted and rifted plateau on continental lithosphere and (2) Lanzarote in the Canary Islands, an intraplate volcanic island on old oceanic lithosphere. μ-CT analysis of samples from both locations has revealed a range of spinel textures from small < 2 mm microcrystals which can be either spatially concentrated or distributed more evenly throughout the rock with a lineation, to large 4-12 mm individual clusters with ellipsoidal complex vermicular textures in random orientation. Microprobe analyses of pyroxenes inside and outside the clusters show broadly similar compositions. Spinel-pyroxene clusters are the result of a transition of shallow lithospheric mantle from the garnet stability field to the spinel stability field. Both the northern Massif Central and Lanzarote are regions that have experienced significant lithospheric thinning. This process provides a mechanism where the sub-solidus reaction of olivine + garnet = orthopyroxene + clinopyroxene + spinel is satisfied by providing a pathway from garnet peridotite to spinel peridotite. We predict that such textures would only occur in the mantle beneath regions that show evidence of thinning of the lithospheric mantle. Metasomatic reactions are seen around spinel-pyroxene clusters in some Lanzarote xenoliths, so metasomatism post-dated cluster formation.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use.

PubMed

Babbin, Steven F; Velicer, Wayne F; Paiva, Andrea L; Brick, Leslie Ann D; Redding, Colleen A

2015-01-01

Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N=4059) and alcohol (N=3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. Copyright © 2014. Published by Elsevier Ltd.

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use

PubMed Central

Babbin, Steven F.; Velicer, Wayne F.; Paiva, Andrea L.; Brick, Leslie Ann D.; Redding, Colleen A.

2015-01-01

Introduction Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Methods Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N= 4059) and alcohol (N= 3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Results Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Conclusions Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. PMID:25222849

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2018-03-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2}). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3}) and the level sets of the Gaussian free field ({d≥ 3}). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2017-12-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2} ). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3} ) and the level sets of the Gaussian free field ({d≥ 3} ). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.

Fast clustering algorithm for large ECG data sets based on CS theory in combination with PCA and K-NN methods.

PubMed

Balouchestani, Mohammadreza; Krishnan, Sridhar

2014-01-01

Long-term recording of Electrocardiogram (ECG) signals plays an important role in health care systems for diagnostic and treatment purposes of heart diseases. Clustering and classification of collecting data are essential parts for detecting concealed information of P-QRS-T waves in the long-term ECG recording. Currently used algorithms do have their share of drawbacks: 1) clustering and classification cannot be done in real time; 2) they suffer from huge energy consumption and load of sampling. These drawbacks motivated us in developing novel optimized clustering algorithm which could easily scan large ECG datasets for establishing low power long-term ECG recording. In this paper, we present an advanced K-means clustering algorithm based on Compressed Sensing (CS) theory as a random sampling procedure. Then, two dimensionality reduction methods: Principal Component Analysis (PCA) and Linear Correlation Coefficient (LCC) followed by sorting the data using the K-Nearest Neighbours (K-NN) and Probabilistic Neural Network (PNN) classifiers are applied to the proposed algorithm. We show our algorithm based on PCA features in combination with K-NN classifier shows better performance than other methods. The proposed algorithm outperforms existing algorithms by increasing 11% classification accuracy. In addition, the proposed algorithm illustrates classification accuracy for K-NN and PNN classifiers, and a Receiver Operating Characteristics (ROC) area of 99.98%, 99.83%, and 99.75% respectively.

Population impact of a high cardiovascular risk management program delivered by village doctors in rural China: design and rationale of a large, cluster-randomized controlled trial.

PubMed

Yan, Lijing L; Fang, Weigang; Delong, Elizabeth; Neal, Bruce; Peterson, Eric D; Huang, Yining; Sun, Ningling; Yao, Chen; Li, Xian; MacMahon, Stephen; Wu, Yangfeng

2014-04-11

The high-risk strategy has been proven effective in preventing cardiovascular disease; however, the population benefits from these interventions remain unknown. This study aims to assess, at the population level, the effects of an evidence-based high cardiovascular risk management program delivered by village doctors in rural China. The study will employ a cluster-randomized controlled trial in which a total of 120 villages in five northern provinces of China, will be assigned to either intervention (60 villages) or control (60 villages). Village doctors in intervention villages will be trained to implement a simple evidence-based management program designed to identify, treat and follow-up as many as possible individuals at high-risk of cardiovascular disease in the village. The intervention will also include performance feedback as well as a performance-based incentive payment scheme and will last for 2 years. We will draw two different (independent) random samples, before and after the intervention, 20 men aged≥50 years and 20 women aged≥60 years from each village in each sample and a total of 9,600 participants from 2 samples to measure the study outcomes at the population level. The primary outcome will be the pre-post difference in mean systolic blood pressure, analyzed with a generalized estimating equations extension of linear regression model to account for cluster effect. Secondary outcomes will include monthly clinic visits, provision of lifestyle advice, use of antihypertensive medications and use of aspirin. Process and economic evaluations will also be conducted. This trial will be the first implementation trial in the world to evaluate the population impact of the high-risk strategy in prevention and control of cardiovascular disease. The results are expected to provide important information (effectiveness, cost-effectiveness, feasibility and acceptability) to guide policy making for rural China as well as other resource-limited countries. The trial is registered at ClinicalTrials.gov (NCT01259700). Date of initial registration is December 13, 2010.

Assessing map accuracy in a remotely sensed, ecoregion-scale cover map

USGS Publications Warehouse

Edwards, T.C.; Moisen, Gretchen G.; Cutler, D.R.

1998-01-01

Landscape- and ecoregion-based conservation efforts increasingly use a spatial component to organize data for analysis and interpretation. A challenge particular to remotely sensed cover maps generated from these efforts is how best to assess the accuracy of the cover maps, especially when they can exceed 1000 s/km2 in size. Here we develop and describe a methodological approach for assessing the accuracy of large-area cover maps, using as a test case the 21.9 million ha cover map developed for Utah Gap Analysis. As part of our design process, we first reviewed the effect of intracluster correlation and a simple cost function on the relative efficiency of cluster sample designs to simple random designs. Our design ultimately combined clustered and subsampled field data stratified by ecological modeling unit and accessibility (hereafter a mixed design). We next outline estimation formulas for simple map accuracy measures under our mixed design and report results for eight major cover types and the three ecoregions mapped as part of the Utah Gap Analysis. Overall accuracy of the map was 83.2% (SE=1.4). Within ecoregions, accuracy ranged from 78.9% to 85.0%. Accuracy by cover type varied, ranging from a low of 50.4% for barren to a high of 90.6% for man modified. In addition, we examined gains in efficiency of our mixed design compared with a simple random sample approach. In regard to precision, our mixed design was more precise than a simple random design, given fixed sample costs. We close with a discussion of the logistical constraints facing attempts to assess the accuracy of large-area, remotely sensed cover maps.

Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

NASA Astrophysics Data System (ADS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-07-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

NASA Technical Reports Server (NTRS)

Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

1994-01-01

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

A multicomponent matched filter cluster confirmation tool for eROSITA: initial application to the RASS and DES-SV data sets

NASA Astrophysics Data System (ADS)

Klein, M.; Mohr, J. J.; Desai, S.; Israel, H.; Allam, S.; Benoit-Lévy, A.; Brooks, D.; Buckley-Geer, E.; Carnero Rosell, A.; Carrasco Kind, M.; Cunha, C. E.; da Costa, L. N.; Dietrich, J. P.; Eifler, T. F.; Evrard, A. E.; Frieman, J.; Gruen, D.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; James, D. J.; Kuehn, K.; Lima, M.; Maia, M. A. G.; March, M.; Melchior, P.; Menanteau, F.; Miquel, R.; Plazas, A. A.; Reil, K.; Romer, A. K.; Sanchez, E.; Santiago, B.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Collaboration, the DES

2018-03-01

We describe a multicomponent matched filter (MCMF) cluster confirmation tool designed for the study of large X-ray source catalogues produced by the upcoming X-ray all-sky survey mission eROSITA. We apply the method to confirm a sample of 88 clusters with redshifts 0.05 < z < 0.8 in the recently published 2RXS catalogue from the ROSAT All-Sky Survey (RASS) over the 208 deg2 region overlapped by the Dark Energy Survey (DES) Science Verification (DES-SV) data set. In our pilot study, we examine all X-ray sources, regardless of their extent. Our method employs a multicolour red sequence (RS) algorithm that incorporates the X-ray count rate and peak position in determining the region of interest for follow-up and extracts the positionally and colour-weighted optical richness λMCMF as a function of redshift for each source. Peaks in the λMCMF-redshift distribution are identified and used to extract photometric redshifts, richness and uncertainties. The significances of all optical counterparts are characterized using the distribution of richnesses defined along random lines of sight. These significances are used to extract cluster catalogues and to estimate the contamination by random superpositions of unassociated optical systems. The delivered photometric redshift accuracy is δz/(1 + z) = 0.010. We find a well-defined X-ray luminosity-λMCMF relation with an intrinsic scatter of δln (λMCMF|Lx) = 0.21. Matching our catalogue with the DES-SV redMaPPer catalogue yields good agreement in redshift and richness estimates; comparing our catalogue with the South Pole Telescope (SPT) selected clusters shows no inconsistencies. SPT clusters in our data set are consistent with the high-mass extension of the RASS-based λMCMF-mass relation.

Interest of LQAS method in a survey of HTLV-I infection in Benin (West Africa).

PubMed

Houinato, Dismand; Preux, Pierre-Marie; Charriere, Bénédicte; Massit, Bruno; Avodé, Gilbert; Denis, François; Dumas, Michel; Boutros-Toni, Fernand; Salamon, Roger

2002-02-01

HTLV-I is heterogeneously distributed in Sub-Saharan Africa. Traditional survey methods as cluster sampling could provide information for a country or region of interest. However, they cannot identify small areas with higher prevalences of infection to help in the health policy planning. Identification of such areas could be done by a Lot Quality Assurance Sampling (LQAS) method, which is currently used in industry to identify a poor performance in assembly lines. The LQAS method was used in Atacora (Northern Benin) between March and May 1998 to identify areas with a HTLV-I seroprevalence higher than 4%. Sixty-five subjects were randomly selected in each of 36 communes (lots) of this department. Lots were classified as unacceptable when the sample contained at least one positive subject. The LQAS method identified 25 (69.4 %) communes with a prevalence higher than 4%. Using stratified sampling theory, the overall HTLV-I seroprevalence was 4.5% (95% CI: 3.6-5.4%). These data show the interest of LQAS method application under field conditions to detect clusters of infection.

Spatial design and strength of spatial signal: Effects on covariance estimation

USGS Publications Warehouse

Irvine, Kathryn M.; Gitelman, Alix I.; Hoeting, Jennifer A.

2007-01-01

In a spatial regression context, scientists are often interested in a physical interpretation of components of the parametric covariance function. For example, spatial covariance parameter estimates in ecological settings have been interpreted to describe spatial heterogeneity or “patchiness” in a landscape that cannot be explained by measured covariates. In this article, we investigate the influence of the strength of spatial dependence on maximum likelihood (ML) and restricted maximum likelihood (REML) estimates of covariance parameters in an exponential-with-nugget model, and we also examine these influences under different sampling designs—specifically, lattice designs and more realistic random and cluster designs—at differing intensities of sampling (n=144 and 361). We find that neither ML nor REML estimates perform well when the range parameter and/or the nugget-to-sill ratio is large—ML tends to underestimate the autocorrelation function and REML produces highly variable estimates of the autocorrelation function. The best estimates of both the covariance parameters and the autocorrelation function come under the cluster sampling design and large sample sizes. As a motivating example, we consider a spatial model for stream sulfate concentration.

Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…

Household costs of dengue illness: secondary outcomes from a randomised controlled trial of dengue prevention in Guerrero state, Mexico.

PubMed

Legorreta-Soberanis, José; Paredes-Solís, Sergio; Morales-Pérez, Arcadio; Nava-Aguilera, Elizabeth; Serrano-de Los Santos, Felipe René; Dimas-Garcia, Diana Lisseth; Ledogar, Robert J; Cockcroft, Anne; Andersson, Neil

2017-05-30

Dengue is a serious public health problem with an important economic impact. This study used data from a cluster randomised controlled trial of community mobilisation for dengue prevention to estimate the household costs of treatment of dengue illness. It examined the economic impact of the trial intervention in the three coastal regions of Mexico's Guerrero State. The 2010 baseline survey covered households in a random sample of 90 clusters in the coastal regions; the clusters were randomly allocated to intervention or control and re-surveyed in 2012. The surveys asked about dengue cases in the last 12 months, expenditures on their treatment, and work or school days lost by patients and care givers. We did not assign monetary value to days lost, since a lost day to a person of low earning power is of equal or higher value to that person than to one who earns more. The 12,312 households in 2010 reported 1020 dengue cases in the last 12 months (1.9% of the sample population). Most (78%) were ambulatory cases, with a mean cost of USD 51 and 10.8 work/school days, rising to USD 96 and 11.4 work/school days if treated by a private physician. Hospitalised cases cost USD 28-94 in government institutions and USD 392 in private hospitals (excluding additional inpatient charges), as well as 9.6-17.3 work/school days. Dengue cases cost households an estimated 412,825 work/school days throughout the three coastal regions. In the follow up survey, 6.1% (326/5349) of households in intervention clusters and 7.9% (405/5139) in control clusters reported at least one dengue case. The mean of days lost per case was similar in intervention and control clusters, but the number of days lost from dengue and all elements of costs for dengue cases per 1000 population were lower in intervention clusters. If the total population of the three coastal regions had received the intervention, some 149,401 work or school days lost per year could have been prevented. The economic effect of dengue on households, including lost work days, is substantial. The Camino Verde trial intervention reduced household costs for treatment of dengue cases. The trial was registered as ISRCTN:27,581,154 .

General Framework for Effect Sizes in Cluster Randomized Experiments

ERIC Educational Resources Information Center

VanHoudnos, Nathan

2016-01-01

Cluster randomized experiments are ubiquitous in modern education research. Although a variety of modeling approaches are used to analyze these data, perhaps the most common methodology is a normal mixed effects model where some effects, such as the treatment effect, are regarded as fixed, and others, such as the effect of group random assignment…

Improving Language Comprehension in Preschool Children with Language Difficulties: A Cluster Randomized Trial

ERIC Educational Resources Information Center

Hagen, Åste M.; Melby-Lervåg, Monica; Lervåg, Arne

2017-01-01

Background: Children with language comprehension difficulties are at risk of educational and social problems, which in turn impede employment prospects in adulthood. However, few randomized trials have examined how such problems can be ameliorated during the preschool years. Methods: We conducted a cluster randomized trial in 148 preschool…

The Walking School Bus and children's physical activity: A pilot cluster randomized controlled trial

USDA-ARS?s Scientific Manuscript database

To evaluate the impact of a "walking school bus" program on children's rates of active commuting to school and physical activity. We conducted a pilot cluster randomized controlled trial among 4th-graders from 8 schools in Houston, Texas (N = 149). Random allocation to treatment or control condition...

Quantifying the impact of fixed effects modeling of clusters in multiple imputation for cluster randomized trials

PubMed Central

Andridge, Rebecca. R.

2011-01-01

In cluster randomized trials (CRTs), identifiable clusters rather than individuals are randomized to study groups. Resulting data often consist of a small number of clusters with correlated observations within a treatment group. Missing data often present a problem in the analysis of such trials, and multiple imputation (MI) has been used to create complete data sets, enabling subsequent analysis with well-established analysis methods for CRTs. We discuss strategies for accounting for clustering when multiply imputing a missing continuous outcome, focusing on estimation of the variance of group means as used in an adjusted t-test or ANOVA. These analysis procedures are congenial to (can be derived from) a mixed effects imputation model; however, this imputation procedure is not yet available in commercial statistical software. An alternative approach that is readily available and has been used in recent studies is to include fixed effects for cluster, but the impact of using this convenient method has not been studied. We show that under this imputation model the MI variance estimator is positively biased and that smaller ICCs lead to larger overestimation of the MI variance. Analytical expressions for the bias of the variance estimator are derived in the case of data missing completely at random (MCAR), and cases in which data are missing at random (MAR) are illustrated through simulation. Finally, various imputation methods are applied to data from the Detroit Middle School Asthma Project, a recent school-based CRT, and differences in inference are compared. PMID:21259309

E-Rehabilitation - an Internet and mobile phone based tailored intervention to enhance self-management of cardiovascular disease: study protocol for a randomized controlled trial.

PubMed

Antypas, Konstantinos; Wangberg, Silje C

2012-07-09

Cardiac rehabilitation is very important for the recovery and the secondary prevention of cardiovascular disease, and one of its main strategies is to increase the level of physical activity. Internet and mobile phone based interventions have been successfully used to help people to achieve this. One of the components that are related to the efficacy of these interventions is tailoring of content to the individual. This trial is studying the effect of a longitudinally tailored Internet and mobile phone based intervention that is based on models of health behaviour, on the level of physical activity and the adherence to the intervention, as an extension of a face-to-face cardiac rehabilitation stay. A parallel group, cluster randomized controlled trial. The study population is adult participants of a cardiac rehabilitation programme in Norway with home Internet access and mobile phone, who in monthly clusters are randomized to the control or the intervention condition. Participants have access to a website with information regarding cardiac rehabilitation, an online discussion forum and an online activity calendar. Those randomized to the intervention condition, receive in addition tailored content based on models of health behaviour, through the website and mobile text messages. The objective is to assess the effect of the intervention on maintenance of self-management behaviours after the rehabilitation stay. Main outcome is the level of physical activity one month, three months and one year after the end of the cardiac rehabilitation programme. The randomization of clusters is based on a true random number online service, and participants, investigators and outcome assessor are blinded to the condition of the clusters. The study suggests a theory-based intervention that combines models of health behaviour in an innovative way, in order to tailor the delivered content. The users have been actively involved in its design, and because of the use of Open-Source software, the intervention can easily and at low-cost be reproduced and expanded by others. Challenges are the recruitment in the elderly population and the possible underrepresentation of women in the study sample. Funding by Northern Norway Regional Health Authority. Trial registry http://www.clinicaltrials.gov: NCT01223170.

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

DOE PAGES

Gatti, M.

2018-02-22

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric red- shifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We also apply the method to three photo-z codes run in our simulated data: Bayesian Photometric Redshift (BPZ), Directional Neighborhoodmore » Fitting (DNF), and Random Forest-based photo-z (RF). We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-z's. The systematic uncertainty in the mean redshift bias of the source galaxy sample is z ≲ 0.02, though the precise value depends on the redshift bin under consideration. Here, we discuss possible ways to mitigate the impact of our dominant systematics in future analyses.« less

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

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

Gatti, M.

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric red- shifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We also apply the method to three photo-z codes run in our simulated data: Bayesian Photometric Redshift (BPZ), Directional Neighborhoodmore » Fitting (DNF), and Random Forest-based photo-z (RF). We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-z's. The systematic uncertainty in the mean redshift bias of the source galaxy sample is z ≲ 0.02, though the precise value depends on the redshift bin under consideration. Here, we discuss possible ways to mitigate the impact of our dominant systematics in future analyses.« less

An adaptive clustering algorithm for image matching based on corner feature

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

Impacts of an Enhanced Family Health and Sexuality Module of the HealthTeacher Middle School Curriculum: A Cluster Randomized Trial

PubMed Central

Scott, Mindy E.; Cook, Elizabeth

2016-01-01

Objectives. To evaluate the impacts of an enhanced version of the Family Life and Sexuality Module of the HealthTeacher middle school curriculum. Methods. We conducted a cluster randomized trial of Chicago, Illinois, middle schools. We randomly assigned schools to a treatment group that received the intervention during the 2010–2011 school year or a control group that did not. The primary analysis sample included 595 students (7 schools) in the treatment group and 594 students (7 schools) in the control group. Results. Students in the treatment schools reported greater exposure to information on reproductive health topics such as sexually transmitted infections (STIs; 78% vs 60%; P < .01), abstinence (64% vs 37%; P < .01), and birth control (45% vs 29%; P < .01). They also reported higher average scores on an index of knowledge of contraceptive methods and STI transmission (0.5 vs 0.3; P = .02). We found no statistically significant differences in rates of sexual intercourse (12% vs 12%; P = .99), oral sex (12% vs 9%; P = .18), or other intermediate outcomes. Conclusions. The program had modest effects when tested among Chicago middle school students. PMID:27689479

Strengthening referral of sick children from the private health sector and its impact on referral uptake in Uganda: a cluster randomized controlled trial protocol.

PubMed

Buregyeya, Esther; Rutebemberwa, Elizeus; LaRussa, Philip; Mbonye, Anthony

2016-11-11

Uganda's under-five mortality is high, currently estimated at 66/1000 live births. Poor referral of sick children that seek care from the private sector is one of the contributory factors. The proposed intervention aims to improve referral and uptake of referral advice for children that seek care from private facilities (registered drug shops/private clinics). A cluster randomized design will be applied to test the intervention in Mukono District, central Uganda. A sample of study clusters will implement the intervention. The intervention will consist of three components: i) raising awareness in the community: village health teams will discuss the importance of referral and encourage households to save money, ii) training and supervision of providers in the private sector to diagnose, treat and refer sick children, iii) regular meetings between the public and private providers (convened by the district health team) to discuss the referral system. Twenty clusters will be included in the study, randomized in the ratio of 1:1. A minimum of 319 sick children per cluster and the total number of sick children to be recruited from all clusters will be 8910; adjusting for a 10 % loss to follow up and possible withdrawal of private outlets. The immediate sustainable impact will be appropriate treatment of sick children. The intervention is likely to impact on private sector practices since the scope of the services they provide will have expanded. The proposed study is also likely to have an impact on families as; i) they may appreciate the importance of timely referral on child illness management, ii) the cost savings related to reduced morbidity will be used by household to access other social services. The linkage between the private and public sectors will create a potential avenue for delivery of other public health interventions and improved working relations in the two sectors. Further, improved quality of services in the private sector will improve provider confidence and hopefully more clientelle to the private practices. NCT02450630 Registration date: May/9 th /2015.

Reducing the psychosocial impact of aphasia on mood and quality of life in people with aphasia and the impact of caregiving in family members through the Aphasia Action Success Knowledge (Aphasia ASK) program: study protocol for a randomized controlled trial.

PubMed

Worrall, Linda; Ryan, Brooke; Hudson, Kyla; Kneebone, Ian; Simmons-Mackie, Nina; Khan, Asaduzzaman; Hoffmann, Tammy; Power, Emma; Togher, Leanne; Rose, Miranda

2016-03-22

People with aphasia and their family members are at high risk of experiencing post stroke depression. The impact of early interventions on mood and quality of life for people with aphasia is unknown. This study will determine whether an early intervention for both the person with aphasia after stroke and their family members leads to better mood and quality of life outcomes for people with aphasia, and less caregiver burden and better mental health for their family members. This is a multicenter, cluster-randomized controlled trial. Clusters, which are represented by Health Service Districts, will be randomized to the experimental intervention (Aphasia Action Success Knowledge Program) or an attention control (Secondary Stroke Prevention Information Program). People with aphasia and their family members will be blinded to the study design and treatment allocation (that is, will not know there are two arms to the study). Both arms of the study will receive usual care in addition to either the experimental or the attention control intervention. A total of 344 people with aphasia and their family members will be recruited. Considering a cluster size of 20, the required sample size can be achieved from 18 clusters. However, 20 clusters will be recruited to account for the potential of cluster attrition during the study. Primary outcome measures will be mood and quality of life of people with aphasia at 12 months post stroke. Secondary measures will be family member outcomes assessing the impact of caregiving and mental health, and self-reported stroke risk-related behaviors of people with aphasia. This is the first known program tailored for people with aphasia and their family members that aims to prevent depression in people with aphasia by providing intervention early after the stroke. This trial is registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) as ACTRN12614000979651 . Date registered: 11 September 2014.

Refining a complex diagnostic construct: subtyping Dysthymia with the Shedler-Westen Assessment Procedure-II.

PubMed

Huprich, Steven K; Defife, Jared; Westen, Drew

2014-01-01

We sought to determine whether meaningful subtypes of Dysthymic patients could be identified when grouping them by similar personality profiles. A random, national sample of psychiatrists and clinical psychologists (n=1201) described a randomly selected current patient with personality pathology using the descriptors in the Shedler-Westen Assessment Procedure-II (SWAP-II), completed assessments of patients' adaptive functioning, and provided DSM-IV Axis I and II diagnoses. We applied Q-factor cluster analyses to those patients diagnosed with Dysthymic Disorder. Four clusters were identified-High Functioning, Anxious/Dysphoric, Emotionally Dysregulated, and Narcissistic. These factor scores corresponded with a priori hypotheses regarding diagnostic comorbidity and level of adaptive functioning. We compared these groups to diagnostic constructs described and empirically identified in the past literature. The results converge with past and current ideas about the ways in which chronic depression and personality are related and offer an enhanced means by which to understand a heterogeneous diagnostic category that is empirically grounded and clinically useful. © 2013 Published by Elsevier B.V.

HIV risk reduction intervention among traditionally circumcised young men in South Africa: a cluster randomized control trial.

PubMed

Peltzer, Karl; Simbayi, Leickness; Banyini, Mercy; Kekana, Queen

2011-01-01

The aim of this study was to test a 180-minute group HIV risk-reduction counseling intervention trial with men undergoing traditional circumcision in South Africa to reduce behavioral disinhibition (false security) as a result of the procedure. A cluster randomized controlled trial design was employed using a sample of 160 men, 80 in the experimental group and 80 in the control group. Comparisons between baseline and 3-month follow-up assessments on key behavioral outcomes were completed. We found that behavioral intentions, risk-reduction skills, and male role norms did not change in the experimental compared to the control condition. However, HIV-related stigma beliefs were significantly reduced in both conditions over time. These findings show that one small-group HIV risk-reduction intervention did not reduce sexual risk behaviors in recently traditionally circumcised men at high risk for behavioral disinhibition. Copyright © 2011 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Poverty and blindness in Pakistan: results from the Pakistan national blindness and visual impairment survey.

PubMed

Gilbert, Clare E; Shah, S P; Jadoon, M Z; Bourne, R; Dineen, B; Khan, M A; Johnson, G J; Khan, M D

2008-01-05

To explore the association between blindness and deprivation in a nationally representative sample of adults in Pakistan. Cross sectional population based survey. 221 rural and urban clusters selected randomly throughout Pakistan. Nationally representative sample of 16 507 adults aged 30 or above (95.3% response rate). Associations between visual impairment and poverty assessed by a cluster level deprivation index and a household level poverty indicator; prevalence and causes of blindness; measures of the rate of uptake and quality of eye care services. 561 blind participants (<3/60 in the better eye) were identified during the survey. Clusters in urban Sindh province were the most affluent, whereas rural areas in Balochistan were the poorest. The prevalence of blindness in adults living in affluent clusters was 2.2%, compared with 3.7% in medium clusters and 3.9% in poor clusters (P<0.001 for affluent v poor). The highest prevalence of blindness was found in rural Balochistan (5.2%). The prevalence of total blindness (bilateral no light perception) was more than three times higher in poor clusters than in affluent clusters (0.24% v 0.07%, P<0.001). The prevalences of blindness caused by cataract, glaucoma, and corneal opacity were lower in affluent clusters and households. Reflecting access to eye care services, cataract surgical coverage was higher in affluent clusters (80.6%) than in medium (76.8%) and poor areas (75.1%). Intraocular lens implantation rates were significantly lower in participants from poorer households. 10.2% of adults living in affluent clusters presented to the examination station wearing spectacles, compared with 6.7% in medium clusters and 4.4% in poor cluster areas. Spectacle coverage in affluent areas was more than double that in poor clusters (23.5% v 11.1%, P<0.001). Blindness is associated with poverty in Pakistan; lower access to eye care services was one contributory factor. To reduce blindness, strategies targeting poor people will be needed. These interventions may have an impact on deprivation in Pakistan.

Does poverty alleviation decrease depression symptoms in post-conflict settings? A cluster-randomized trial of microenterprise assistance in Northern Uganda.

PubMed

Green, E P; Blattman, C; Jamison, J; Annan, J

2016-01-01

By 2009, two decades of war and widespread displacement left the majority of the population of Northern Uganda impoverished. This study used a cluster-randomized design to test the hypothesis that a poverty alleviation program would improve economic security and reduce symptoms of depression in a sample of mostly young women. Roughly 120 villages in Northern Uganda were invited to participate. Community committees were asked to identify the most vulnerable women (and some men) to participate. The implementing agency screened all proposed participants, and a total of 1800 were enrolled. Following a baseline survey, villages were randomized to a treatment or wait-list control group. Participants in treatment villages received training, start-up capital, and follow-up support. Participants, implementers, and data collectors were not blinded to treatment status. Villages were randomized to the treatment group (60 villages with 896 participants) or the wait-list control group (60 villages with 904 participants) with an allocation ration of 1:1. All clusters participated in the intervention and were included in the analysis. The intent-to-treat analysis included 860 treatment participants and 866 control participants (4.1% attrition). Sixteen months after the program, monthly cash earnings doubled from UGX 22 523 to 51 124, non-household and non-farm businesses doubled, and cash savings roughly quadrupled. There was no measurable effect on a locally derived measure of symptoms of depression. Despite finding large increases in business, income, and savings among the treatment group, we do not find support for an indirect effect of poverty alleviation on symptoms of depression.

Quasi-Likelihood Techniques in a Logistic Regression Equation for Identifying Simulium damnosum s.l. Larval Habitats Intra-cluster Covariates in Togo.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent; Sanfo, Moussa S; Afriyie, Abena N; Ibrahim, Mohammed A; Griffith, Daniel A; Unnasch, Thomas R

2012-01-01

The standard methods for regression analyses of clustered riverine larval habitat data of Simulium damnosum s.l. a major black-fly vector of Onchoceriasis, postulate models relating observational ecological-sampled parameter estimators to prolific habitats without accounting for residual intra-cluster error correlation effects. Generally, this correlation comes from two sources: (1) the design of the random effects and their assumed covariance from the multiple levels within the regression model; and, (2) the correlation structure of the residuals. Unfortunately, inconspicuous errors in residual intra-cluster correlation estimates can overstate precision in forecasted S.damnosum s.l. riverine larval habitat explanatory attributes regardless how they are treated (e.g., independent, autoregressive, Toeplitz, etc). In this research, the geographical locations for multiple riverine-based S. damnosum s.l. larval ecosystem habitats sampled from 2 pre-established epidemiological sites in Togo were identified and recorded from July 2009 to June 2010. Initially the data was aggregated into proc genmod. An agglomerative hierarchical residual cluster-based analysis was then performed. The sampled clustered study site data was then analyzed for statistical correlations using Monthly Biting Rates (MBR). Euclidean distance measurements and terrain-related geomorphological statistics were then generated in ArcGIS. A digital overlay was then performed also in ArcGIS using the georeferenced ground coordinates of high and low density clusters stratified by Annual Biting Rates (ABR). This data was overlain onto multitemporal sub-meter pixel resolution satellite data (i.e., QuickBird 0.61m wavbands ). Orthogonal spatial filter eigenvectors were then generated in SAS/GIS. Univariate and non-linear regression-based models (i.e., Logistic, Poisson and Negative Binomial) were also employed to determine probability distributions and to identify statistically significant parameter estimators from the sampled data. Thereafter, Durbin-Watson test statistics were used to test the null hypothesis that the regression residuals were not autocorrelated against the alternative that the residuals followed an autoregressive process in AUTOREG. Bayesian uncertainty matrices were also constructed employing normal priors for each of the sampled estimators in PROC MCMC. The residuals revealed both spatially structured and unstructured error effects in the high and low ABR-stratified clusters. The analyses also revealed that the estimators, levels of turbidity and presence of rocks were statistically significant for the high-ABR-stratified clusters, while the estimators distance between habitats and floating vegetation were important for the low-ABR-stratified cluster. Varying and constant coefficient regression models, ABR- stratified GIS-generated clusters, sub-meter resolution satellite imagery, a robust residual intra-cluster diagnostic test, MBR-based histograms, eigendecomposition spatial filter algorithms and Bayesian matrices can enable accurate autoregressive estimation of latent uncertainity affects and other residual error probabilities (i.e., heteroskedasticity) for testing correlations between georeferenced S. damnosum s.l. riverine larval habitat estimators. The asymptotic distribution of the resulting residual adjusted intra-cluster predictor error autocovariate coefficients can thereafter be established while estimates of the asymptotic variance can lead to the construction of approximate confidence intervals for accurately targeting productive S. damnosum s.l habitats based on spatiotemporal field-sampled count data.

E-learning or educational leaflet: does it make a difference in oral health promotion? A clustered randomized trial.

PubMed

Al Bardaweel, Susan; Dashash, Mayssoon

2018-05-10

The early recognition of technology together with great ability to use computers and smart systems have promoted researchers to investigate the possibilities of utilizing technology for improving health care in children. The aim of this study was to compare between the traditional educational leaflets and E-applications in improving oral health knowledge, oral hygiene and gingival health in schoolchildren of Damascus city, Syria. A clustered randomized controlled trial at two public primary schools was performed. About 220 schoolchildren aged 10-11 years were included in this study and grouped into two clusters. Children in Leaflet cluster received oral health education through leaflets, while children in E-learning cluster received oral health education through an E-learning program. A questionnaire was designed to register information related to oral health knowledge and to record Plaque and Gingival indices. Questionnaire administration and clinical assessment were undertaken at baseline, 6 and at 12 weeks of oral health education. Data was analysed using one way repeated measures ANOVA, post hoc Bonferroni test and independent samples t-test. Leaflet cluster (107 participants) had statistically significant better oral health knowledge than E-learning cluster (104 participants) at 6 weeks (P < 0.05) and at 12 weeks (P < 0.05) (Leaflet cluster:100 participants, E-learning cluster:100 participants). The mean knowledge gain compared to baseline was higher in Leaflet cluster than in E-learning cluster. A significant reduction in the PI means at 6 weeks and 12 weeks was observed in both clusters (P < 0.05) when compared to baseline. Children in Leaflet cluster had significantly less plaque than those in E-learning cluster at 6 weeks (P < 0.05) and at 12 weeks (P < 0.05). Similarly, a significant reduction in the GI means at 6 weeks and 12 weeks was observed in both clusters when compared to baseline (P < 0.05). Children in Leaflet cluster had statistically significant better gingival health than E-learning cluster at 6 weeks (P < 0.05) and 12 weeks (P < 0.05). Traditional educational leaflets are an effective tool in the improvement of both oral health knowledge as well as clinical indices of oral hygiene and care among Syrian children. Leaflets can be used in school-based oral health education for a positive outcome. Australian New Zealand Clinical Trials Registry ( ACTRN12618000395235 ), Date registered: 16/03/2018, retrospectively registered.

Determining the Number of Clusters in a Data Set Without Graphical Interpretation

NASA Technical Reports Server (NTRS)

Aguirre, Nathan S.; Davies, Misty D.

2011-01-01

Cluster analysis is a data mining technique that is meant ot simplify the process of classifying data points. The basic clustering process requires an input of data points and the number of clusters wanted. The clustering algorithm will then pick starting C points for the clusters, which can be either random spatial points or random data points. It then assigns each data point to the nearest C point where "nearest usually means Euclidean distance, but some algorithms use another criterion. The next step is determining whether the clustering arrangement this found is within a certain tolerance. If it falls within this tolerance, the process ends. Otherwise the C points are adjusted based on how many data points are in each cluster, and the steps repeat until the algorithm converges,

A Cluster-Randomized Trial of Restorative Practices: An Illustration to Spur High-Quality Research and Evaluation

ERIC Educational Resources Information Center

Acosta, Joie D.; Chinman, Matthew; Ebener, Patricia; Phillips, Andrea; Xenakis, Lea; Malone, Patrick S.

2016-01-01

Restorative practices in schools lack rigorous evaluation studies. As an example of rigorous school-based research, this article describes the first randomized control trial of restorative practices to date, the Study of Restorative Practices. It is a 5-year, cluster-randomized controlled trial (RCT) of the Restorative Practices Intervention (RPI)…

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects

PubMed Central

2012-01-01

Background Time-course gene expression data such as yeast cell cycle data may be periodically expressed. To cluster such data, currently used Fourier series approximations of periodic gene expressions have been found not to be sufficiently adequate to model the complexity of the time-course data, partly due to their ignoring the dependence between the expression measurements over time and the correlation among gene expression profiles. We further investigate the advantages and limitations of available models in the literature and propose a new mixture model with autoregressive random effects of the first order for the clustering of time-course gene-expression profiles. Some simulations and real examples are given to demonstrate the usefulness of the proposed models. Results We illustrate the applicability of our new model using synthetic and real time-course datasets. We show that our model outperforms existing models to provide more reliable and robust clustering of time-course data. Our model provides superior results when genetic profiles are correlated. It also gives comparable results when the correlation between the gene profiles is weak. In the applications to real time-course data, relevant clusters of coregulated genes are obtained, which are supported by gene-function annotation databases. Conclusions Our new model under our extension of the EMMIX-WIRE procedure is more reliable and robust for clustering time-course data because it adopts a random effects model that allows for the correlation among observations at different time points. It postulates gene-specific random effects with an autocorrelation variance structure that models coregulation within the clusters. The developed R package is flexible in its specification of the random effects through user-input parameters that enables improved modelling and consequent clustering of time-course data. PMID:23151154

Leveraging contact network structure in the design of cluster randomized trials.

PubMed

Harling, Guy; Wang, Rui; Onnela, Jukka-Pekka; De Gruttola, Victor

2017-02-01

In settings like the Ebola epidemic, where proof-of-principle trials have provided evidence of efficacy but questions remain about the effectiveness of different possible modes of implementation, it may be useful to conduct trials that not only generate information about intervention effects but also themselves provide public health benefit. Cluster randomized trials are of particular value for infectious disease prevention research by virtue of their ability to capture both direct and indirect effects of intervention, the latter of which depends heavily on the nature of contact networks within and across clusters. By leveraging information about these networks-in particular the degree of connection across randomized units, which can be obtained at study baseline-we propose a novel class of connectivity-informed cluster trial designs that aim both to improve public health impact (speed of epidemic control) and to preserve the ability to detect intervention effects. We several designs for cluster randomized trials with staggered enrollment, in each of which the order of enrollment is based on the total number of ties (contacts) from individuals within a cluster to individuals in other clusters. Our designs can accommodate connectivity based either on the total number of external connections at baseline or on connections only to areas yet to receive the intervention. We further consider a "holdback" version of the designs in which control clusters are held back from re-randomization for some time interval. We investigate the performance of these designs in terms of epidemic control outcomes (time to end of epidemic and cumulative incidence) and power to detect intervention effect, by simulating vaccination trials during an SEIR-type epidemic outbreak using a network-structured agent-based model. We compare results to those of a traditional Stepped Wedge trial. In our simulation studies, connectivity-informed designs lead to a 20% reduction in cumulative incidence compared to comparable traditional study designs, but have little impact on epidemic length. Power to detect intervention effect is reduced in all connectivity-informed designs, but "holdback" versions provide power that is very close to that of a traditional Stepped Wedge approach. Incorporating information about cluster connectivity in the design of cluster randomized trials can increase their public health impact, especially in acute outbreak settings. Using this information helps control outbreaks-by minimizing the number of cross-cluster infections-with very modest cost in terms of power to detect effectiveness.

Stability of Special Education Eligibility from Kindergarten to Third Grade: Are There Variables from Fall of Kindergarten That Predict Later Classification Status?

ERIC Educational Resources Information Center

Flynn, Kylie Shawn

2012-01-01

This study examined students' movement in and out of special education and predictors for later special education placement. The sample ( N = 556) came from a response to intervention (RTI) study, specifically, a cluster-randomized control field trial that undertook the development and study of a hybrid Tier 1 (classroom instruction) and Tier 2…

Accuracy assessments and areal estimates using two-phase stratified random sampling, cluster plots, and the multivariate composite estimator

Treesearch

Raymond L. Czaplewski

2000-01-01

Consider the following example of an accuracy assessment. Landsat data are used to build a thematic map of land cover for a multicounty region. The map classifier (e.g., a supervised classification algorithm) assigns each pixel into one category of land cover. The classification system includes 12 different types of forest and land cover: black spruce, balsam fir,...

1979 Reserve Force Studies Surveys: User’s Manual and Codebooks.

DTIC Science & Technology

1981-09-01

units, for instance, artillery, which have the same manpower demand characteristics (similar size, skills and grade structure) provided better...personnel groups. With random cluster sampling, the pattern of questionnaire returns for each group of analytic interest should match the Guard and...marking the matching bubbles. First, although the instructions ask the respondent to "zero-fill" and "right-justify," some respondents entered the value

What Works in Gifted Education Mathematics Study: Impact of Pre-Differentiated and Enriched Curricula on General Education Teachers and Their Students. Research Monograph Series. RM13242

ERIC Educational Resources Information Center

Gubbins, E. Jean; McCoach, D. Betsy; Foreman, Jennifer L.; Gilson, Cindy M.; Bruce-Davis, Micah N.; Rubenstein, Lisa DaVia; Savino, Jennifer; Rambo, Karen; Waterman, Craig

2013-01-01

The present study seeks to determine how exposure to pre-differentiated and enriched curricula incorporating educative curriculum materials affects students' achievement as well as teacher and administrator responses to the intervention. A 2-year multi-site cluster randomized control trial study recruited a national sample of 4,530 grade 3…

Prevalence of latent tuberculous infection among adults in the general population of Ca Mau, Viet Nam.

PubMed

Marks, G B; Nhung, N V; Nguyen, T A; Hoa, N B; Khoa, T H; Son, N V; Phuong, N T B; Tin, D M; Ho, J; Fox, G J

2018-03-01

The study was conducted in a randomly selected sample of persons aged 15 years living in Ca Mau Province, southern Viet Nam. To estimate the prevalence of latent tuberculous infection (LTBI) in the general adult population of this province of Viet Nam. The secondary objective was to examine age and sex differences in prevalence. A cross-sectional survey was conducted in a cluster-random sample of the population. Clusters were subcommunes. The presence of LTBI was assessed using the QuantiFERON®-TB Gold In-Tube test system. QuantiFERON tests were performed among 1319 persons aged 15 years (77.7% of those selected). The overall prevalence of positive tests was 36.8% (95%CI 33.4-40.3). The prevalence of a positive test was lower in females than in males (31.0% vs. 44.7%, OR 0.57, 95%CI 0.45-0.72, P < 0.0001). The prevalence of positive tests increased with increasing age quintile (P < 0.0001). More than one third of the general adult population in a province in southern Viet Nam have evidence of LTBI. Although LTBI prevalence is higher in males, the sex difference is not as great as that for TB notification rates.

Knowledge and attitude towards total knee arthroplasty among the public in Saudi Arabia: a nationwide population-based study.

PubMed

Al-Mohrej, Omar A; Alshammari, Faris O; Aljuraisi, Abdulrahman M; Bin Amer, Lujain A; Masuadi, Emad M; Al-Kenani, Nader S

2018-04-01

Studies on total knee arthroplasty (TKA) in Saudi Arabia are scarce, and none have reported the knowledge and attitude of the procedure in Saudi Arabia. Our study aims to measure the knowledge and attitude of TKA among the adult Saudi population. To encompass a representative sample of this cross-sectional survey, all 13 administrative areas were used as ready-made geographical clusters. For each cluster, stratified random sampling was performed to maximize participation in the study. In each area, random samples of mobile phone numbers were selected with a probability proportional to the administrative area population size. Sample size calculation was based on the assumption that 50% of the participants would have some level of knowledge, with a 2% margin of error and 95% confidence level. To reach our intended sample size of 1540, we contacted 1722 participants with a response rate of 89.4%. The expected percentage of public knowledge was 50%; however, the actual percentage revealed by this study was much lower (29.7%). A stepwise multiple logistic regression was used to assess the factors that positively affected the knowledge score regarding TKA. Age [P = 0.016 with OR of 0.47], higher income [P = 0.001 with OR of 0.52] and participants with a positive history of TKA or that have known someone who underwent the surgery [P < 0.001 with OR of 0.15] had a positive impact on the total knowledge score. There are still misconceptions among the public in Saudi Arabia concerning TKA, its indications and results. We recommend that doctors use the results of our survey to assess their conversations with their patients, and to determine whether the results of the procedure are adequately clarified.

Micro-Loans, Insecticide-Treated Bednets, and Malaria: Evidence from a Randomized Controlled Trial in Orissa, India.

PubMed

Tarozzi, Alessandro; Mahajan, Aprajit; Blackburn, Brian; Kopf, Dan; Krishnan, Lakshmi; Yoong, Joanne

2014-07-01

We describe findings from the first large-scale cluster randomized controlled trial in a developing country that evaluates the uptake of a health-protecting technology, insecticide-treated bednets (ITNs), through micro-consumer loans, as compared to free distribution and control conditions. Despite a relatively high price, 52 percent of sample households purchased ITNs, highlighting the role of liquidity constraints in explaining earlier low adoption rates. We find mixed evidence of improvements in malaria indices. We interpret the results and their implications within the debate about cost sharing, sustainability and liquidity constraints in public health initiatives in developing countries.

Behavioral Contexts, Food-Choice Coping Strategies, and Dietary Quality of a Multiethnic Sample of Employed Parents

PubMed Central

Blake, Christine E.; Wethington, Elaine; Farrell, Tracy J.; Bisogni, Carole A.; Devine, Carol M.

2012-01-01

Employed parents’ work and family conditions provide behavioral contexts for their food choices. Relationships between employed parents’ food-choice coping strategies, behavioral contexts, and dietary quality were evaluated. Data on work and family conditions, sociodemographic characteristics, eating behavior, and dietary intake from two 24-hour dietary recalls were collected in a random sample cross-sectional pilot telephone survey in the fall of 2006. Black, white, and Latino employed mothers (n=25) and fathers (n=25) were recruited from a low/moderate income urban area in upstate New York. Hierarchical cluster analysis (Ward’s method) identified three clusters of parents differing in use of food-choice coping strategies (ie, Individualized Eating, Missing Meals, and Home Cooking). Cluster sociodemographic, work, and family characteristics were compared using χ2 and Fisher’s exact tests. Cluster differences in dietary quality (Healthy Eating Index 2005) were analyzed using analysis of variance. Clusters differed significantly (P≤0.05) on food-choice coping strategies, dietary quality, and behavioral contexts (ie, work schedule, marital status, partner’s employment, and number of children). Individualized Eating and Missing Meals clusters were characterized by nonstandard work hours, having a working partner, single parenthood and with family meals away from home, grabbing quick food instead of a meal, using convenience entrées at home, and missing meals or individualized eating. The Home Cooking cluster included considerably more married fathers with nonemployed spouses and more home-cooked family meals. Food-choice coping strategies affecting dietary quality reflect parents’ work and family conditions. Nutritional guidance and family policy needs to consider these important behavioral contexts for family nutrition and health. PMID:21338739

Behavioral contexts, food-choice coping strategies, and dietary quality of a multiethnic sample of employed parents.

PubMed

Blake, Christine E; Wethington, Elaine; Farrell, Tracy J; Bisogni, Carole A; Devine, Carol M

2011-03-01

Employed parents' work and family conditions provide behavioral contexts for their food choices. Relationships between employed parents' food-choice coping strategies, behavioral contexts, and dietary quality were evaluated. Data on work and family conditions, sociodemographic characteristics, eating behavior, and dietary intake from two 24-hour dietary recalls were collected in a random sample cross-sectional pilot telephone survey in the fall of 2006. Black, white, and Latino employed mothers (n=25) and fathers (n=25) were recruited from a low/moderate income urban area in upstate New York. Hierarchical cluster analysis (Ward's method) identified three clusters of parents differing in use of food-choice coping strategies (ie, Individualized Eating, Missing Meals, and Home Cooking). Cluster sociodemographic, work, and family characteristics were compared using χ(2) and Fisher's exact tests. Cluster differences in dietary quality (Healthy Eating Index 2005) were analyzed using analysis of variance. Clusters differed significantly (P≤0.05) on food-choice coping strategies, dietary quality, and behavioral contexts (ie, work schedule, marital status, partner's employment, and number of children). Individualized Eating and Missing Meals clusters were characterized by nonstandard work hours, having a working partner, single parenthood and with family meals away from home, grabbing quick food instead of a meal, using convenience entrées at home, and missing meals or individualized eating. The Home Cooking cluster included considerably more married fathers with nonemployed spouses and more home-cooked family meals. Food-choice coping strategies affecting dietary quality reflect parents' work and family conditions. Nutritional guidance and family policy needs to consider these important behavioral contexts for family nutrition and health. Copyright © 2011 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

Clustering and Phase Transitions on a Neutral Landscape

NASA Astrophysics Data System (ADS)

Scott, Adam; King, Dawn; Maric, Nevena; Bahar, Sonya

2012-02-01

The problem of speciation and species aggregation on a neutral landscape, subject to random mutational fluctuations rather than selective drive, has been a focus of research since the seminal work of Kimura on genetic drift. These ideas have received increased attention due to the more recent development of a neutral ecological theory by Hubbell. De Aguiar et al. recently demonstrated, in a computational model, that speciation can occur under neutral conditions; this study bears some comparison with more mathematical studies of clustering on neutral landscapes in the context of branching and annihilating random walks. Here, we show that clustering can occur on a neutral landscape where the dimensions specify the simulated organisms' phenotypes. Unlike the De Aguiar et al. model, we simulate sympatric speciation: the organisms cluster phenotypically, but are not spatially separated. Moreover, we find that clustering occurs not only in the case of assortative mating, but also in the case of asexual fission. Clustering is not observed in a control case where organisms can mate randomly. We find that the population size and the number of clusters undergo phase-transition-like behavior as the maximum mutation size is varied.

Effectiveness of a group diabetes education programme in underserved communities in South Africa: pragmatic cluster randomized control trial.

PubMed

Mash, Bob; Levitt, Naomi; Steyn, Krisela; Zwarenstein, Merrick; Rollnick, Stephen

2012-12-24

Diabetes is an important contributor to the burden of disease in South Africa and prevalence rates as high as 33% have been recorded in Cape Town. Previous studies show that quality of care and health outcomes are poor. The development of an effective education programme should impact on self-care, lifestyle change and adherence to medication; and lead to better control of diabetes, fewer complications and better quality of life. Pragmatic cluster randomized controlled trialParticipants: Type 2 diabetic patients attending 45 public sector community health centres in Cape TownInterventions: The intervention group will receive 4 sessions of group diabetes education delivered by a health promotion officer in a guiding style. The control group will receive usual care which consists of ad hoc advice during consultations and occasional educational talks in the waiting room. To evaluate the effectiveness of the group diabetes education programmeOutcomes: diabetes self-care activities, 5% weight loss, 1% reduction in HbA1c. self-efficacy, locus of control, mean blood pressure, mean weight loss, mean waist circumference, mean HbA1c, mean total cholesterol, quality of lifeRandomisation: Computer generated random numbersBlinding: Patients, health promoters and research assistants could not be blinded to the health centre's allocationNumbers randomized: Seventeen health centres (34 in total) will be randomly assigned to either control or intervention groups. A sample size of 1360 patients in 34 clusters of 40 patients will give a power of 80% to detect the primary outcomes with 5% precision. Altogether 720 patients were recruited in the intervention arm and 850 in the control arm giving a total of 1570. The study will inform policy makers and managers of the district health system, particularly in low to middle income countries, if this programme can be implemented more widely. Pan African Clinical Trial Registry PACTR201205000380384.

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

Ben-Naim, Eli; Krapivsky, Paul

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

PubMed Central

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

The two-point correlation function for groups of galaxies in the Center for Astrophysics redshift survey

NASA Technical Reports Server (NTRS)

Ramella, Massimo; Geller, Margaret J.; Huchra, John P.

1990-01-01

The large-scale distribution of groups of galaxies selected from complete slices of the CfA redshift survey extension is examined. The survey is used to reexamine the contribution of group members to the galaxy correlation function. The relationship between the correlation function for groups and those calculated for rich clusters is discussed, and the results for groups are examined as an extension of the relation between correlation function amplitude and richness. The group correlation function indicates that groups and individual galaxies are equivalent tracers of the large-scale matter distribution. The distribution of group centers is equivalent to random sampling of the galaxy distribution. The amplitude of the correlation function for groups is consistent with an extrapolation of the amplitude-richness relation for clusters. The amplitude scaled by the mean intersystem separation is also consistent with results for richer clusters.

A Cluster-Randomized Trial of Insecticide-Treated Curtains for Dengue Vector Control in Thailand

PubMed Central

Lenhart, Audrey; Trongtokit, Yuwadee; Alexander, Neal; Apiwathnasorn, Chamnarn; Satimai, Wichai; Vanlerberghe, Veerle; Van der Stuyft, Patrick; McCall, Philip J.

2013-01-01

The efficacy of insecticide-treated window curtains (ITCs) for dengue vector control was evaluated in Thailand in a cluster-randomized controlled trial. A total of 2,037 houses in 26 clusters was randomized to receive the intervention or act as control (no treatment). Entomological surveys measured Aedes infestations (Breteau index, house index, container index, and pupae per person index) and oviposition indices (mean numbers of eggs laid in oviposition traps) immediately before and after intervention, and at 3-month intervals over 12 months. There were no consistent statistically significant differences in entomological indices between intervention and control clusters, although oviposition indices were lower (P < 0.01) in ITC clusters during the wet season. It is possible that the open housing structures in the study reduced the likelihood of mosquitoes making contact with ITCs. ITCs deployed in a region where this house design is common may be unsuitable for dengue vector control. PMID:23166195

Molecular analysis of the microbial diversity present in the colonic wall, colonic lumen, and cecal lumen of a pig.

PubMed

Pryde, S E; Richardson, A J; Stewart, C S; Flint, H J

1999-12-01

Random clones of 16S ribosomal DNA gene sequences were isolated after PCR amplification with eubacterial primers from total genomic DNA recovered from samples of the colonic lumen, colonic wall, and cecal lumen from a pig. Sequences were also obtained for cultures isolated anaerobically from the same colonic-wall sample. Phylogenetic analysis showed that many sequences were related to those of Lactobacillus or Streptococcus spp. or fell into clusters IX, XIVa, and XI of gram-positive bacteria. In addition, 59% of randomly cloned sequences showed less than 95% similarity to database entries or sequences from cultivated organisms. Cultivation bias is also suggested by the fact that the majority of isolates (54%) recovered from the colon wall by culturing were related to Lactobacillus and Streptococcus, whereas this group accounted for only one-third of the sequence variation for the same sample from random cloning. The remaining cultured isolates were mainly Selenomonas related. A higher proportion of Lactobacillus reuteri-related sequences than of Lactobacillus acidophilus- and Lactobacillus amylovorus-related sequences were present in the colonic-wall sample. Since the majority of bacterial ribosomal sequences recovered from the colon wall are less than 95% related to known organisms, the roles of many of the predominant wall-associated bacteria remain to be defined.

Molecular Analysis of the Microbial Diversity Present in the Colonic Wall, Colonic Lumen, and Cecal Lumen of a Pig

PubMed Central

Pryde, Susan E.; Richardson, Anthony J.; Stewart, Colin S.; Flint, Harry J.

1999-01-01

Random clones of 16S ribosomal DNA gene sequences were isolated after PCR amplification with eubacterial primers from total genomic DNA recovered from samples of the colonic lumen, colonic wall, and cecal lumen from a pig. Sequences were also obtained for cultures isolated anaerobically from the same colonic-wall sample. Phylogenetic analysis showed that many sequences were related to those of Lactobacillus or Streptococcus spp. or fell into clusters IX, XIVa, and XI of gram-positive bacteria. In addition, 59% of randomly cloned sequences showed less than 95% similarity to database entries or sequences from cultivated organisms. Cultivation bias is also suggested by the fact that the majority of isolates (54%) recovered from the colon wall by culturing were related to Lactobacillus and Streptococcus, whereas this group accounted for only one-third of the sequence variation for the same sample from random cloning. The remaining cultured isolates were mainly Selenomonas related. A higher proportion of Lactobacillus reuteri-related sequences than of Lactobacillus acidophilus- and Lactobacillus amylovorus-related sequences were present in the colonic-wall sample. Since the majority of bacterial ribosomal sequences recovered from the colon wall are less than 95% related to known organisms, the roles of many of the predominant wall-associated bacteria remain to be defined. PMID:10583991

A Cluster Randomized Controlled Trial Testing the Effectiveness of Houvast: A Strengths-Based Intervention for Homeless Young Adults

ERIC Educational Resources Information Center

Krabbenborg, Manon A. M.; Boersma, Sandra N.; van der Veld, William M.; van Hulst, Bente; Vollebergh, Wilma A. M.; Wolf, Judith R. L. M.

2017-01-01

Objective: To test the effectiveness of Houvast: a strengths-based intervention for homeless young adults. Method: A cluster randomized controlled trial was conducted with 10 Dutch shelter facilities randomly allocated to an intervention and a control group. Homeless young adults were interviewed when entering the facility and when care ended.…

Evaluating physical habitat and water chemistry data from statewide stream monitoring programs to establish least-impacted conditions in Washington State

USGS Publications Warehouse

Wilmoth, Siri K.; Irvine, Kathryn M.; Larson, Chad

2015-01-01

Various GIS-generated land-use predictor variables, physical habitat metrics, and water chemistry variables from 75 reference streams and 351 randomly sampled sites throughout Washington State were evaluated for effectiveness at discriminating reference from random sites within level III ecoregions. A combination of multivariate clustering and ordination techniques were used. We describe average observed conditions for a subset of predictor variables as well as proposing statistical criteria for establishing reference conditions for stream habitat in Washington. Using these criteria, we determined whether any of the random sites met expectations for reference condition and whether any of the established reference sites failed to meet expectations for reference condition. Establishing these criteria will set a benchmark from which future data will be compared.

A Highly Efficient Design Strategy for Regression with Outcome Pooling

PubMed Central

Mitchell, Emily M.; Lyles, Robert H.; Manatunga, Amita K.; Perkins, Neil J.; Schisterman, Enrique F.

2014-01-01

The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. PMID:25220822

A highly efficient design strategy for regression with outcome pooling.

PubMed

Mitchell, Emily M; Lyles, Robert H; Manatunga, Amita K; Perkins, Neil J; Schisterman, Enrique F

2014-12-10

The potential for research involving biospecimens can be hindered by the prohibitive cost of performing laboratory assays on individual samples. To mitigate this cost, strategies such as randomly selecting a portion of specimens for analysis or randomly pooling specimens prior to performing laboratory assays may be employed. These techniques, while effective in reducing cost, are often accompanied by a considerable loss of statistical efficiency. We propose a novel pooling strategy based on the k-means clustering algorithm to reduce laboratory costs while maintaining a high level of statistical efficiency when predictor variables are measured on all subjects, but the outcome of interest is assessed in pools. We perform simulations motivated by the BioCycle study to compare this k-means pooling strategy with current pooling and selection techniques under simple and multiple linear regression models. While all of the methods considered produce unbiased estimates and confidence intervals with appropriate coverage, pooling under k-means clustering provides the most precise estimates, closely approximating results from the full data and losing minimal precision as the total number of pools decreases. The benefits of k-means clustering evident in the simulation study are then applied to an analysis of the BioCycle dataset. In conclusion, when the number of lab tests is limited by budget, pooling specimens based on k-means clustering prior to performing lab assays can be an effective way to save money with minimal information loss in a regression setting. Copyright © 2014 John Wiley & Sons, Ltd.

The effect of asthma education program on knowledge of school teachers: a randomized controlled trial.

PubMed

Kawafha, Mariam M; Tawalbeh, Loai Issa

2015-04-01

The purpose of this study was to examine the effect of an asthma education program on schoolteachers' knowledge. Pre-test-post-test experimental randomized controlled design was used. A multistage-cluster sampling technique was used to randomly select governorate, primary schools, and schoolteachers. Schoolteachers were randomly assigned either to the experimental group (n = 36) and attended three educational sessions or to the control group (n = 38) who did not receive any intervention. Knowledge about asthma was measured using the Asthma General Knowledge Questionnaire for Adults (AGKQA). The results indicated that teachers in the experimental group showed significantly (p < .001) higher knowledge of asthma in the first post-test and the second post-test compared with those in the control group. Implementing asthma education enhanced schoolteachers' knowledge of asthma. The asthma education program should target schoolteachers to improve knowledge about asthma. © The Author(s) 2014.

Combining long-lasting insecticidal nets and indoor residual spraying for malaria prevention in Ethiopia: study protocol for a cluster randomized controlled trial.

PubMed

Deressa, Wakgari; Loha, Eskindir; Balkew, Meshesha; Hailu, Alemayehu; Gari, Taye; Kenea, Oljira; Overgaard, Hans J; Gebremichael, Teshome; Robberstad, Bjarne; Lindtjørn, Bernt

2016-01-12

Long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) are the main malaria prevention interventions in Ethiopia. There is conflicting evidence that the combined application of both interventions is better than either LLINs or IRS used alone. This trial aims to investigate whether the combination of LLINs (PermaNet 2.0, Vestergaard Frandsen, Lausanne, Switzerland) with IRS using propoxur will enhance the protective benefits and cost-effectiveness of the interventions against malaria and its effect on mosquito behavior, as compared to each intervention alone. This 2 x 2 factorial cluster randomized controlled trial is being carried out in the Adami Tullu district in south-central Ethiopia for about 116 weeks from September 2014 to December 2016. The trial is based on four arms: LLINs + IRS, LLINs alone, IRS alone and control. Villages (or clusters) will be the unit of randomization. The sample size includes 44 clusters per arm, with each cluster comprised of approximately 35 households (about 175 people). Prior to intervention, all households in the LLINs + IRS and LLINs alone arms will be provided with LLINs free of charge. Households in the LLINs + IRS and IRS alone arms will be sprayed with carbamate propoxur once a year just before the main malaria transmission season throughout the investigation. The primary outcome of this trial will be a malaria incidence based on the results of the rapid diagnostic tests in patients with a fever or history of fever attending health posts by passive case detection. Community-based surveys will be conducted each year to assess anemia among children 5-59 months old. In addition, community-based malaria prevalence surveys will be conducted each year on a representative sample of households during the main transmission season. The cost-effectiveness of the interventions and entomological studies will be simultaneously conducted. Analysis will be based on an intention-to-treat principle. This trial aims to provide evidence on the combined use of LLINs and IRS for malaria prevention by answering the following research questions: Can the combined use of LLINs and IRS significantly reduce the incidence of malaria compared with the use of either LLINs or IRS alone? And is the reduced incidence justifiable compared to the added costs? Will the combined use of LLINs and IRS reduce vector density, infection, longevity and the entomological inoculation rate? These data are crucial in order to maximize the impact of vector control interventions on the morbidity and mortality of malaria. PACTR201411000882128 (8 September 2014).

Internal Cluster Validation on Earthquake Data in the Province of Bengkulu

NASA Astrophysics Data System (ADS)

Rini, D. S.; Novianti, P.; Fransiska, H.

2018-04-01

K-means method is an algorithm for cluster n object based on attribute to k partition, where k < n. There is a deficiency of algorithms that is before the algorithm is executed, k points are initialized randomly so that the resulting data clustering can be different. If the random value for initialization is not good, the clustering becomes less optimum. Cluster validation is a technique to determine the optimum cluster without knowing prior information from data. There are two types of cluster validation, which are internal cluster validation and external cluster validation. This study aims to examine and apply some internal cluster validation, including the Calinski-Harabasz (CH) Index, Sillhouette (S) Index, Davies-Bouldin (DB) Index, Dunn Index (D), and S-Dbw Index on earthquake data in the Bengkulu Province. The calculation result of optimum cluster based on internal cluster validation is CH index, S index, and S-Dbw index yield k = 2, DB Index with k = 6 and Index D with k = 15. Optimum cluster (k = 6) based on DB Index gives good results for clustering earthquake in the Bengkulu Province.

Multiple behaviour change intervention for diarrhoea control in Lusaka, Zambia: a cluster randomised trial.

PubMed

Greenland, Katie; Chipungu, Jenala; Curtis, Val; Schmidt, Wolf-Peter; Siwale, Zumbe; Mudenda, Mweetwa; Chilekwa, Joyce; Lewis, James J; Chilengi, Roma

2016-12-01

Effective prevention and control of diarrhoea requires caregivers to comply with a suite of proven measures, including exclusive breastfeeding, handwashing with soap, correct use of oral rehydration salts, and zinc administration. We aimed to assess the effect of a novel behaviour change intervention using emotional drivers on caregiver practice of these behaviours. We did a cluster randomised controlled trial in Lusaka Province, Zambia. A random sample of 16 health centres (clusters) were selected from a sampling frame of 81 health centres in three of four districts in Lusaka Province using a computerised random number generator. Each cluster was randomly assigned 1:1 to either the intervention-clinic events, community events, and radio messaging-or to a standard care control arm, both for 6 months. Primary outcomes were exclusive breastfeeding (self-report), handwashing with soap (observation), oral rehydration salt solution preparation (demonstration), and zinc use in diarrhoea treatment (self-report). We measured outcome behaviours at baseline before start of intervention and 4-6 weeks post-intervention through repeat cross-sectional surveys with mothers of an infant younger than 6 months and primary caregivers of a child younger than 5 years with recent diarrhoea. We compared outcomes on an intention-to-treat population between intervention and control groups adjusted for baseline behaviour. The study was registered with ClinicalTrials.gov, number NCT02081521. Between Jan 20 and Feb 3, 2014, we recruited 306 mothers of an infant aged 0-5 months (156 intervention, 150 standard care) and 343 primary caregiver of a child aged 0-59 months with recent diarrhoea (176 intervention, 167 standard care) at baseline. Between Oct 20 to Nov 7, 2014, we recruited 401 mothers of an infant 0-5 months (234 intervention, 167 standard care) and 410 primary caregivers of a child 0-59 months with recent diarrhoea (257 intervention, 163 standard care) at endline. Intervention was associated with increased prevalence of self-reported exclusive breastfeeding of infants aged 0-5 months (adjusted difference 10·5%, 95% CI 0·9-19·9). Other primary outcomes were not affected by intervention. Cluster intervention exposure ranged from 11-81%, measured by participant self-report with verification questions. Comparison of control and intervention clusters with coverage greater than 35% provided strong evidence of an intervention effect on oral rehydration salt solution preparation and breastfeeding outcomes. The intervention may have improved exclusive breastfeeding (assessed by self-reporting), but intervention effects were diluted in clusters with low exposure. Complex caregiver practices can improve through interventions built around human motives, but these must be implemented more intensely. Absolute Return for Kids (ARK) and Comic Relief. Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

Mapping Health Data: Improved Privacy Protection With Donut Method Geomasking

PubMed Central

Hampton, Kristen H.; Fitch, Molly K.; Allshouse, William B.; Doherty, Irene A.; Gesink, Dionne C.; Leone, Peter A.; Serre, Marc L.; Miller, William C.

2010-01-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest. PMID:20817785

Mapping health data: improved privacy protection with donut method geomasking.

PubMed

Hampton, Kristen H; Fitch, Molly K; Allshouse, William B; Doherty, Irene A; Gesink, Dionne C; Leone, Peter A; Serre, Marc L; Miller, William C

2010-11-01

A major challenge in mapping health data is protecting patient privacy while maintaining the spatial resolution necessary for spatial surveillance and outbreak identification. A new adaptive geomasking technique, referred to as the donut method, extends current methods of random displacement by ensuring a user-defined minimum level of geoprivacy. In donut method geomasking, each geocoded address is relocated in a random direction by at least a minimum distance, but less than a maximum distance. The authors compared the donut method with current methods of random perturbation and aggregation regarding measures of privacy protection and cluster detection performance by masking multiple disease field simulations under a range of parameters. Both the donut method and random perturbation performed better than aggregation in cluster detection measures. The performance of the donut method in geoprivacy measures was at least 42.7% higher and in cluster detection measures was less than 4.8% lower than that of random perturbation. Results show that the donut method provides a consistently higher level of privacy protection with a minimal decrease in cluster detection performance, especially in areas where the risk to individual geoprivacy is greatest.

Enhancing students’ mathematical problem posing skill through writing in performance tasks strategy

NASA Astrophysics Data System (ADS)

Kadir; Adelina, R.; Fatma, M.

2018-01-01

Many researchers have studied the Writing in Performance Task (WiPT) strategy in learning, but only a few paid attention on its relation to the problem-posing skill in mathematics. The problem-posing skill in mathematics covers problem reformulation, reconstruction, and imitation. The purpose of the present study was to examine the effect of WiPT strategy on students’ mathematical problem-posing skill. The research was conducted at a Public Junior Secondary School in Tangerang Selatan. It used a quasi-experimental method with randomized control group post-test. The samples were 64 students consists of 32 students of the experiment group and 32 students of the control. A cluster random sampling technique was used for sampling. The research data were obtained by testing. The research shows that the problem-posing skill of students taught by WiPT strategy is higher than students taught by a conventional strategy. The research concludes that the WiPT strategy is more effective in enhancing the students’ mathematical problem-posing skill compared to the conventional strategy.

An Empirically Derived Taxonomy for Personality Diagnosis: Bridging Science and Practice in Conceptualizing Personality

PubMed Central

Westen, Drew; Shedler, Jonathan; Bradley, Bekh; DeFife, Jared A.

2013-01-01

Objective The authors describe a system for diagnosing personality pathology that is empirically derived, clinically relevant, and practical for day-to-day use. Method A random national sample of psychiatrists and clinical psychologists (N=1,201) described a randomly selected current patient with any degree of personality dysfunction (from minimal to severe) using the descriptors in the Shedler-Westen Assessment Procedure–II and completed additional research forms. Results The authors applied factor analysis to identify naturally occurring diagnostic groupings within the patient sample. The analysis yielded 10 clinically coherent personality diagnoses organized into three higher-order clusters: internalizing, externalizing, and borderline-dysregulated. The authors selected the most highly rated descriptors to construct a diagnostic prototype for each personality syndrome. In a second, independent sample, research interviewers and patients’ treating clinicians were able to diagnose the personality syndromes with high agreement and minimal comorbidity among diagnoses. Conclusions The empirically derived personality prototypes described here provide a framework for personality diagnosis that is both empirically based and clinically relevant. PMID:22193534

Searching for a Gulf War syndrome using cluster analysis.

PubMed

Everitt, B; Ismail, K; David, A S; Wessely, S

2002-11-01

Gulf veterans report medically unexplained symptoms more frequently than non-Gulf veterans did. We examined whether Gulf and non-Gulf veterans could be distinguished by their patterns of symptom reporting. A k-means cluster analysis was applied to 500 randomly sampled veterans from each of three United Kingdom military cohorts of veterans; those deployed to the Gulf conflict between 1990 and 1991; to the Bosnia peacekeeping mission between 1992 and 1997; and military personnel who were in active service but not deployed to the Gulf (Era). Sociodemographic, health variables and scores for ten symptom groups were calculated. The gap statistic indicated the five-group solution as one that provided a particularly informative description of the structure in the data. Cluster 1 consisted of low scores for all symptom groups. Cluster 2 had veterans with highest symptom scores for musculoskeletal symptoms and high scores for psychiatric symptoms. Cluster 3 had high scores for psychiatric symptoms and marginally elevated scores for the remaining nine groups symptom groups. Cluster 4 had elevated scores for musculoskeletal symptoms only and cluster 5 was distinguishable from the other clusters in having high scores in all symptom groups, especially psychiatric and musculoskeletal. The findings do not support the existence of a unique syndrome affecting a subgroup of Gulf veterans but emphasize the excess of non-specific self-reported ill health in this group.

Cluster-Randomized Trial to Increase Hepatitis B Testing among Koreans in Los Angeles

PubMed Central

Bastani, Roshan; Glenn, Beth A.; Maxwell, Annette E.; Jo, Angela M.; Herrmann, Alison K.; Crespi, Catherine M.; Wong, Weng K.; Chang, L. Cindy; Stewart, Susan L.; Nguyen, Tung T.; Chen, Moon S.; Taylor, Victoria M.

2015-01-01

Background In the United States, Korean immigrants experience a disproportionately high burden of chronic hepatitis B (HBV) viral infection and associated liver cancer compared to the general population. However, despite clear clinical guidelines, HBV serologic testing among Koreans remains persistently sub-optimal. Methods We conducted a cluster-randomized trial to evaluate a church-based small group intervention to improve HBV testing among Koreans in Los Angeles. Fifty-two Korean churches, stratified by size (small, medium, large) and location (Koreatown versus other), were randomized to intervention or control conditions. Intervention church participants attended a single-session small-group discussion on liver cancer and HBV testing and control church participants attended a similar session on physical activity and nutrition. Outcome data consisted of self-reported HBV testing obtained via 6-month telephone follow-up interviews. Results We recruited 1123 individuals, 18-64 years of age, across the 52 churches. Ninety-two percent of the sample attended the assigned intervention session and 86% completed the 6-month follow-up. Sample characteristics included: mean age 46 years, 65% female, 97% born in Korea, 69% completed some college, and 43% insured. In an intent-to-treat analysis, the intervention produced a statistically significant effect (OR = 4.9, p < .001), with 19% of intervention and 6% of control group participants reporting a HBV test. Conclusion Our intervention was successful in achieving a large and robust effect in a population at high risk of HBV infection and sequelae. Impact The intervention was fairly resource efficient and thus has high potential for replication in other high-risk Asian groups. PMID:26104909

Using Cluster Bootstrapping to Analyze Nested Data With a Few Clusters.

PubMed

Huang, Francis L

2018-04-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials are performed with a low number of clusters (~20 groups). Although multilevel models are often used to analyze nested data, researchers may be concerned of potentially biased results due to having only a few groups under study. Cluster bootstrapping has been suggested as an alternative procedure when analyzing clustered data though it has seen very little use in educational and psychological studies. Using a Monte Carlo simulation that varied the number of clusters, average cluster size, and intraclass correlations, we compared standard errors using cluster bootstrapping with those derived using ordinary least squares regression and multilevel models. Results indicate that cluster bootstrapping, though more computationally demanding, can be used as an alternative procedure for the analysis of clustered data when treatment effects at the group level are of primary interest. Supplementary material showing how to perform cluster bootstrapped regressions using R is also provided.

A sampling design framework for monitoring secretive marshbirds

USGS Publications Warehouse

Johnson, D.H.; Gibbs, J.P.; Herzog, M.; Lor, S.; Niemuth, N.D.; Ribic, C.A.; Seamans, M.; Shaffer, T.L.; Shriver, W.G.; Stehman, S.V.; Thompson, W.L.

2009-01-01

A framework for a sampling plan for monitoring marshbird populations in the contiguous 48 states is proposed here. The sampling universe is the breeding habitat (i.e. wetlands) potentially used by marshbirds. Selection protocols would be implemented within each of large geographical strata, such as Bird Conservation Regions. Site selection will be done using a two-stage cluster sample. Primary sampling units (PSUs) would be land areas, such as legal townships, and would be selected by a procedure such as systematic sampling. Secondary sampling units (SSUs) will be wetlands or portions of wetlands in the PSUs. SSUs will be selected by a randomized spatially balanced procedure. For analysis, the use of a variety of methods as a means of increasing confidence in conclusions that may be reached is encouraged. Additional effort will be required to work out details and implement the plan.

Reference Values of Within-District Intraclass Correlations of Academic Achievement by District Characteristics: Results from a Meta-Analysis of District-Specific Values

ERIC Educational Resources Information Center

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

2014-01-01

Randomized experiments are often considered the strongest designs to study the impact of educational interventions. Perhaps the most prevalent class of designs used in large scale education experiments is the cluster randomized design in which entire schools are assigned to treatments. In cluster randomized trials (CRTs) that assign schools to…

Disentangling giant component and finite cluster contributions in sparse random matrix spectra.

PubMed

Kühn, Reimer

2016-04-01

We describe a method for disentangling giant component and finite cluster contributions to sparse random matrix spectra, using sparse symmetric random matrices defined on Erdős-Rényi graphs as an example and test bed. Our methods apply to sparse matrices defined in terms of arbitrary graphs in the configuration model class, as long as they have finite mean degree.

Evaluating outcome-correlated recruitment and geographic recruitment bias in a respondent-driven sample of people who inject drugs in Tijuana, Mexico.

PubMed

Rudolph, Abby E; Gaines, Tommi L; Lozada, Remedios; Vera, Alicia; Brouwer, Kimberly C

2014-12-01

Respondent-driven sampling's (RDS) widespread use and reliance on untested assumptions suggests a need for new exploratory/diagnostic tests. We assessed geographic recruitment bias and outcome-correlated recruitment among 1,048 RDS-recruited people who inject drugs (Tijuana, Mexico). Surveys gathered demographics, drug/sex behaviors, activity locations, and recruiter-recruit pairs. Simulations assessed geographic and network clustering of active syphilis (RPR titers ≥1:8). Gender-specific predicted probabilities were estimated using logistic regression with GEE and robust standard errors. Active syphilis prevalence was 7 % (crude: men = 5.7 % and women = 16.6 %; RDS-adjusted: men = 6.7 % and women = 7.6 %). Syphilis clustered in the Zona Norte, a neighborhood known for drug and sex markets. Network simulations revealed geographic recruitment bias and non-random recruitment by syphilis status. Gender-specific prevalence estimates accounting for clustering were highest among those living/working/injecting/buying drugs in the Zona Norte and directly/indirectly connected to syphilis cases (men: 15.9 %, women: 25.6 %) and lowest among those with neither exposure (men: 3.0 %, women: 6.1 %). Future RDS analyses should assess/account for network and spatial dependencies.

Clustering, randomness and regularity in cloud fields. I - Theoretical considerations. II - Cumulus cloud fields

NASA Technical Reports Server (NTRS)

Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.

1992-01-01

The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.

What is the role and authority of gatekeepers in cluster randomized trials in health research?

PubMed Central

2012-01-01

This article is part of a series of papers examining ethical issues in cluster randomized trials (CRTs) in health research. In the introductory paper in this series, we set out six areas of inquiry that must be addressed if the CRT is to be set on a firm ethical foundation. This paper addresses the sixth of the questions posed, namely, what is the role and authority of gatekeepers in CRTs in health research? ‘Gatekeepers’ are individuals or bodies that represent the interests of cluster members, clusters, or organizations. The need for gatekeepers arose in response to the difficulties in obtaining informed consent because of cluster randomization, cluster-level interventions, and cluster size. In this paper, we call for a more restrictive understanding of the role and authority of gatekeepers. Previous papers in this series have provided solutions to the challenges posed by informed consent in CRTs without the need to invoke gatekeepers. We considered that consent to randomization is not required when cluster members are approached for consent at the earliest opportunity and before any study interventions or data-collection procedures have started. Further, when cluster-level interventions or cluster size means that obtaining informed consent is not possible, a waiver of consent may be appropriate. In this paper, we suggest that the role of gatekeepers in protecting individual interests in CRTs should be limited. Generally, gatekeepers do not have the authority to provide proxy consent for cluster members. When a municipality or other community has a legitimate political authority that is empowered to make such decisions, cluster permission may be appropriate; however, gatekeepers may usefully protect cluster interests in other ways. Cluster consultation may ensure that the CRT addresses local health needs, and is conducted in accord with local values and customs. Gatekeepers may also play an important role in protecting the interests of organizations, such as hospitals, nursing homes, general practices, and schools. In these settings, permission to access the organization relies on resource implications and adherence to institutional policies. PMID:22834691

The Relation between Globular Cluster Systems and Supermassive Black Holes in Spiral Galaxies: The Case Study of NGC 4258

NASA Astrophysics Data System (ADS)

González-Lópezlira, Rosa A.; Lomelí-Núñez, Luis; Álamo-Martínez, Karla; Órdenes-Briceño, Yasna; Loinard, Laurent; Georgiev, Iskren Y.; Muñoz, Roberto P.; Puzia, Thomas H.; Bruzual A., Gustavo; Gwyn, Stephen

2017-02-01

We aim to explore the relationship between globular cluster total number, {N}{GC}, and central black hole mass, M •, in spiral galaxies, and compare it with that recently reported for ellipticals. We present results for the Sbc galaxy NGC 4258, from Canada-France-Hawaii Telescope data. Thanks to water masers with Keplerian rotation in a circumnuclear disk, NGC 4258 has the most precisely measured extragalactic distance and supermassive black hole mass to date. The globular cluster (GC) candidate selection is based on the ({u}* -{I}\\prime ) versus ({I}\\prime -{K}s) diagram, which is a superb tool to distinguish GCs from foreground stars, background galaxies, and young stellar clusters, and hence can provide the best number counts of GCs from photometry alone, virtually free of contamination, even if the galaxy is not completely edge-on. The mean optical and optical-near-infrared colors of the clusters are consistent with those of the Milky Way and M 31, after extinction is taken into account. We directly identify 39 GC candidates; after completeness correction, GC luminosity function extrapolation, and correction for spatial coverage, we calculate a total {N}{GC}=144+/- {31}-36+38 (random and systematic uncertainties, respectively). We have thus increased to six the sample of spiral galaxies with measurements of both M • and {N}{GC}. NGC 4258 has a specific frequency {S}{{N}}=0.4+/- 0.1 (random uncertainty), and is consistent within 2σ with the {N}{GC} versus M • correlation followed by elliptical galaxies. The Milky Way continues to be the only spiral that deviates significantly from the relation.

Physiogenomic analysis of the Puerto Rican population.

PubMed

Ruaño, Gualberto; Duconge, Jorge; Windemuth, Andreas; Cadilla, Carmen L; Kocherla, Mohan; Villagra, David; Renta, Jessica; Holford, Theodore; Santiago-Borrero, Pedro J

2009-04-01

Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population. A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing. The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations. Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine.

Perceptions of a nearby exurban protected area in South Carolina, United States.

PubMed

Weaver, David B; Lawton, Laura J

2008-03-01

To address the dearth of literature on the relations between local residents in urban areas and nearby higher-order exurban protected areas, this study examined the perceptions of Columbia (South Carolina) residents toward Congaree National Park. Mail-out survey results from a random sample of 455 adult residents showed positive overall attitudes toward the park, although this did not extend to a desire to personally volunteer in park activities. Cluster analysis on the basis of seven perceptual statements produced three groups: "very enthusiastic park supporters" (VEPS), accounting for one fourth of the sample; "less enthusiastic park supporters" (LEPS), accounting for approximately one half of the sample; and "ambivalents" (AMBS), accounting for the rest. The AMBS tend to be younger than members of the other clusters and have higher income, but enthusiasm was more clearly related to high levels of interaction and awareness relative to the park. Managerial implications of the study are considered, including the need to encourage higher levels of park awareness and visitation, as well as more ecologically responsible behavior, among residents of the greater Columbia urban area.

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

Milk culture results in a large Norwegian survey--effects of season, parity, days in milk, resistance, and clustering.

PubMed

Osterås, O; Sølverød, L; Reksen, O

2006-03-01

A nationwide random computerized assignment survey that included 3,538 sets of 4 quarter milk samples from 2,834 dairy cows was conducted during 2000. Every fifth cow from every 50th herd was randomly selected for sampling and culture during each quarter of the year. Milk culture results of pathogens known to be related to mastitis were recorded regardless of whether mastitis had been indicated by any inflammatory measure or not. Farmers were blinded to all test results to minimize any potential interventions that might be prompted by the results. The most prevalent isolate was Staphylococcus aureus, which was identified in 8.2% of the quarter milk samples. More than 15 colony-forming units/0.01 mL of Staph. aureus were found in 4.3% of the quarter milk samples, whereas 3.5% had only 1 to 3 colony-forming units/0.01 mL. Streptococcus dysgalactiae, coagulase-negative staphylococci (CNS), and Streptococcus uberis were isolated from 1.2, 3.3, and 0.4% of quarter milk samples, respectively. No isolates were found in 76.6% of the quarter milk samples tested. Among individual cows, 22.2% had an isolate of Staph. aureus in > or = 1 quarter. Only Strep. dysgalactiae exhibited a higher prevalence with increased parity. Prevalence of Staph. aureus decreased throughout days in milk, but prevalence of Strep. dysgalactiae increased. There was a strong seasonal effect; the highest prevalence of Strep. dysgalactiae and CNS was observed during April and May (late indoor season), and the highest prevalence of Staph. aureus and Strep. uberis was observed during June and July (the outdoor season). A substantial within-cow clustering effect was found for Strep. dysgalactiae, Staph. aureus, and CNS. Additionally, a within-herd effect was found for Strep. uberis, penicillin-resistant Staph. aureus, total Staph. aureus, and CNS. No within-county cluster effect was found. Lastly, both Staph. aureus and CNS exhibited a surprisingly high seasonal effect regarding the prevalence of resistance to penicillin G. Penicillin resistance of Staph. aureus was likely due to higher prevalence of Staph. aureus as a whole, but for CNS, there was also an additional increase caused by a higher proportional rate of penicillin resistance during the late indoor season.

The Wilcoxon signed rank test for paired comparisons of clustered data.

PubMed

Rosner, Bernard; Glynn, Robert J; Lee, Mei-Ling T

2006-03-01

The Wilcoxon signed rank test is a frequently used nonparametric test for paired data (e.g., consisting of pre- and posttreatment measurements) based on independent units of analysis. This test cannot be used for paired comparisons arising from clustered data (e.g., if paired comparisons are available for each of two eyes of an individual). To incorporate clustering, a generalization of the randomization test formulation for the signed rank test is proposed, where the unit of randomization is at the cluster level (e.g., person), while the individual paired units of analysis are at the subunit within cluster level (e.g., eye within person). An adjusted variance estimate of the signed rank test statistic is then derived, which can be used for either balanced (same number of subunits per cluster) or unbalanced (different number of subunits per cluster) data, with an exchangeable correlation structure, with or without tied values. The resulting test statistic is shown to be asymptotically normal as the number of clusters becomes large, if the cluster size is bounded. Simulation studies are performed based on simulating correlated ranked data from a signed log-normal distribution. These studies indicate appropriate type I error for data sets with > or =20 clusters and a superior power profile compared with either the ordinary signed rank test based on the average cluster difference score or the multivariate signed rank test of Puri and Sen. Finally, the methods are illustrated with two data sets, (i) an ophthalmologic data set involving a comparison of electroretinogram (ERG) data in retinitis pigmentosa (RP) patients before and after undergoing an experimental surgical procedure, and (ii) a nutritional data set based on a randomized prospective study of nutritional supplements in RP patients where vitamin E intake outside of study capsules is compared before and after randomization to monitor compliance with nutritional protocols.

Assessing variation in life-history tactics within a population using mixture regression models: a practical guide for evolutionary ecologists.

PubMed

Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel

2017-05-01

Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.

Estimation After a Group Sequential Trial.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

2015-10-01

Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.

Spatial clustering of childhood leukaemia in Switzerland: A nationwide study.

PubMed

Konstantinoudis, Garyfallos; Kreis, Christian; Ammann, Roland A; Niggli, Felix; Kuehni, Claudia E; Spycher, Ben D

2017-10-01

The aetiology of childhood leukaemia remains largely unknown. Several hypotheses involve environmental exposures that could implicate spatial clustering of cases. The evidence from previous clustering studies is inconclusive. Most of them used areal data and thus had limited spatial resolution. We investigated whether childhood leukaemia tends to cluster in space using exact geocodes of place of residence both at the time of birth or diagnosis. We included 1,871 leukaemia cases diagnosed between 1985 and 2015 at age 0-15 years from the Swiss Childhood Cancer Registry. For each case, we randomly sampled 10 age and sex matched controls from national censuses closest in time. We used the difference of k-functions, Cuzick-Edwards' test and Tango's index for point data to assess spatial clustering and Kulldorff's circular scan to detect clusters. We separately investigated acute lymphoid leukaemia (ALL), acute myeloid leukaemia (AML), different age groups at diagnosis (0-4, 5-15 years) and adjusted for multiple testing. After adjusting for multiple testing, we found no evidence of spatial clustering of childhood leukaemia neither around time of birth (p = 0.52) nor diagnosis (p = 0.51). Individual tests indicated spatial clustering for leukaemia diagnosed at age 5-15 years, p k-functions = 0.05 and p Cuzick-Edwards' = 0.04 and a cluster of ALL cases diagnosed at age 0-4 years in a small rural area (p = 0.05). This study provides little evidence of spatial clustering of childhood leukaemia in Switzerland and highlights the importance of accounting for multiple testing in clustering studies. © 2017 UICC.

Kinetics of Aggregation with Choice

DOE PAGES

Ben-Naim, Eli; Krapivsky, Paul

2016-12-01

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

Patterns of Dysmorphic Features in Schizophrenia

PubMed Central

Scutt, L.E.; Chow, E.W.C.; Weksberg, R.; Honer, W.G.; Bassett, Anne S.

2011-01-01

Congenital dysmorphic features are prevalent in schizophrenia and may reflect underlying neurodevelopmental abnormalities. A cluster analysis approach delineating patterns of dysmorphic features has been used in genetics to classify individuals into more etiologically homogeneous subgroups. In the present study, this approach was applied to schizophrenia, using a sample with a suspected genetic syndrome as a testable model. Subjects (n = 159) with schizophrenia or schizoaffective disorder were ascertained from chronic patient populations (random, n=123) or referred with possible 22q11 deletion syndrome (referred, n = 36). All subjects were evaluated for presence or absence of 70 reliably assessed dysmorphic features, which were used in a three-step cluster analysis. The analysis produced four major clusters with different patterns of dysmorphic features. Significant between-cluster differences were found for rates of 37 dysmorphic features (P < 0.05), median number of dysmorphic features (P = 0.0001), and validating features not used in the cluster analysis: mild mental retardation (P = 0.001) and congenital heart defects (P = 0.002). Two clusters (1 and 4) appeared to represent more developmental subgroups of schizophrenia with elevated rates of dysmorphic features and validating features. Cluster 1 (n = 27) comprised mostly referred subjects. Cluster 4 (n= 18) had a different pattern of dysmorphic features; one subject had a mosaic Turner syndrome variant. Two other clusters had lower rates and patterns of features consistent with those found in previous studies of schizophrenia. Delineating patterns of dysmorphic features may help identify subgroups that could represent neurodevelopmental forms of schizophrenia with more homogeneous origins. PMID:11803519

A Refined Methodology for Defining Plant Communities Using Postagricultural Data from the Neotropics

PubMed Central

Myster, Randall W.

2012-01-01

How best to define and quantify plant communities was investigated using long-term plot data sampled from a recovering pasture in Puerto Rico and abandoned sugarcane and banana plantations in Ecuador. Significant positive associations between pairs of old field species were first computed and then clustered together into larger and larger species groups. I found that (1) no pasture or plantation had more than 5% of the possible significant positive associations, (2) clustering metrics showed groups of species participating in similar clusters among the five pasture/plantations over a gradient of decreasing association strength, and (3) there was evidence for repeatable communities—especially after banana cultivation—suggesting that past crops not only persist after abandonment but also form significant associations with invading plants. I then showed how the clustering hierarchy could be used to decide if any two pasture/plantation plots were in the same community, that is, to define old field communities. Finally, I suggested a similar procedure could be used for any plant community where the mechanisms and tolerances of species form the “cohesion” that produces clustering, making plant communities different than random assemblages of species. PMID:22536137

Relaxation dynamics of maximally clustered networks

NASA Astrophysics Data System (ADS)

Klaise, Janis; Johnson, Samuel

2018-01-01

We study the relaxation dynamics of fully clustered networks (maximal number of triangles) to an unclustered state under two different edge dynamics—the double-edge swap, corresponding to degree-preserving randomization of the configuration model, and single edge replacement, corresponding to full randomization of the Erdős-Rényi random graph. We derive expressions for the time evolution of the degree distribution, edge multiplicity distribution and clustering coefficient. We show that under both dynamics networks undergo a continuous phase transition in which a giant connected component is formed. We calculate the position of the phase transition analytically using the Erdős-Rényi phenomenology.

Ranking and clustering of nodes in networks with smart teleportation

NASA Astrophysics Data System (ADS)

Lambiotte, R.; Rosvall, M.

2012-05-01

Random teleportation is a necessary evil for ranking and clustering directed networks based on random walks. Teleportation enables ergodic solutions, but the solutions must necessarily depend on the exact implementation and parametrization of the teleportation. For example, in the commonly used PageRank algorithm, the teleportation rate must trade off a heavily biased solution with a uniform solution. Here we show that teleportation to links rather than nodes enables a much smoother trade-off and effectively more robust results. We also show that, by not recording the teleportation steps of the random walker, we can further reduce the effect of teleportation with dramatic effects on clustering.

A novel harmony search-K means hybrid algorithm for clustering gene expression data

PubMed Central

Nazeer, KA Abdul; Sebastian, MP; Kumar, SD Madhu

2013-01-01

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms. PMID:23390351

A novel harmony search-K means hybrid algorithm for clustering gene expression data.

PubMed

Nazeer, Ka Abdul; Sebastian, Mp; Kumar, Sd Madhu

2013-01-01

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms.

Bayesian hierarchical models for cost-effectiveness analyses that use data from cluster randomized trials.

PubMed

Grieve, Richard; Nixon, Richard; Thompson, Simon G

2010-01-01

Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.

Random variability explains apparent global clustering of large earthquakes

USGS Publications Warehouse

Michael, A.J.

2011-01-01

The occurrence of 5 Mw ≥ 8.5 earthquakes since 2004 has created a debate over whether or not we are in a global cluster of large earthquakes, temporarily raising risks above long-term levels. I use three classes of statistical tests to determine if the record of M ≥ 7 earthquakes since 1900 can reject a null hypothesis of independent random events with a constant rate plus localized aftershock sequences. The data cannot reject this null hypothesis. Thus, the temporal distribution of large global earthquakes is well-described by a random process, plus localized aftershocks, and apparent clustering is due to random variability. Therefore the risk of future events has not increased, except within ongoing aftershock sequences, and should be estimated from the longest possible record of events.

Cluster Randomized Trial of a Church-Based Peer Counselor and Tailored Newsletter Intervention to Promote Colorectal Cancer Screening and Physical Activity among Older African Americans

ERIC Educational Resources Information Center

Leone, Lucia A.; Allicock, Marlyn; Pignone, Michael P.; Walsh, Joan F.; Johnson, La-Shell; Armstrong-Brown, Janelle; Carr, Carol C.; Langford, Aisha; Ni, Andy; Resnicow, Ken; Campbell, Marci K.

2016-01-01

Action Through Churches in Time to Save Lives (ACTS) of Wellness was a cluster randomized controlled trial developed to promote colorectal cancer screening and physical activity (PA) within urban African American churches. Churches were recruited from North Carolina (n = 12) and Michigan (n = 7) and were randomized to intervention (n = 10) or…

Cost-Effectiveness of a Long-Term Internet-Delivered Worksite Health Promotion Programme on Physical Activity and Nutrition: A Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Robroek, Suzan J. W.; Polinder, Suzanne; Bredt, Folef J.; Burdorf, Alex

2012-01-01

This study aims to evaluate the cost-effectiveness of a long-term workplace health promotion programme on physical activity (PA) and nutrition. In total, 924 participants enrolled in a 2-year cluster randomized controlled trial, with departments (n = 74) within companies (n = 6) as the unit of randomization. The intervention was compared with a…

[A phylogenetic analysis of plant communities of Teberda Biosphere Reserve].

PubMed

Shulakov, A A; Egorov, A V; Onipchenko, V G

2016-01-01

Phylogenetic analysis of communities is based on the comparison of distances on the phylogenetic tree between species of a community under study and those distances in random samples taken out of local flora. It makes it possible to determine to what extent a community composition is formed by more closely related species (i.e., "clustered") or, on the opposite, it is more even and includes species that are less related with each other. The first case is usually interpreted as a result of strong influence caused by abiotic factors, due to which species with similar ecology, a priori more closely related, would remain: In the second case, biotic factors, such as competition, may come to the fore and lead to forming a community out of distant clades due to divergence of their ecological niches: The aim of this' study Was Ad explore the phylogenetic structure in communities of the northwestern Caucasus at two spatial scales - the scale of area from 4 to 100 m2 and the smaller scale within a community. The list of local flora of the alpine belt has been composed using the database of geobotanic descriptions carried out in Teberda Biosphere Reserve at true altitudes exceeding.1800 m. It includes 585 species of flowering plants belonging to 57 families. Basal groups of flowering plants are.not represented in the list. At the scale of communities of three classes, namely Thlaspietea rotundifolii - commumties formed on screes and pebbles, Calluno-Ulicetea - alpine meadow, and Mulgedio-Aconitetea subalpine meadows, have not demonstrated significant distinction of phylogenetic structure. At intra level, for alpine meadows the larger share of closely related species. (clustered community) is detected. Significantly clustered happen to be those communities developing on rocks (class Asplenietea trichomanis) and alpine (class Juncetea trifidi). At the same time, alpine lichen proved to have even phylogenetic structure at the small scale. Alpine (class Salicetea herbaceae) that develop under conditions of winter snow accumulation were more,even at the both.scale, i.e., contained more diverse and distantly related plant species compared with random samples. (Scheuchzerio-Caricetea fuscae) aquatic communities in cold (Montio-Cardaminetea), sedge meadows (Carici rupestris-Kobresietea bellardii), and communities, in which shrubs and predominated (juniper and rhododendron elfin woods, class Loiseleurio-Vaccinietea), have been studied only at the larger scale and showed significant evenness of species composition, i.e., were phylogenetically more diverse compared with random samples.

Health-risk behaviour in Croatia.

PubMed

Bécue-Bertaut, Mónica; Kern, Josipa; Hernández-Maldonado, Maria-Luisa; Juresa, Vesna; Vuletic, Silvije

2008-02-01

To identify the health-risk behaviour of various homogeneous clusters of individuals. The study was conducted in 13 of the 20 Croatian counties and in Zagreb, the Croatian capital. In the first stage, general practices were selected in each county. The second-stage sample was created by drawing a random subsample of 10% of the patients registered at each selected general practice. The sample was divided into seven homogenous clusters using statistical methodology, combining multiple factor analysis with a hybrid clustering method. Seven homogeneous clusters were identified, three composed of males and four composed of females, based on statistically significant differences between selected characteristics (P<0.001). Although, in general, self-assessed health declined with age, significant variations were observed within specific age intervals. Higher levels of self-assessed health were associated with higher levels of education and/or socio-economic status. Many individuals, especially females, who self-reported poor health were heavy consumers of sleeping pills. Males and females reported different health-risk behaviours related to lifestyle, diet and use of the healthcare system. Heavy alcohol and tobacco use, unhealthy diet, risky physical activity and non-use of the healthcare system influenced self-assessed health in males. Females were slightly less satisfied with their health than males of the same age and educational level. Even highly educated females who took preventive healthcare tests and ate a healthy diet reported a less satisfactory self-assessed level of health than expected. Sociodemographic characteristics, life style, self-assessed health and use of the healthcare system were used in the identification of seven homogeneous population clusters. A comprehensive analysis of these clusters suggests health-related prevention and intervention efforts geared towards specific populations.

Best (but oft-forgotten) practices: designing, analyzing, and reporting cluster randomized controlled trials.

PubMed

Brown, Andrew W; Li, Peng; Bohan Brown, Michelle M; Kaiser, Kathryn A; Keith, Scott W; Oakes, J Michael; Allison, David B

2015-08-01

Cluster randomized controlled trials (cRCTs; also known as group randomized trials and community-randomized trials) are multilevel experiments in which units that are randomly assigned to experimental conditions are sets of grouped individuals, whereas outcomes are recorded at the individual level. In human cRCTs, clusters that are randomly assigned are typically families, classrooms, schools, worksites, or counties. With growing interest in community-based, public health, and policy interventions to reduce obesity or improve nutrition, the use of cRCTs has increased. Errors in the design, analysis, and interpretation of cRCTs are unfortunately all too common. This situation seems to stem in part from investigator confusion about how the unit of randomization affects causal inferences and the statistical procedures required for the valid estimation and testing of effects. In this article, we provide a brief introduction and overview of the importance of cRCTs and highlight and explain important considerations for the design, analysis, and reporting of cRCTs by using published examples. © 2015 American Society for Nutrition.

Informing resource-poor populations and the delivery of entitled health and social services in rural India: a cluster randomized controlled trial.

PubMed

Pandey, Priyanka; Sehgal, Ashwini R; Riboud, Michelle; Levine, David; Goyal, Madhav

2007-10-24

A lack of awareness about entitled health and social services may contribute to poor delivery of such services in developing countries, especially among individuals of low socioeconomic status. To determine the impact of informing resource-poor rural populations about entitled services. Community-based, cluster randomized controlled trial conducted from May 2004 to May 2005 in 105 randomly selected village clusters in Uttar Pradesh state in India. Households (548 intervention and 497 control) were selected by a systematic sampling design, including both low-caste and mid- to high-caste households. Four to 6 public meetings were held in each intervention village cluster to disseminate information on entitled health services, entitled education services, and village governance requirements. No intervention took place in control village clusters. Visits by nurse midwife; prenatal examinations, tetanus vaccinations, and prenatal supplements received by pregnant women; vaccinations received by infants; excess school fees charged; occurrence of village council meetings; and development work in villages. At baseline, there were no significant differences in self-reported delivery of health and social services. After 1 year, intervention villagers reported better delivery of several services compared with control villagers: in a multivariate analysis, 30% more prenatal examinations (95% confidence interval [CI], 17%-43%; P < .001), 27% more tetanus vaccinations (95% CI, 12%-41%; P < .001), 24% more prenatal supplements (95% CI, 8%-39%; P = .003), 25% more infant vaccinations (95% CI, 8%-42%; P = .004), and decreased excess school fees of 8 rupees (95% CI, 4-13 rupees; P < .001). In a difference-in-differences analysis, 21% more village council meetings were reported (95% CI, 5%-36%; P = .01). There were no improvements in visits by a nurse midwife or in development work in the villages. Both low-caste and mid- to high-caste intervention households reported significant improvements in service delivery. Informing resource-poor rural populations in India about entitled services enhanced the delivery of health and social services among both low- and mid- to high-caste households. Interventions that emphasize educating resource-poor populations about entitled services may improve the delivery of such services. clinicaltrials.gov Identifier: NCT00421291.

Sleep Complaints in the Adult Brazilian Population: A National Survey Based on Screening Questions

PubMed Central

Bittencourt, Lia Rita A.; Santos-Silva, Rogerio; Taddei, Jose A.; Andersen, Monica L.; de Mello, Marco T.; Tufik, Sergio

2009-01-01

Study Objectives: The aim of the current survey was to investigate the prevalence of sleep complaints in a randomized cluster sample of the Brazilian population. Methods: A 3-stage cluster sampling technique was utilized to randomly select Brazilian subjects older than 16 years, of both genders and all socioeconomic classes. The final sample of 2,110 subjects from 150 different cities was enough to estimate prevalence in the Brazilian population with a sampling error of ± 2%. Questions about sleep complaints were administered face-to-face by Instituto Datafolha interviewers on March 26 and 27, 2008. Data were expanded using a weighted variable. Results: Of all interviewed subjects, 63% reported at least one sleep related complaint. Sleep complaint prevalence increased with age and was similar among inhabitants of different Brazilian regions, as well as between metropolitan areas and smaller cities. Insomnia and nightmares were significantly more prevalent in women (40% and 25%, respectively), and snoring was more prevalent in men (35%). For sleep complaints with frequencies greater than 3 times per week, we found the following prevalence: 61% for snoring, 35% for insomnia, 17% for nightmares, 53% for leg kicking, and 37% for breathing pauses. Conclusions: Because sleep disorders are affect a high proportion of the population and are known to be correlated with decreased well-being and productivity, more detailed national surveys are necessary to provide relevant information to develop approaches to prevention and treatment. Citation: Bittencourt LRA; Santos-Silva R; Taddei JA; Andersen ML; de Mello MT; Tufik S. Sleep complaints in the adult brazilian population: a national survey based on screening questions. J Clin Sleep Med 2009;5(5):459-463. PMID:19961032

Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

PubMed

Gomes, Manuel; Ng, Edmond S-W; Grieve, Richard; Nixon, Richard; Carpenter, James; Thompson, Simon G

2012-01-01

Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering--seemingly unrelated regression (SUR) without a robust standard error (SE)--and 4 methods that recognized clustering--SUR and generalized estimating equations (GEEs), both with robust SE, a "2-stage" nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92-0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters.

Impact of Probiotics on Necrotizing Enterocolitis

PubMed Central

Underwood, Mark A.

2016-01-01

A large number of randomized placebo-controlled clinical trials and cohort studies have demonstrated a decrease in the incidence of necrotizing enterocolitis with administration of probiotic microbes. These studies have prompted many neonatologists to adopt routine prophylactic administration of probiotics while others await more definitive studies and/or probiotic products with demonstrated purity and stable numbers of live organisms. Cross-contamination and inadequate sample size limit the value of further traditional placebo-controlled randomized controlled trials. Key areas for future research include mechanisms of protection, optimum probiotic species or strains (or combinations thereof) and duration of treatment, interactions between diet and the administered probiotic, and the influence of genetic polymorphisms in the mother and infant on probiotic response. Next generation probiotics selected based on bacterial genetics rather than ease of production and large cluster-randomized clinical trials hold great promise for NEC prevention. PMID:27836423

The Implications of "Contamination" for Experimental Design in Education

ERIC Educational Resources Information Center

Rhoads, Christopher H.

2011-01-01

Experimental designs that randomly assign entire clusters of individuals (e.g., schools and classrooms) to treatments are frequently advocated as a way of guarding against contamination of the estimated average causal effect of treatment. However, in the absence of contamination, experimental designs that randomly assign intact clusters to…

Application of adaptive cluster sampling to low-density populations of freshwater mussels

USGS Publications Warehouse

Smith, D.R.; Villella, R.F.; Lemarie, D.P.

2003-01-01

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

PubMed

Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra

2016-11-20

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

X-ray versus infrared selection of distant galaxy clusters: A case study using the XMM-LSS and SpARCS cluster samples

NASA Astrophysics Data System (ADS)

Willis, J. P.; Ramos-Ceja, M. E.; Muzzin, A.; Pacaud, F.; Yee, H. K. C.; Wilson, G.

2018-04-01

We present a comparison of two samples of z > 0.8 galaxy clusters selected using different wavelength-dependent techniques and examine the physical differences between them. We consider 18 clusters from the X-ray selected XMM-LSS distant cluster survey and 92 clusters from the optical-MIR selected SpARCS cluster survey. Both samples are selected from the same approximately 9 square degree sky area and we examine them using common XMM-Newton, Spitzer-SWIRE and CFHT Legacy Survey data. Clusters from each sample are compared employing aperture measures of X-ray and MIR emission. We divide the SpARCS distant cluster sample into three sub-samples: a) X-ray bright, b) X-ray faint, MIR bright, and c) X-ray faint, MIR faint clusters. We determine that X-ray and MIR selected clusters display very similar surface brightness distributions of galaxy MIR light. In addition, the average location and amplitude of the galaxy red sequence as measured from stacked colour histograms is very similar in the X-ray and MIR-selected samples. The sub-sample of X-ray faint, MIR bright clusters displays a distribution of BCG-barycentre position offsets which extends to higher values than all other samples. This observation indicates that such clusters may exist in a more disturbed state compared to the majority of the distant cluster population sampled by XMM-LSS and SpARCS. This conclusion is supported by stacked X-ray images for the X-ray faint, MIR bright cluster sub-sample that display weak, centrally-concentrated X-ray emission, consistent with a population of growing clusters accreting from an extended envelope of material.

Design of the Indian NCA study (Indian national collaboration on AIDS): a cluster randomized trial to evaluate the effectiveness of integrated care centers to improve HIV outcomes among men who have sex with men and persons who inject drugs in India.

PubMed

Solomon, Sunil S; Lucas, Gregory M; Celentano, David D; McFall, Allison M; Ogburn, Elizabeth; Moulton, Lawrence H; Srikrishnan, Aylur K; Kumar, M Suresh; Anand, Santhanam; Solomon, Suniti; Mehta, Shruti H

2016-11-14

Globally, men who have sex with men and people who inject drugs remain disproportionately affected by HIV, but they have not been the focus of prevention and treatment interventions in many resource-limited settings. This cluster-randomized trial (conducted from June 2012 to June 2017), evaluates whether single-venue, integrated delivery of core HIV services to vulnerable high-risk populations improves service utilization and consequently, HIV testing and other outcomes along the HIV care continuum. Core services include: HIV counseling and testing, information, education and communication, condom distribution, needle and syringe exchange programs, opioid agonist therapy, management of sexually transmitted infections, tuberculosis screening, diagnosis, and treatment, and antiretroviral therapy. Stratified restricted randomization was used to allocate 22 Indian cities (10 men who have sex with men and 12 people who inject drugs sites) at a 1:1 ratio to either the intervention or control condition. Integrated care centers were scaled-up and implemented in the 11 intervention cities and outcomes will be assessed by pre- and post-intervention surveys at intervention and control sites. As men who have sex with men and people who inject drugs are hidden populations, with no sampling frame, respondent-driven sampling will be used to accrue samples for the two independent cross-sectional surveys. For an AIDS-free generation to be realized, prevention, care and treatment services need to reach all populations at risk for HIV infection. There is a clear gap in access to services among men who have sex with men and people who inject drugs. Trials need to be designed to optimize utilization of services in these populations. ClinicalTrials.gov Identifier: NCT01686750 Date of Registration: September 13, 2012.

Validation of spot-testing kits to determine iodine content in salt.

PubMed Central

Pandav, C. S.; Arora, N. K.; Krishnan, A.; Sankar, R.; Pandav, S.; Karmarkar, M. G.

2000-01-01

Iodine deficiency disorders are a major public health problem, and salt iodization is the most widely practised intervention for their elimination. For the intervention to be successful and sustainable, it is vital to monitor the iodine content of salt regularly. Iodometric titration, the traditional method for measuring iodine content, has problems related to accessibility and cost. The newer spot-testing kits are inexpensive, require minimal training, and provide immediate results. Using data from surveys to assess the availability of iodized salt in two states in India, Madhya Pradesh and the National Capital Territory of Delhi, we tested the suitability of such a kit in field situations. Salt samples from Delhi were collected from 30 schools, chosen using the Expanded Programme on Immunization (EPI) cluster sampling technique. A single observer made the measurement for iodine content using the kit. Salt samples from Madhya Pradesh were from 30 rural and 30 urban clusters, identified by using census data and the EPI cluster sampling technique. In each cluster, salt samples were collected from 10 randomly selected households and all retailers. The 15 investigators performing the survey estimated the iodine content of salt samples in the field using the kit. All the samples were brought to the central laboratory in Delhi, where iodine content was estimated using iodometric titration as a reference method. The agreement between the kit and titration values decreased as the number of observers increased. Although sensitivity was not much affected by the increase in the number of observers (93.3% for a single observer and 93.9% for multiple observers), specificity decreased sharply (90.4% for a single observer and 40.4% for multiple observers). Due to the low specificity and resulting high numbers of false-positives for the kit when used by multiple observers ("real-life situations"), kits were likely to consistently overestimate the availability of iodized salt. This overestimation could result in complacency. Therefore, we conclude that until a valid alternative is available, the titration method should be used for monitoring the iodine content of salt at all levels, from producer to consumer, to ensure effectiveness of the programme. PMID:10994281

Variation of δ2H, δ18O & δ13C in crude palm oil from different regions in Malaysia: Potential of stable isotope signatures as a key traceability parameter.

PubMed

Muhammad, Syahidah Akmal; Seow, Eng-Keng; Mohd Omar, A K; Rodhi, Ainolsyakira Mohd; Mat Hassan, Hasnuri; Lalung, Japareng; Lee, Sze-Chi; Ibrahim, Baharudin

2018-01-01

A total of 33 crude palm oil samples were randomly collected from different regions in Malaysia. Stable carbon isotopic composition (δ 13 C) was determined using Flash 2000 elemental analyzer while hydrogen and oxygen isotopic compositions (δ 2 H and δ 18 O) were analyzed by Thermo Finnigan TC/EA, wherein both instruments were coupled to an isotope ratio mass spectrometer. The bulk δ 2 H, δ 18 O and δ 13 C of the samples were analyzed by Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Unsupervised HCA and PCA methods have demonstrated that crude palm oil samples were grouped into clusters according to respective state. A predictive model was constructed by supervised OPLS-DA with good predictive power of 52.60%. Robustness of the predictive model was validated with overall accuracy of 71.43%. Blind test samples were correctly assigned to their respective cluster except for samples from southern region. δ 18 O was proposed as the promising discriminatory marker for discerning crude palm oil samples obtained from different regions. Stable isotopes profile was proven to be useful for origin traceability of crude palm oil samples at a narrower geographical area, i.e. based on regions in Malaysia. Predictive power and accuracy of the predictive model was expected to improve with the increase in sample size. Conclusively, the results in this study has fulfilled the main objective of this work where the simple approach of combining stable isotope analysis with chemometrics can be used to discriminate crude palm oil samples obtained from different regions in Malaysia. Overall, this study shows the feasibility of this approach to be used as a traceability assessment of crude palm oils. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

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

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

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

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

Sehgal, Neelima; Hlozek, Renee; Addison, Graeme

We present the measured Sunyaev-Zel'dovich (SZ) flux from 474 optically selected MaxBCG clusters that fall within the Atacama Cosmology Telescope (ACT) Equatorial survey region. The ACT Equatorial region used in this analysis covers 510 deg{sup 2} and overlaps Stripe 82 of the Sloan Digital Sky Survey. We also present the measured SZ flux stacked on 52 X-ray-selected MCXC clusters that fall within the ACT Equatorial region and an ACT Southern survey region covering 455 deg{sup 2}. We find that the measured SZ flux from the X-ray-selected clusters is consistent with expectations. However, we find that the measured SZ flux frommore » the optically selected clusters is both significantly lower than expectations and lower than the recovered SZ flux measured by the Planck satellite. Since we find a lower recovered SZ signal than Planck, we investigate the possibility that there is a significant offset between the optically selected brightest cluster galaxies (BCGs) and the SZ centers, to which ACT is more sensitive due to its finer resolution. Such offsets can arise due to either an intrinsic physical separation between the BCG and the center of the gas concentration or from misidentification of the cluster BCG. We find that the entire discrepancy for both ACT and Planck can be explained by assuming that the BCGs are offset from the SZ maxima with a uniform random distribution between 0 and 1.5 Mpc. Such large offsets between gas peaks and BCGs for optically selected cluster samples seem unlikely given that we find the physical separation between BCGs and X-ray peaks for an X-ray-selected subsample of MaxBCG clusters to have a much narrower distribution that peaks within 0.2 Mpc. It is possible that other effects are lowering the ACT and Planck signals by the same amount, with offsets between BCGs and SZ peaks explaining the remaining difference between ACT and Planck measurements. Several effects that can lower the SZ signal equally for both ACT and Planck, but not explain the difference in measured signals, include a larger percentage of false detections in the MaxBCG sample, a lower normalization of the mass-richness relation, radio or infrared galaxy contamination of the SZ flux, and a low intrinsic SZ signal. In the latter two cases, the effects would need to be preferentially more significant in the optically selected MaxBCG sample than in the MCXC X-ray sample.« less

Implementation of authentic assessment in the project based learning to improve student's concept mastering

NASA Astrophysics Data System (ADS)

Sambeka, Yana; Nahadi, Sriyati, Siti

2017-05-01

The study aimed to obtain the scientific information about increase of student's concept mastering in project based learning that used authentic assessment. The research was conducted in May 2016 at one of junior high school in Bandung in the academic year of 2015/2016. The research method was weak experiment with the one-group pretest-posttest design. The sample was taken by random cluster sampling technique and the sample was 24 students. Data collected through instruments, i.e. written test, observation sheet, and questionnaire sheet. Student's concept mastering test obtained N-Gain of 0.236 with the low category. Based on the result of paired sample t-test showed that implementation of authentic assessment in the project based learning increased student's concept mastering significantly, (sig<0.05).

X-ray versus infrared selection of distant galaxy clusters: a case study using the XMM-LSS and SpARCS cluster samples

NASA Astrophysics Data System (ADS)

Willis, J. P.; Ramos-Ceja, M. E.; Muzzin, A.; Pacaud, F.; Yee, H. K. C.; Wilson, G.

2018-07-01

We present a comparison of two samples of z> 0.8 galaxy clusters selected using different wavelength-dependent techniques and examine the physical differences between them. We consider 18 clusters from the X-ray-selected XMM Large Scale Structure (LSS) distant cluster survey and 92 clusters from the optical-mid-infrared (MIR)-selected Spitzer Adaptation of the Red Sequence Cluster survey (SpARCS) cluster survey. Both samples are selected from the same approximately 9 sq deg sky area and we examine them using common XMM-Newton, Spitizer Wide-Area Infrared Extra-galactic (SWIRE) survey, and Canada-France-Hawaii Telescope Legacy Survey data. Clusters from each sample are compared employing aperture measures of X-ray and MIR emission. We divide the SpARCS distant cluster sample into three sub-samples: (i) X-ray bright, (ii) X-ray faint, MIR bright, and (iii) X-ray faint, MIR faint clusters. We determine that X-ray- and MIR-selected clusters display very similar surface brightness distributions of galaxy MIR light. In addition, the average location and amplitude of the galaxy red sequence as measured from stacked colour histograms is very similar in the X-ray- and MIR-selected samples. The sub-sample of X-ray faint, MIR bright clusters displays a distribution of brightest cluster galaxy-barycentre position offsets which extends to higher values than all other samples. This observation indicates that such clusters may exist in a more disturbed state compared to the majority of the distant cluster population sampled by XMM-LSS and SpARCS. This conclusion is supported by stacked X-ray images for the X-ray faint, MIR bright cluster sub-sample that display weak, centrally concentrated X-ray emission, consistent with a population of growing clusters accreting from an extended envelope of material.

Clustering and phase transitions on a neutral landscape

NASA Astrophysics Data System (ADS)

Scott, Adam D.; King, Dawn M.; Marić, Nevena; Bahar, Sonya

2013-06-01

Recent computational studies have shown that speciation can occur under neutral conditions, i.e., when the simulated organisms all have identical fitness. These works bear comparison with mathematical studies of clustering on neutral landscapes in the context of branching and coalescing random walks. Here, we show that sympatric clustering/speciation can occur on a neutral landscape whose dimensions specify only the simulated organisms’ phenotypes. We demonstrate that clustering occurs not only in the case of assortative mating, but also in the case of asexual fission; it is not observed in the control case of random mating. We find that the population size and the number of clusters undergo a second-order non-equilibrium phase transition as the maximum mutation size is varied.

Resuscitation Outcomes Consortium (ROC) PRIMED Cardiac Arrest Trial Methods Part 2: Rationale and Methodology for “Analyze Later” Protocol

PubMed Central

Stiell, Ian G.; Callaway, Clif; Davis, Dan; Terndrup, Tom; Powell, Judy; Cook, Andrea; Kudenchuk, Peter J.; Daya, Mohamud; Kerber, Richard; Idris, Ahamed; Morrison, Laurie J.; Aufderheide, Tom

2008-01-01

Objective The primary objective of the trial is to compare survival to hospital discharge with Modified Rankin Score (MRS) ≤3 between a strategy that prioritizes a specified period of CPR before rhythm analysis (Analyze Later) versus a strategy of minimal CPR followed by early rhythm analysis (Analyze Early) in patients with out-of-hospital cardiac arrest. Methods   Design Cluster randomized trial with cluster units defined by geographic region, or monitor/defibrillator machine. Population Adults treated by Emergency Medical Service (EMS) providers for non-traumatic out-of-hospital cardiac arrest not witnessed by EMS. Setting EMS systems participating in the Resuscitation Outcomes Consortium and agreeing to cluster randomization to the Analyze Later versus Analyze Early intervention in a crossover fashion. Sample Size Based on a two-sided significance level of 0.05, a maximum of 13,239 evaluable patients will allow statistical power of 0.996 to detect a hypothesized improvement in the probability of survival to discharge with MRS ≤ 3 rate from 5.41% after Analyze Early to 7.45% after Analyze Later (2.04% absolute increase in primary outcome). Conclusion If this trial demonstrates a significant improvement in survival with a strategy of Analyze Later, it is estimated that 4,000 premature deaths from cardiac arrest would be averted annually in North America alone. PMID:18487004

Resuscitation Outcomes Consortium (ROC) PRIMED cardiac arrest trial methods part 2: rationale and methodology for "Analyze Later vs. Analyze Early" protocol.

PubMed

Stiell, Ian G; Callaway, Clif; Davis, Dan; Terndrup, Tom; Powell, Judy; Cook, Andrea; Kudenchuk, Peter J; Daya, Mohamud; Kerber, Richard; Idris, Ahamed; Morrison, Laurie J; Aufderheide, Tom

2008-08-01

The primary objective of the trial is to compare survival to hospital discharge with modified Rankin score (MRS) < or =3 between a strategy that prioritizes a specified period of CPR before rhythm analysis (Analyze Later) versus a strategy of minimal CPR followed by early rhythm analysis (Analyze Early) in patients with out-of-hospital cardiac arrest. Design-Cluster randomized trial with cluster units defined by geographic region, or monitor/defibrillator machine. Population-Adults treated by emergency medical service (EMS) providers for non-traumatic out-of-hospital cardiac arrest not witnessed by EMS. Setting-EMS systems participating in the Resuscitation Outcomes Consortium and agreeing to cluster randomization to the Analyze Later versus Analyze Early intervention in a crossover fashion. Sample size-Based on a two-sided significance level of 0.05, a maximum of 13,239 evaluable patients will allow statistical power of 0.996 to detect a hypothesized improvement in the probability of survival to discharge with MRS < or =3 rate from 5.41% after Analyze Early to 7.45% after Analyze Later (2.04% absolute increase in primary outcome). If this trial demonstrates a significant improvement in survival with a strategy of Analyze Later, it is estimated that 4000 premature deaths from cardiac arrest would be averted annually in North America alone.

[Analysis of Time-to-onset of Interstitial Lung Disease after the Administration of Small Molecule Molecularly-targeted Drugs].

PubMed

Komada, Fusao

2018-01-01

　The aim of this study was to investigate the time-to-onset of drug-induced interstitial lung disease (DILD) following the administration of small molecule molecularly-targeted drugs via the use of the spontaneous adverse reaction reporting system of the Japanese Adverse Drug Event Report database. DILD datasets for afatinib, alectinib, bortezomib, crizotinib, dasatinib, erlotinib, everolimus, gefitinib, imatinib, lapatinib, nilotinib, osimertinib, sorafenib, sunitinib, temsirolimus, and tofacitinib were used to calculate the median onset times of DILD and the Weibull distribution parameters, and to perform the hierarchical cluster analysis. The median onset times of DILD for afatinib, bortezomib, crizotinib, erlotinib, gefitinib, and nilotinib were within one month. The median onset times of DILD for dasatinib, everolimus, lapatinib, osimertinib, and temsirolimus ranged from 1 to 2 months. The median onset times of the DILD for alectinib, imatinib, and tofacitinib ranged from 2 to 3 months. The median onset times of the DILD for sunitinib and sorafenib ranged from 8 to 9 months. Weibull distributions for these drugs when using the cluster analysis showed that there were 4 clusters. Cluster 1 described a subgroup with early to later onset DILD and early failure type profiles or a random failure type profile. Cluster 2 exhibited early failure type profiles or a random failure type profile with early onset DILD. Cluster 3 exhibited a random failure type profile or wear out failure type profiles with later onset DILD. Cluster 4 exhibited an early failure type profile or a random failure type profile with the latest onset DILD.

Cluster-cluster correlations and constraints on the correlation hierarchy

NASA Technical Reports Server (NTRS)

Hamilton, A. J. S.; Gott, J. R., III

1988-01-01

The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

Covariations of adolescent weight-control, health-risk and health-promoting behaviors.

PubMed

Rafiroiu, Codruta; Sargent, Roger G; Parra-Medina, Deborah; Drane, Wanzer J; Valois, Robert F

2003-01-01

To assess the prevalence of dieting and investigate clusters of risk behaviors among adolescents. Data were secured from a random sample of adolescents (4,636) and analyzed using bivariate methods and logistic regression. From the survey sample, 19.2% adolescents were classified as extreme, 43.2% as moderate dieters, 37.2% as nondieters. Extreme dieters were more likely to use alcohol, cigarettes, and/or marijuana and to attempt suicide and less likely to practice vigorous exercise. Moderate dieters were less likely to use cigarettes, marijuana and more likely to engage in vigorous exercise, with differences across gender-race categories. Results have relevance for developing multicomponent programs for adolescents.

Cluster-Randomized Trial to Increase Hepatitis B Testing among Koreans in Los Angeles.

PubMed

Bastani, Roshan; Glenn, Beth A; Maxwell, Annette E; Jo, Angela M; Herrmann, Alison K; Crespi, Catherine M; Wong, Weng K; Chang, L Cindy; Stewart, Susan L; Nguyen, Tung T; Chen, Moon S; Taylor, Victoria M

2015-09-01

In the United States, Korean immigrants experience a disproportionately high burden of chronic hepatitis B (HBV) viral infection and associated liver cancer compared with the general population. However, despite clear clinical guidelines, HBV serologic testing among Koreans remains persistently suboptimal. We conducted a cluster-randomized trial to evaluate a church-based small group intervention to improve HBV testing among Koreans in Los Angeles. Fifty-two Korean churches, stratified by size (small, medium, large) and location (Koreatown versus other), were randomized to intervention or control conditions. Intervention church participants attended a single-session small-group discussion on liver cancer and HBV testing, and control church participants attended a similar session on physical activity and nutrition. Outcome data consisted of self-reported HBV testing obtained via 6-month telephone follow-up interviews. We recruited 1,123 individuals, 18 to 64 years of age, across the 52 churches. Ninety-two percent of the sample attended the assigned intervention session and 86% completed the 6-month follow-up. Sample characteristics included were as follows: mean age 46 years, 65% female, 97% born in Korea, 69% completed some college, and 43% insured. In an intent-to-treat analysis, the intervention produced a statistically significant effect (OR = 4.9, P < 0.001), with 19% of intervention and 6% of control group participants reporting a HBV test. Our intervention was successful in achieving a large and robust effect in a population at high risk of HBV infection and sequelae. The intervention was fairly resource efficient and thus has high potential for replication in other high-risk Asian groups. ©2015 American Association for Cancer Research.

Effects of improved sanitation on diarrheal reduction for children under five in Idiofa, DR Congo: a cluster randomized trial.

PubMed

Cha, Seungman; Lee, JaeEun; Seo, DongSik; Park, Byoung Mann; Mansiangi, Paul; Bernard, Kabore; Mulakub-Yazho, Guy Jerome Nkay; Famasulu, Honore Minka

2017-09-19

The lack of safe water and sanitation contributes to the rampancy of diarrhea in many developing countries. This study describes the design of a cluster-randomized trial in Idiofa, the Democratic Republic of the Congo, seeking evidence of the impact of improved sanitation on diarrhea for children under four. Of the 276 quartiers, 18 quartiers were randomly allocated to the intervention or control arm. Seven hundred and-twenty households were sampled and the youngest under-four child in each household was registered for this study. The primary endpoint of the study is diarrheal incidence, prevalence and duration in children under five. Material subsidies will be provided only to the households who complete pit digging plus superstructure and roof construction, regardless of their income level. This study employs a Sanitation Calendar so that the mother of each household can record the diarrheal episodes of her under-four child on a daily basis. The diary enables examination of the effect of the sanitation intervention on diarrhea duration and also resolves the limitation of the small number of clusters in the trial. In addition, the project will be monitored through the 'Sanitation Map', on which all households in the study area, including both the control and intervention arms, are registered. To avoid information bias or courtesy bias, photos will be taken of the latrine during the household visit, and a supervisor will determine well-equipped latrine uptake based on the photos. This reduces the possibility of recall bias and under- or over-estimation of diarrhea, which was the main limitation of previous studies. The study was approved by the Institutional Review Board of the School of Public Health, Kinshasa University (ESP/CE/040/15; April 13, 2015) and registered as an International Standard Randomized Controlled Trial (ISRCTN: 10,419,317) on March 13, 2015.

Expanding Access to BRCA1/2 Genetic Counseling with Telephone Delivery: A Cluster Randomized Trial

PubMed Central

Butler, Karin M.; Schwartz, Marc D.; Mandelblatt, Jeanne S.; Boucher, Kenneth M.; Pappas, Lisa M.; Gammon, Amanda; Kohlmann, Wendy; Edwards, Sandra L.; Stroup, Antoinette M.; Buys, Saundra S.; Flores, Kristina G.; Campo, Rebecca A.

2014-01-01

Background The growing demand for cancer genetic services underscores the need to consider approaches that enhance access and efficiency of genetic counseling. Telephone delivery of cancer genetic services may improve access to these services for individuals experiencing geographic (rural areas) and structural (travel time, transportation, childcare) barriers to access. Methods This cluster-randomized clinical trial used population-based sampling of women at risk for BRCA1/2 mutations to compare telephone and in-person counseling for: 1) equivalency of testing uptake and 2) noninferiority of changes in psychosocial measures. Women 25 to 74 years of age with personal or family histories of breast or ovarian cancer and who were able to travel to one of 14 outreach clinics were invited to participate. Randomization was by family. Assessments were conducted at baseline one week after pretest and post-test counseling and at six months. Of the 988 women randomly assigned, 901 completed a follow-up assessment. Cluster bootstrap methods were used to estimate the 95% confidence interval (CI) for the difference between test uptake proportions, using a 10% equivalency margin. Differences in psychosocial outcomes for determining noninferiority were estimated using linear models together with one-sided 97.5% bootstrap CIs. Results Uptake of BRCA1/2 testing was lower following telephone (21.8%) than in-person counseling (31.8%, difference = 10.2%, 95% CI = 3.9% to 16.3%; after imputation of missing data: difference = 9.2%, 95% CI = -0.1% to 24.6%). Telephone counseling fulfilled the criteria for noninferiority to in-person counseling for all measures. Conclusions BRCA1/2 telephone counseling, although leading to lower testing uptake, appears to be safe and as effective as in-person counseling with regard to minimizing adverse psychological reactions, promoting informed decision making, and delivering patient-centered communication for both rural and urban women. PMID:25376862

The Effectiveness of Healthy Start Home Visit Program: Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Leung, Cynthia; Tsang, Sandra; Heung, Kitty

2015-01-01

Purpose: The study reported the effectiveness of a home visit program for disadvantaged Chinese parents with preschool children, using cluster randomized controlled trial design. Method: Participants included 191 parents and their children from 24 preschools, with 84 dyads (12 preschools) in the intervention group and 107 dyads (12 preschools) in…

Standardized Effect Size Measures for Mediation Analysis in Cluster-Randomized Trials

ERIC Educational Resources Information Center

Stapleton, Laura M.; Pituch, Keenan A.; Dion, Eric

2015-01-01

This article presents 3 standardized effect size measures to use when sharing results of an analysis of mediation of treatment effects for cluster-randomized trials. The authors discuss 3 examples of mediation analysis (upper-level mediation, cross-level mediation, and cross-level mediation with a contextual effect) with demonstration of the…

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

ERIC Educational Resources Information Center

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

2013-01-01

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

Fit 5 Kids TV reduction program for Latino preschoolers: A cluster randomized controlled trial

USDA-ARS?s Scientific Manuscript database

Reducing Latino preschoolers' TV viewing is needed to reduce their risk of obesity and other chronic diseases. This study's objective was to evaluate the Fit 5 Kids (F5K) TV reduction program's impact on Latino preschooler's TV viewing. The study design was a cluster randomized controlled trial (RCT...

Random phase approximation and cluster mean field studies of hard core Bose Hubbard model

NASA Astrophysics Data System (ADS)

Alavani, Bhargav K.; Gaude, Pallavi P.; Pai, Ramesh V.

2018-04-01

We investigate zero temperature and finite temperature properties of the Bose Hubbard Model in the hard core limit using Random Phase Approximation (RPA) and Cluster Mean Field Theory (CMFT). We show that our RPA calculations are able to capture quantum and thermal fluctuations significantly better than CMFT.

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

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, Eric C.

2013-01-01

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

Impact of Sampling Density on the Extent of HIV Clustering

PubMed Central

Novitsky, Vlad; Moyo, Sikhulile; Lei, Quanhong; DeGruttola, Victor

2014-01-01

Abstract Identifying and monitoring HIV clusters could be useful in tracking the leading edge of HIV transmission in epidemics. Currently, greater specificity in the definition of HIV clusters is needed to reduce confusion in the interpretation of HIV clustering results. We address sampling density as one of the key aspects of HIV cluster analysis. The proportion of viral sequences in clusters was estimated at sampling densities from 1.0% to 70%. A set of 1,248 HIV-1C env gp120 V1C5 sequences from a single community in Botswana was utilized in simulation studies. Matching numbers of HIV-1C V1C5 sequences from the LANL HIV Database were used as comparators. HIV clusters were identified by phylogenetic inference under bootstrapped maximum likelihood and pairwise distance cut-offs. Sampling density below 10% was associated with stochastic HIV clustering with broad confidence intervals. HIV clustering increased linearly at sampling density >10%, and was accompanied by narrowing confidence intervals. Patterns of HIV clustering were similar at bootstrap thresholds 0.7 to 1.0, but the extent of HIV clustering decreased with higher bootstrap thresholds. The origin of sampling (local concentrated vs. scattered global) had a substantial impact on HIV clustering at sampling densities ≥10%. Pairwise distances at 10% were estimated as a threshold for cluster analysis of HIV-1 V1C5 sequences. The node bootstrap support distribution provided additional evidence for 10% sampling density as the threshold for HIV cluster analysis. The detectability of HIV clusters is substantially affected by sampling density. A minimal genotyping density of 10% and sampling density of 50–70% are suggested for HIV-1 V1C5 cluster analysis. PMID:25275430

Bayesian Nonparametric Ordination for the Analysis of Microbial Communities.

PubMed

Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Holmes, Susan; Trippa, Lorenzo

2017-01-01

Human microbiome studies use sequencing technologies to measure the abundance of bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material. Typically the data are organized in contingency tables with OTU counts across heterogeneous biological samples. In the microbial ecology community, ordination methods are frequently used to investigate latent factors or clusters that capture and describe variations of OTU counts across biological samples. It remains important to evaluate how uncertainty in estimates of each biological sample's microbial distribution propagates to ordination analyses, including visualization of clusters and projections of biological samples on low dimensional spaces. We propose a Bayesian analysis for dependent distributions to endow frequently used ordinations with estimates of uncertainty. A Bayesian nonparametric prior for dependent normalized random measures is constructed, which is marginally equivalent to the normalized generalized Gamma process, a well-known prior for nonparametric analyses. In our prior, the dependence and similarity between microbial distributions is represented by latent factors that concentrate in a low dimensional space. We use a shrinkage prior to tune the dimensionality of the latent factors. The resulting posterior samples of model parameters can be used to evaluate uncertainty in analyses routinely applied in microbiome studies. Specifically, by combining them with multivariate data analysis techniques we can visualize credible regions in ecological ordination plots. The characteristics of the proposed model are illustrated through a simulation study and applications in two microbiome datasets.

Study protocol of Prednisone in episodic Cluster Headache (PredCH): a randomized, double-blind, placebo-controlled parallel group trial to evaluate the efficacy and safety of oral prednisone as an add-on therapy in the prophylactic treatment of episodic cluster headache with verapamil

PubMed Central

2013-01-01

Background Episodic cluster headache (ECH) is a primary headache disorder that severely impairs patient’s quality of life. First-line therapy in the initiation of a prophylactic treatment is verapamil. Due to its delayed onset of efficacy and the necessary slow titration of dosage for tolerability reasons prednisone is frequently added by clinicians to the initial prophylactic treatment of a cluster episode. This treatment strategy is thought to effectively reduce the number and intensity of cluster attacks in the beginning of a cluster episode (before verapamil is effective). This study will assess the efficacy and safety of oral prednisone as an add-on therapy to verapamil and compare it to a monotherapy with verapamil in the initial prophylactic treatment of a cluster episode. Methods and design PredCH is a prospective, randomized, double-blind, placebo-controlled trial with parallel study arms. Eligible patients with episodic cluster headache will be randomized to a treatment intervention with prednisone or a placebo arm. The multi-center trial will be conducted in eight German headache clinics that specialize in the treatment of ECH. Discussion PredCH is designed to assess whether oral prednisone added to first-line agent verapamil helps reduce the number and intensity of cluster attacks in the beginning of a cluster episode as compared to monotherapy with verapamil. Trial registration German Clinical Trials Register DRKS00004716 PMID:23889923

The Atacama Cosmology Telescope: Relation Between Galaxy Cluster Optical Richness and Sunyaev-Zel'dovich Effect

NASA Technical Reports Server (NTRS)

Sehgal, Neelima; Addison, Graeme; Battaglia, Nick; Battistelli, Elia S.; Bond, J. Richard; Das, Sudeep; Devlin, Mark J.; Dunkley, Joanna; Duenner, Rolando; Gralla, Megan;

Differentials in colostrum feeding among lactating women of block RS Pura of J and K: A lesson for nursing practice.

PubMed

Raina, Sunil Kumar; Mengi, Vijay; Singh, Gurdeep

2012-07-01

Breast feeding is universally and traditionally practicised in India. Experts advocate breast feeding as the best method of feeding young infants. To assess the role of various factors in determining colostrum feeding in block R. S. Pura of district Jammu. A stratified two-stage design with villages as the primary sampling unit and lactating mothers as secondary sampling unit. Villages were divided into different clusters on the basis of population and sampling units were selected by a simple random technique. Breastfeeding is almost universal in R. S. Pura. Differentials in discarding the first milk were not found to be important among various socioeconomic groups and the phenomenon appeared more general than specific.

A cluster-randomized trial of a college health center-based alcohol and sexual violence intervention (GIFTSS): Design, rationale, and baseline sample.

PubMed

Abebe, Kaleab Z; Jones, Kelley A; Rofey, Dana; McCauley, Heather L; Clark, Duncan B; Dick, Rebecca; Gmelin, Theresa; Talis, Janine; Anderson, Jocelyn; Chugani, Carla; Algarroba, Gabriela; Antonio, Ashley; Bee, Courtney; Edwards, Clare; Lethihet, Nadia; Macak, Justin; Paley, Joshua; Torres, Irving; Van Dusen, Courtney; Miller, Elizabeth

2018-02-01

Sexual violence (SV) on college campuses is common, especially alcohol-related SV. This is a 2-arm cluster randomized controlled trial to test a brief intervention to reduce risk for alcohol-related sexual violence (SV) among students receiving care from college health centers (CHCs). Intervention CHC staff are trained to deliver universal SV education to all students seeking care, to facilitate patient and provider comfort in discussing SV and related abusive experiences (including the role of alcohol). Control sites provide participants with information about drinking responsibly. Across 28 participating campuses (12 randomized to intervention and 16 to control), 2292 students seeking care at CHCs complete surveys prior to their appointment (baseline), immediately after (exit), 4months later (T2) and one year later (T3). The primary outcome is change in recognition of SV and sexual risk. Among those reporting SV exposure at baseline, changes in SV victimization, disclosure, and use of SV services are additional outcomes. Intervention effects will be assessed using generalized linear mixed models that account for clustering of repeated observations both within CHCs and within students. Slightly more than half of the participating colleges have undergraduate enrollment of ≥3000 students; two-thirds are public and almost half are urban. Among participants there were relatively more Asian (10 v 1%) and Black/African American (13 v 7%) and fewer White (58 v 74%) participants in the intervention compared to control. This study will offer the first formal assessment for SV prevention in the CHC setting. Clinical Trials #: NCT02355470. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

In a rural area of Bangladesh, traditional birth attendant training improved early infant feeding practices: a pragmatic cluster randomized trial.

PubMed

Talukder, Shamim; Farhana, Dina; Vitta, Bineti; Greiner, Ted

2017-01-01

In rural Bangladesh, most births take place at home. There is little evidence regarding the influence of traditional birth attendants (TBAs) or community volunteers (CVs) on early infant feeding practices. We conducted a pragmatic cluster randomized controlled trial in Panchagarh District to examine the effects of training and post-training supervision of TBAs/CVs on early breastfeeding practices. Nine unions were randomized into three groups of three unions. We compared outcomes between mothers in a control group (CG), those living in unions where TBAs/CVs had received a 5-day training in early feeding practices (TG) and those living in unions where TBAs/CVs were both trained and supervised (SG). A total of 1182 mothers of infants aged 0-6 months were interviewed at baseline. After 6 months of intervention, an endline survey was conducted on a different sample of 1148 mothers of infants aged 0-6 months in the same areas. In both intervention areas, TBAs/CVs made regular home visits and attended births whenever possible. Rates of early initiation of breastfeeding, avoidance of prelacteal feeds and exclusive breastfeeding were compared between groups using cluster-controlled mixed model logistic regression. At endline, both intervention groups had significantly higher proportions of mothers who reported early initiation of breastfeeding (CG: 88%, TG: 96%, SG: 96%) and avoidance of prelacteal feeds (CG: 48%, TG: 80%, SG: 88%) compared with the control group; there were no significant differences between the two intervention groups. The endline rates of reported exclusive breastfeeding were not significantly different among groups (CG: 67%, TG: 76%, SG: 83%). © 2016 John Wiley & Sons Ltd.

Bohman-Frieze-Wormald model on the lattice, yielding a discontinuous percolation transition

NASA Astrophysics Data System (ADS)

Schrenk, K. J.; Felder, A.; Deflorin, S.; Araújo, N. A. M.; D'Souza, R. M.; Herrmann, H. J.

2012-03-01

The BFW model introduced by Bohman, Frieze, and Wormald [Random Struct. Algorithms1042-983210.1002/rsa.20038, 25, 432 (2004)], and recently investigated in the framework of discontinuous percolation by Chen and D'Souza [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.106.115701 106, 115701 (2011)], is studied on the square and simple-cubic lattices. In two and three dimensions, we find numerical evidence for a strongly discontinuous transition. In two dimensions, the clusters at the threshold are compact with a fractal surface of fractal dimension df=1.49±0.02. On the simple-cubic lattice, distinct jumps in the size of the largest cluster are observed. We proceed to analyze the tree-like version of the model, where only merging bonds are sampled, for dimension two to seven. The transition is again discontinuous in any considered dimension. Finally, the dependence of the cluster-size distribution at the threshold on the spatial dimension is also investigated.

Stability of similarity measurements for bipartite networks

PubMed Central

Liu, Jian-Guo; Hou, Lei; Pan, Xue; Guo, Qiang; Zhou, Tao

2016-01-01

Similarity is a fundamental measure in network analyses and machine learning algorithms, with wide applications ranging from personalized recommendation to socio-economic dynamics. We argue that an effective similarity measurement should guarantee the stability even under some information loss. With six bipartite networks, we investigate the stabilities of fifteen similarity measurements by comparing the similarity matrixes of two data samples which are randomly divided from original data sets. Results show that, the fifteen measurements can be well classified into three clusters according to their stabilities, and measurements in the same cluster have similar mathematical definitions. In addition, we develop a top-n-stability method for personalized recommendation, and find that the unstable similarities would recommend false information to users, and the performance of recommendation would be largely improved by using stable similarity measurements. This work provides a novel dimension to analyze and evaluate similarity measurements, which can further find applications in link prediction, personalized recommendation, clustering algorithms, community detection and so on. PMID:26725688

Image Registration Algorithm Based on Parallax Constraint and Clustering Analysis

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-01-01

To resolve the problem of slow computation speed and low matching accuracy in image registration, a new image registration algorithm based on parallax constraint and clustering analysis is proposed. Firstly, Harris corner detection algorithm is used to extract the feature points of two images. Secondly, use Normalized Cross Correlation (NCC) function to perform the approximate matching of feature points, and the initial feature pair is obtained. Then, according to the parallax constraint condition, the initial feature pair is preprocessed by K-means clustering algorithm, which is used to remove the feature point pairs with obvious errors in the approximate matching process. Finally, adopt Random Sample Consensus (RANSAC) algorithm to optimize the feature points to obtain the final feature point matching result, and the fast and accurate image registration is realized. The experimental results show that the image registration algorithm proposed in this paper can improve the accuracy of the image matching while ensuring the real-time performance of the algorithm.

Stability of similarity measurements for bipartite networks.

PubMed

Liu, Jian-Guo; Hou, Lei; Pan, Xue; Guo, Qiang; Zhou, Tao

2016-01-04

Similarity is a fundamental measure in network analyses and machine learning algorithms, with wide applications ranging from personalized recommendation to socio-economic dynamics. We argue that an effective similarity measurement should guarantee the stability even under some information loss. With six bipartite networks, we investigate the stabilities of fifteen similarity measurements by comparing the similarity matrixes of two data samples which are randomly divided from original data sets. Results show that, the fifteen measurements can be well classified into three clusters according to their stabilities, and measurements in the same cluster have similar mathematical definitions. In addition, we develop a top-n-stability method for personalized recommendation, and find that the unstable similarities would recommend false information to users, and the performance of recommendation would be largely improved by using stable similarity measurements. This work provides a novel dimension to analyze and evaluate similarity measurements, which can further find applications in link prediction, personalized recommendation, clustering algorithms, community detection and so on.

Physiogenomic analysis of the Puerto Rican population

PubMed Central

Ruaño, Gualberto; Duconge, Jorge; Windemuth, Andreas; Cadilla, Carmen L; Kocherla, Mohan; Villagra, David; Renta, Jessica; Holford, Theodore; Santiago-Borrero, Pedro J

2009-01-01

Aims Admixture in the population of the island of Puerto Rico is of general interest with regards to pharmacogenetics to develop comprehensive strategies for personalized healthcare in Latin Americans. This research was aimed at determining the frequencies of SNPs in key physiological, pharmacological and biochemical genes to infer population structure and ancestry in the Puerto Rican population. Materials & methods A noninterventional, cross-sectional, retrospective study design was implemented following a controlled, stratified-by-region, random sampling protocol. The sample was based on birthrates in each region of the island of Puerto Rico, according to the 2004 National Birth Registry. Genomic DNA samples from 100 newborns were obtained from the Puerto Rico Newborn Screening Program in dried-blood spot cards. Genotyping using a physiogenomic array was performed for 332 SNPs from 196 cardiometabolic and neuroendocrine genes. Population structure was examined using a Bayesian clustering approach as well as by allelic dissimilarity as a measure of allele sharing. Results The Puerto Rican sample was found to be broadly heterogeneous. We observed three main clusters in the population, which we hypothesize to reflect the historical admixture in the Puerto Rican population from Amerindian, African and European ancestors. We present evidence for this interpretation by comparing allele frequencies for the three clusters with those for the same SNPs available from the International HapMap project for Asian, African and European populations. Conclusion Our results demonstrate that population analysis can be performed with a physiogenomic array of cardiometabolic and neuroendocrine genes to facilitate the translation of genome diversity into personalized medicine. PMID:19374515

Deeper Insights into the Circumgalactic Medium using Multivariate Analysis Methods

NASA Astrophysics Data System (ADS)

Lewis, James; Churchill, Christopher W.; Nielsen, Nikole M.; Kacprzak, Glenn

2017-01-01

Drawing from a database of galaxies whose surrounding gas has absorption from MgII, called the MgII-Absorbing Galaxy Catalog (MAGIICAT, Neilsen et al 2013), we studied the circumgalactic medium (CGM) for a sample of 47 galaxies. Using multivariate analysis, in particular the k-means clustering algorithm, we determined that simultaneously examining column density (N), rest-frame B-K color, virial mass, and azimuthal angle (the projected angle between the galaxy major axis and the quasar line of sight) yields two distinct populations: (1) bluer, lower mass galaxies with higher column density along the minor axis, and (2) redder, higher mass galaxies with lower column density along the major axis. We support this grouping by running (i) two-sample, two-dimensional Kolmogorov-Smirnov (KS) tests on each of the six bivariate planes and (ii) two-sample KS tests on each of the four variables to show that the galaxies significantly cluster into two independent populations. To account for the fact that 16 of our 47 galaxies have upper limits on N, we performed Monte-Carlo tests whereby we replaced upper limits with random deviates drawn from a Schechter distribution fit, f(N). These tests strengthen the results of the KS tests. We examined the behavior of the MgII λ2796 absorption line equivalent width and velocity width for each galaxy population. We find that equivalent width and velocity width do not show similar characteristic distinctions between the two galaxy populations. We discuss the k-means clustering algorithm for optimizing the analysis of populations within datasets as opposed to using arbitrary bivariate subsample cuts. We also discuss the power of the k-means clustering algorithm in extracting deeper physical insight into the CGM in relationship to host galaxies.

Galaxy And Mass Assembly (GAMA): colour- and luminosity-dependent clustering from calibrated photometric redshifts

NASA Astrophysics Data System (ADS)

Christodoulou, L.; Eminian, C.; Loveday, J.; Norberg, P.; Baldry, I. K.; Hurley, P. D.; Driver, S. P.; Bamford, S. P.; Hopkins, A. M.; Liske, J.; Peacock, J. A.; Bland-Hawthorn, J.; Brough, S.; Cameron, E.; Conselice, C. J.; Croom, S. M.; Frenk, C. S.; Gunawardhana, M.; Jones, D. H.; Kelvin, L. S.; Kuijken, K.; Nichol, R. C.; Parkinson, H.; Pimbblet, K. A.; Popescu, C. C.; Prescott, M.; Robotham, A. S. G.; Sharp, R. G.; Sutherland, W. J.; Taylor, E. N.; Thomas, D.; Tuffs, R. J.; van Kampen, E.; Wijesinghe, D.

2012-09-01

We measure the two-point angular correlation function of a sample of 4289 223 galaxies with r < 19.4 mag from the Sloan Digital Sky Survey (SDSS) as a function of photometric redshift, absolute magnitude and colour down to Mr - 5 log h = -14 mag. Photometric redshifts are estimated from ugriz model magnitudes and two Petrosian radii using the artificial neural network package ANNz, taking advantage of the Galaxy And Mass Assembly (GAMA) spectroscopic sample as our training set. These photometric redshifts are then used to determine absolute magnitudes and colours. For all our samples, we estimate the underlying redshift and absolute magnitude distributions using Monte Carlo resampling. These redshift distributions are used in Limber's equation to obtain spatial correlation function parameters from power-law fits to the angular correlation function. We confirm an increase in clustering strength for sub-L* red galaxies compared with ˜L* red galaxies at small scales in all redshift bins, whereas for the blue population the correlation length is almost independent of luminosity for ˜L* galaxies and fainter. A linear relation between relative bias and log luminosity is found to hold down to luminosities L ˜ 0.03L*. We find that the redshift dependence of the bias of the L* population can be described by the passive evolution model of Tegmark & Peebles. A visual inspection of a random sample from our r < 19.4 sample of SDSS galaxies reveals that about 10 per cent are spurious, with a higher contamination rate towards very faint absolute magnitudes due to over-deblended nearby galaxies. We correct for this contamination in our clustering analysis.

Multilevel Analysis of Trachomatous Trichiasis and Corneal Opacity in Nigeria: The Role of Environmental and Climatic Risk Factors on the Distribution of Disease.

PubMed

Smith, Jennifer L; Sivasubramaniam, Selvaraj; Rabiu, Mansur M; Kyari, Fatima; Solomon, Anthony W; Gilbert, Clare

2015-01-01

The distribution of trachoma in Nigeria is spatially heterogeneous, with large-scale trends observed across the country and more local variation within areas. Relative contributions of individual and cluster-level risk factors to the geographic distribution of disease remain largely unknown. The primary aim of this analysis is to assess the relationship between climatic factors and trachomatous trichiasis (TT) and/or corneal opacity (CO) due to trachoma in Nigeria, while accounting for the effects of individual risk factors and spatial correlation. In addition, we explore the relative importance of variation in the risk of trichiasis and/or corneal opacity (TT/CO) at different levels. Data from the 2007 National Blindness and Visual Impairment Survey were used for this analysis, which included a nationally representative sample of adults aged 40 years and above. Complete data were available from 304 clusters selected using a multi-stage stratified cluster-random sampling strategy. All participants (13,543 individuals) were interviewed and examined by an ophthalmologist for the presence or absence of TT and CO. In addition to field-collected data, remotely sensed climatic data were extracted for each cluster and used to fit Bayesian hierarchical logistic models to disease outcome. The risk of TT/CO was associated with factors at both the individual and cluster levels, with approximately 14% of the total variation attributed to the cluster level. Beyond established individual risk factors (age, gender and occupation), there was strong evidence that environmental/climatic factors at the cluster-level (lower precipitation, higher land surface temperature, higher mean annual temperature and rural classification) were also associated with a greater risk of TT/CO. This study establishes the importance of large-scale risk factors in the geographical distribution of TT/CO in Nigeria, supporting anecdotal evidence that environmental conditions are associated with increased risk in this context and highlighting their potential use in improving estimates of disease burden at large scales.

A clinical carepath for obese pregnant women: A pragmatic pilot cluster randomized controlled trial.

PubMed

McDonald, Sarah D; Viaje, Kristen A; Rooney, Rebecca A; Jarde, Alexander; Giglia, Lucia; Maxwell, Cynthia V; Small, David; Kelly, Tracy Pearce; Midwifery, B H Sc; Sabatino, Lisa; Thabane, Lehana

2018-05-17

Obese women are at increased risks for complications during pregnancy, birth and in their infants. Although guidelines have been established for the clinical care of obese pregnant women, management is sometimes suboptimal. Our goal was to determine the feasibility of implementing and testing a clinical carepath for obese pregnant women compared to standard care, in a pilot cluster randomized controlled trial (RCT). A pragmatic pilot cluster RCT was conducted, randomly allocating eight clinics to the carepath or standard care for obese pregnant women. Women were eligible if they had a prepregnancy body mass index of ≥ 30 kg/m 2 and a viable singleton < 21 weeks. The primary outcomes were the feasibility of conducting a full-scale cluster RCT (defined as > 80%: randomization of clinics, use in eligible women, and completeness of follow-up) and of the intervention (defined as > 80%: compliance with each step in the carepath, and recommendation of the carepath by clinicians to a colleague). All eight approached clinics agreed to participate and were randomized. Half of the intervention clinics used the carepath, resulting in < 80% uptake of eligible women. High follow-up (99.5%) was achieved, in 188 of 189 women. The carepath was feasible for numerous guideline-directed recommendations for screening, but less so for counselling topics. When the carepath was used in the majority of women, all clinicians, most of whom were midwives, reported they would recommend it to a colleague. The intervention group had significantly higher overall adherence to the guideline recommendations compared to control (relative risk 1.71, 95% confidence interval 1.57-1.87). In this pragmatic pilot cluster RCT, a guideline-directed clinical carepath improved some aspects of care of obese pregnant women and was recommended by clinicians, particularly midwives. A cluster RCT may not be feasible in a mix of obstetric and midwifery clinics, but may be feasible in midwifery clinics. This pragmatic pilot cluster RCT was registered on clinicaltrials.gov (identifier: NCT02534051 ).

Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials

PubMed Central

Gomes, Manuel; Ng, Edmond S.-W.; Nixon, Richard; Carpenter, James; Thompson, Simon G.

2012-01-01

Aim. Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Methods. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering—seemingly unrelated regression (SUR) without a robust standard error (SE)—and 4 methods that recognized clustering—SUR and generalized estimating equations (GEEs), both with robust SE, a “2-stage” nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Results. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92–0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. Conclusions. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters. PMID:22016450

Random isotropic one-dimensional XY-model

NASA Astrophysics Data System (ADS)

Gonçalves, L. L.; Vieira, A. P.

1998-01-01

The 1D isotropic s = ½XY-model ( N sites), with random exchange interaction in a transverse random field is considered. The random variables satisfy bimodal quenched distributions. The solution is obtained by using the Jordan-Wigner fermionization and a canonical transformation, reducing the problem to diagonalizing an N × N matrix, corresponding to a system of N noninteracting fermions. The calculations are performed numerically for N = 1000, and the field-induced magnetization at T = 0 is obtained by averaging the results for the different samples. For the dilute case, in the uniform field limit, the magnetization exhibits various discontinuities, which are the consequence of the existence of disconnected finite clusters distributed along the chain. Also in this limit, for finite exchange constants J A and J B, as the probability of J A varies from one to zero, the saturation field is seen to vary from Γ A to Γ B, where Γ A(Γ B) is the value of the saturation field for the pure case with exchange constant equal to J A(J B) .

Review of Recent Methodological Developments in Group-Randomized Trials: Part 1—Design

PubMed Central

Li, Fan; Gallis, John A.; Prague, Melanie; Murray, David M.

2017-01-01

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have highlighted the developments of the past 13 years in design with a companion article to focus on developments in analysis. As a pair, these articles update the 2004 review. We have discussed developments in the topics of the earlier review (e.g., clustering, matching, and individually randomized group-treatment trials) and in new topics, including constrained randomization and a range of randomized designs that are alternatives to the standard parallel-arm GRT. These include the stepped-wedge GRT, the pseudocluster randomized trial, and the network-randomized GRT, which, like the parallel-arm GRT, require clustering to be accounted for in both their design and analysis. PMID:28426295

Review of Recent Methodological Developments in Group-Randomized Trials: Part 1-Design.

PubMed

Turner, Elizabeth L; Li, Fan; Gallis, John A; Prague, Melanie; Murray, David M

2017-06-01

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have highlighted the developments of the past 13 years in design with a companion article to focus on developments in analysis. As a pair, these articles update the 2004 review. We have discussed developments in the topics of the earlier review (e.g., clustering, matching, and individually randomized group-treatment trials) and in new topics, including constrained randomization and a range of randomized designs that are alternatives to the standard parallel-arm GRT. These include the stepped-wedge GRT, the pseudocluster randomized trial, and the network-randomized GRT, which, like the parallel-arm GRT, require clustering to be accounted for in both their design and analysis.

[Amplicon density-weighted algorithms for analyzing dissimilarity and dynamic alterations of RAPD polymorphisms of Cordyceps sinensis].

PubMed

Yao, Yi-sang; Gao, Ling; Li, Yu-ling; Ma, Shao-li; Wu, Zi-mei; Tan, Ning-zhi; Wu, Jian-yong; Ni, Lu-qun; Zhu, Jia-shi

2014-08-18

To examine the dynamic maturational alterations of random amplified polymorphic DNA (RAPD) molecular marker polymorphism resulted from differential expressions of multiple fungi in the caterpillar body, stroma and ascocarp portion of Cordyceps sinensis (Cs). Used the fuzzy, integral RAPD molecular marker polymorphism method with 20 random primers; used density-weighted cluster algorithms and ZUNIX similarity equations; compared RAPD polymorphisms of the caterpillar body, stroma and ascocarp of Cs during maturation; and compared RAPD polymorphisms of Cs and Hirsutella sinensis (Hs). Density-unweighted algorithms neglected the differences in density of the DNA amplicons. Use of the density-weighted ZUNIX similarity equations and the clustering method integrated components of the amplicon density differences in similarity computations and clustering construction and prevented from the loss of the information of fungal genomes. An overall similarity 0.42 (< the overall dissimilarity 0.58) was observed for all compartments of Cs at different maturation stages. The similarities for the stromata or caterpillar bodies of Cs at 3 maturational stages were 0.57 or 0.50, respectively. During Cs maturation, there were dynamic Low→High→Low alterations of the RAPD polymorphisms between stromata and caterpillar bodies dissected from the same pieces of Cs. The polymorphic similarity was the highest (0.87) between the ascocarp and mature stroma, forming a clustering clade, while the premature stroma and caterpillar body formed another clade. These 2 clades merged into one cluster. Another clade containing the maturing stroma and caterpillar body merged with mature caterpillar body, forming another cluster. The RAPD polymorphic similarities between Hs and Cs samples were 0.55-0.69. Hs were separated from Cs clusters by the out-group control Paecilomyces militaris. The wealthy RAPD polymorphisms change dynamically in the Cs compartments with maturation. The different RAPD polymorphism for Hs from those for Cs supports the hypothesis of integrated micro-ecosystem Cs with multiple fungi, but does not support the "single fungal species" hypothesis for Cs and the anamorph-teleomorph connection between Hs and Cs.

Energetic Materials Effects on Essential Soil Processes: Decomposition of Orchard Grass (Dactylis glomerata) Litter in Soil Contaminated with Energetic Materials

DTIC Science & Technology

2014-02-01

moisture level of 14% dry soil mass was maintained for the duration of the study by weekly additions of ASTM Type I water. Soil samples were collected...maintain the initial soil moisture level. One cluster of Orchard grass straw was harvested from a set of randomly selected replicate containers...decomposition is among the most integrating processes within the soil ecosystem because it involves complex interactions of soil microbial, plant , and

Theory-based behavioral intervention increases self-reported physical activity in South African men: a cluster-randomized controlled trial.

PubMed

Jemmott, John B; Jemmott, Loretta S; Ngwane, Zolani; Zhang, Jingwen; Heeren, G Anita; Icard, Larry D; O'Leary, Ann; Mtose, Xoliswa; Teitelman, Anne; Carty, Craig

2014-07-01

To determine whether a health-promotion intervention increases South African men's adherence to physical-activity guidelines. We utilized a cluster-randomized controlled trial design. Eligible clusters, residential neighborhoods near East London, South Africa, were matched in pairs. Within randomly selected pairs, neighborhoods were randomized to theory-based, culturally congruent health-promotion intervention encouraging physical activity or attention-matched HIV/STI risk-reduction control intervention. Men residing in the neighborhoods and reporting coitus in the previous 3 months were eligible. Primary outcome was self-reported individual-level adherence to physical-activity guidelines averaged over 6-month and 12-month post-intervention assessments. Data were collected in 2007-2010. Data collectors, but not facilitators or participants, were blind to group assignment. Primary outcome intention-to-treat analysis included 22 of 22 clusters and 537 of 572 men in the health-promotion intervention and 22 of 22 clusters and 569 of 609 men in the attention-control intervention. Model-estimated probability of meeting physical-activity guidelines was 51.0% in the health-promotion intervention and 44.7% in attention-matched control (OR=1.34; 95% CI, 1.09-1.63), adjusting for baseline prevalence and clustering from 44 neighborhoods. A theory-based culturally congruent intervention increased South African men's self-reported physical activity, a key contributor to deaths from non-communicable diseases in South Africa. ClinicalTrials.gov Identifier: NCT01490359. Copyright © 2014 Elsevier Inc. All rights reserved.

Cluster mass inference via random field theory.

PubMed

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

2009-01-01

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

Camino Verde (The Green Way): evidence-based community mobilisation for dengue control in Nicaragua and Mexico: feasibility study and study protocol for a randomised controlled trial.

PubMed

Andersson, Neil; Arostegui, Jorge; Nava-Aguilera, Elizabeth; Harris, Eva; Ledogar, Robert J

2017-05-30

Since the Aedes aegypti mosquitoes that transmit dengue virus can breed in clean water, WHO-endorsed vector control strategies place sachets of organophosphate pesticide, temephos (Abate), in household water storage containers. These and other pesticide-dependent approaches have failed to curb the spread of dengue and multiple dengue virus serotypes continue to spread throughout tropical and subtropical regions worldwide. A feasibility study in Managua, Nicaragua, generated instruments, intervention protocols, training schedules and impact assessment tools for a cluster randomised controlled trial of community-based approaches to vector control comprising an alternative strategy for dengue prevention and control in Nicaragua and Mexico. The Camino Verde (Green Way) is a pragmatic parallel group trial of pesticide-free dengue vector control, adding effectiveness to the standard government dengue control. A random sample from the most recent census in three coastal regions of Guerrero state in Mexico will generate 90 study clusters and the equivalent sampling frame in Managua, Nicaragua will generate 60 clusters, making a total of 150 clusters each of 137-140 households. After a baseline study, computer-driven randomisation will allocate to intervention one half of the sites, stratified by country, evidence of recent dengue virus infection in children aged 3-9 years and, in Nicaragua, level of community organisation. Following a common evidence-based education protocol, each cluster will develop and implement its own collective interventions including house-to-house visits, school-based programmes and inter-community visits. After 18 months, a follow-up study will compare dengue history, serological evidence of recent dengue virus infection (via measurement of anti-dengue virus antibodies in saliva samples) and entomological indices between intervention and control sites. Our hypothesis is that informed community mobilisation adds effectiveness in controlling dengue. ISRCTN27581154 .

Evaluation of immunization coverage by lot quality assurance sampling compared with 30-cluster sampling in a primary health centre in India.

PubMed

Singh, J; Jain, D C; Sharma, R S; Verghese, T

1996-01-01

The immunization coverage of infants, children and women residing in a primary health centre (PHC) area in Rajasthan was evaluated both by lot quality assurance sampling (LQAS) and by the 30-cluster sampling method recommended by WHO's Expanded Programme on Immunization (EPI). The LQAS survey was used to classify 27 mutually exclusive subunits of the population, defined as residents in health subcentre areas, on the basis of acceptable or unacceptable levels of immunization coverage among infants and their mothers. The LQAS results from the 27 subcentres were also combined to obtain an overall estimate of coverage for the entire population of the primary health centre, and these results were compared with the EPI cluster survey results. The LQAS survey did not identify any subcentre with a level of immunization among infants high enough to be classified as acceptable; only three subcentres were classified as having acceptable levels of tetanus toxoid (TT) coverage among women. The estimated overall coverage in the PHC population from the combined LQAS results showed that a quarter of the infants were immunized appropriately for their ages and that 46% of their mothers had been adequately immunized with TT. Although the age groups and the periods of time during which the children were immunized differed for the LQAS and EPI survey populations, the characteristics of the mothers were largely similar. About 57% (95% CI, 46-67) of them were found to be fully immunized with TT by 30-cluster sampling, compared with 46% (95% CI, 41-51) by stratified random sampling. The difference was not statistically significant. The field work to collect LQAS data took about three times longer, and cost 60% more than the EPI survey. The apparently homogeneous and low level of immunization coverage in the 27 subcentres makes this an impractical situation in which to apply LQAS, and the results obtained were therefore not particularly useful. However, if LQAS had been applied by local staff in an area with overall high coverage and population subunits with heterogeneous coverage, the method would have been less costly and should have produced useful results.

Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

PubMed

Wang, Wei; Griswold, Michael E

2016-11-30

The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Efficacy of a Universal Parent Training Program (HOPE-20): Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Leung, Cynthia; Tsang, Sandra; Kwan, H. W.

2017-01-01

Objective: This study examined the efficacy of Hands-On Parent Empowerment-20 (HOPE-20) program. Methods: Eligible participants were parents residing in Hong Kong with target children aged 2 years attending nursery schools. Cluster randomized control trial was adopted, with 10 schools (110 participants) assigned to intervention group and 8 schools…

Motivational Pathways to Leisure-Time Physical Activity Participation in Urban Physical Education: A Cluster-Randomized Trial

ERIC Educational Resources Information Center

Yli-Piipari, Sami; Layne, Todd; Hinson, Janet; Irwin, Carol

2018-01-01

Purpose: Grounded in the trans-contextual model of motivation framework, this cluster-randomized trial examined the effectiveness of an autonomy supportive physical education (PE) instruction on student motivation and physical activity (PA). Method: The study comprised six middle schools and 408 students (M[subscript age] = 12.29), with primary…

A Multisite Cluster Randomized Field Trial of Open Court Reading

ERIC Educational Resources Information Center

Borman, Geoffrey D.; Dowling, N. Maritza; Schneck, Carrie

2008-01-01

In this article, the authors report achievement outcomes of a multisite cluster randomized field trial of Open Court Reading 2005 (OCR), a K-6 literacy curriculum published by SRA/McGraw-Hill. The participants are 49 first-grade through fifth-grade classrooms from predominantly minority and poor contexts across the nation. Blocking by grade level…

Clogging and depinning of ballistic active matter systems in disordered media

NASA Astrophysics Data System (ADS)

Reichhardt, C.; Reichhardt, C. J. O.

2018-05-01

We numerically examine ballistic active disks driven through a random obstacle array. Formation of a pinned or clogged state occurs at much lower obstacle densities for the active disks than for passive disks. As a function of obstacle density, we identify several distinct phases including a depinned fluctuating cluster state, a pinned single-cluster or jammed state, a pinned multicluster state, a pinned gel state, and a pinned disordered state. At lower active disk densities, a drifting uniform liquid forms in the absence of obstacles, but when even a small number of obstacles are introduced, the disks organize into a pinned phase-separated cluster state in which clusters nucleate around the obstacles, similar to a wetting phenomenon. We examine how the depinning threshold changes as a function of disk or obstacle density and find a crossover from a collectively pinned cluster state to a disordered plastic depinning transition as a function of increasing obstacle density. We compare this to the behavior of nonballistic active particles and show that as we vary the activity from completely passive to completely ballistic, a clogged phase-separated state appears in both the active and passive limits, while for intermediate activity, a readily flowing liquid state appears and there is an optimal activity level that maximizes the flux through the sample.

Community-wide intervention and population-level physical activity: a 5-year cluster randomized trial.

PubMed

Kamada, Masamitsu; Kitayuguchi, Jun; Abe, Takafumi; Taguri, Masataka; Inoue, Shigeru; Ishikawa, Yoshiki; Bauman, Adrian; Lee, I-Min; Miyachi, Motohiko; Kawachi, Ichiro

2018-04-01

Evidence from a limited number of short-term trials indicates the difficulty in achieving population-level improvements in physical activity (PA) through community-wide interventions (CWIs). We sought to evaluate the effectiveness of a 5-year CWI for promoting PA in middle-aged and older adults using a cluster randomized design. We randomized 12 communities in Unnan, Japan, to either intervention (9) or control (3). Additionally, intervention communities were randomly allocated to three subgroups by different PA types promoted. Randomly sampled residents aged 40-79 years responded to the baseline survey (n = 4414; 74%) and were followed at 1, 3 and 5 years (78-83% response rate). The intervention was a 5-year CWI using social marketing to promote PA. The primary outcome was a change in recommended levels of PA. Compared with control communities, adults achieving recommended levels of PA increased in intervention communities [adjusted change difference = 4.6 percentage points (95% confidence interval: 0.4, 8.8)]. The intervention was effective for promoting all types of recommended PAs, i.e. aerobic (walking, 6.4%), flexibility (6.1%) and muscle-strengthening activities (5.7%). However, a bundled approach, which attempted to promote all forms of PAs above simultaneously, was not effective (1.3-3.4%, P ≥ 0.138). Linear dose-response relationships between the CWI awareness and changes in PA were observed (P ≤ 0.02). Pain intensity decreased in shoulder (intervention and control) and lower back (intervention only) but there was little change difference in all musculoskeletal pain outcomes between the groups. The 5-year CWI using the focused social marketing strategy increased the population-level of PA.

Community-wide intervention and population-level physical activity: a 5-year cluster randomized trial

PubMed Central

Kamada, Masamitsu; Kitayuguchi, Jun; Abe, Takafumi; Taguri, Masataka; Inoue, Shigeru; Ishikawa, Yoshiki; Bauman, Adrian; Lee, I-Min; Miyachi, Motohiko; Kawachi, Ichiro

2018-01-01

Abstract Background Evidence from a limited number of short-term trials indicates the difficulty in achieving population-level improvements in physical activity (PA) through community-wide interventions (CWIs). We sought to evaluate the effectiveness of a 5-year CWI for promoting PA in middle-aged and older adults using a cluster randomized design. Methods We randomized 12 communities in Unnan, Japan, to either intervention (9) or control (3). Additionally, intervention communities were randomly allocated to three subgroups by different PA types promoted. Randomly sampled residents aged 40–79 years responded to the baseline survey (n = 4414; 74%) and were followed at 1, 3 and 5 years (78–83% response rate). The intervention was a 5-year CWI using social marketing to promote PA. The primary outcome was a change in recommended levels of PA. Results Compared with control communities, adults achieving recommended levels of PA increased in intervention communities [adjusted change difference = 4.6 percentage points (95% confidence interval: 0.4, 8.8)]. The intervention was effective for promoting all types of recommended PAs, i.e. aerobic (walking, 6.4%), flexibility (6.1%) and muscle-strengthening activities (5.7%). However, a bundled approach, which attempted to promote all forms of PAs above simultaneously, was not effective (1.3–3.4%, P ≥ 0.138). Linear dose–response relationships between the CWI awareness and changes in PA were observed (P ≤ 0.02). Pain intensity decreased in shoulder (intervention and control) and lower back (intervention only) but there was little change difference in all musculoskeletal pain outcomes between the groups. Conclusions The 5-year CWI using the focused social marketing strategy increased the population-level of PA. PMID:29228255

The Incomplete Conditional Stellar Mass Function: Unveiling the Stellar Mass Functions of Galaxies at 0.1 < Z < 0.8 from BOSS Observations

NASA Astrophysics Data System (ADS)

Guo, Hong; Yang, Xiaohu; Lu, Yi

2018-05-01

We propose a novel method to constrain the missing fraction of galaxies using galaxy clustering measurements in the galaxy conditional stellar mass function (CSMF) framework, which is applicable to surveys that suffer significantly from sample selection effects. The clustering measurements, which are not sensitive to the random sampling (missing fraction) of galaxies, are widely used to constrain the stellar–halo mass relation (SHMR). By incorporating a missing fraction (incompleteness) component into the CSMF model (ICSMF), we use the incomplete stellar mass function and galaxy clustering to simultaneously constrain the missing fractions and the SHMRs. Tests based on mock galaxy catalogs with a few typical missing fraction models show that this method can accurately recover the missing fraction and the galaxy SHMR, hence providing us with reliable measurements of the galaxy stellar mass functions. We then apply it to the Baryon Oscillation Spectroscopic Survey (BOSS) over the redshift range of 0.1 < z < 0.8 for galaxies of M * > 1011 M ⊙. We find that the sample completeness for BOSS is over 80% at z < 0.6 but decreases at higher redshifts to about 30%. After taking these completeness factors into account, we provide accurate measurements of the stellar mass functions for galaxies with {10}11 {M}ȯ < {M}* < {10}12 {M}ȯ , as well as the SHMRs, over the redshift range 0.1 < z < 0.8 in this largest galaxy redshift survey.

Are There Subtypes of Panic Disorder? An Interpersonal Perspective

PubMed Central

Zilcha-Mano, Sigal; McCarthy, Kevin S.; Dinger, Ulrike; Chambless, Dianne L.; Milrod, Barbara L.; Kunik, Lauren; Barber, Jacques P.

2015-01-01

Objective Panic disorder (PD) is associated with significant personal, social, and economic costs. However, little is known about specific interpersonal dysfunctions that characterize the PD population. The current study systematically examined these interpersonal dysfunctions. Method The present analyses included 194 patients with PD out of a sample of 201 who were randomized to cognitive-behavioral therapy, panic-focused psychodynamic psychotherapy, or applied relaxation training. Interpersonal dysfunction was measured using the Inventory of Interpersonal Problems–Circumplex (Horowitz, Alden, Wiggins, & Pincus, 2000). Results Individuals with PD reported greater levels of interpersonal distress than that of a normative cohort (especially when PD was accompanied by agoraphobia), but lower than that of a cohort of patients with major depression. There was no single interpersonal profile that characterized PD patients. Symptom-based clusters (with versus without agoraphobia) could not be discriminated on core or central interpersonal problems. Rather, as revealed by cluster analysis based on the pathoplasticity framework, there were two empirically derived interpersonal clusters among PD patients which were not accounted for by symptom severity and were opposite in nature: domineering-intrusive and nonassertive. The empirically derived interpersonal clusters appear to be of clinical utility in predicting alliance development throughout treatment: While the domineering-intrusive cluster did not show any changes in the alliance throughout treatment, the non-assertive cluster showed a process of significant strengthening of the alliance. Conclusions Empirically derived interpersonal clusters in PD provide clinically useful and non-redundant information about individuals with PD. PMID:26030762

Social Influences on the Clustering of Underage Risky Drinking and Its Consequences in Communities

PubMed Central

Reboussin, Beth A.; Song, Eun-Young; Wolfson, Mark

2012-01-01

Objective: The purpose of this research was to examine whether the clustering of underage risky drinking and its consequences within communities might arise from shared perceptions regarding underage drinking as well as the social context of drinking. Method: The Enforcing Underage Drinking Laws Randomized Community Trial provided data from repeated cross-sectional samples of 5,017 current drinkers (2,619 male) ages 14–20 years from 68 communities surveyed in 2004, 2006, and 2007. Alternating logistic regressions were used to estimate the influence of social factors on the clustering of getting drunk, heavy episodic drinking, nonviolent consequences, and driving after drinking or riding with a drinking driver. Results: The clustering of getting drunk, heavy episodic drinking, and nonviolent consequences was no longer statistically significant after adjustment for drinking with friends and drinking with parents. Parents providing alcohol explained the clustering of heavy episodic drinking and nonviolent consequences, whereas drinking with other underage drinkers and friends providing alcohol explained the clustering of nonviolent consequences. Drinking with friends or other underage drinkers and friends providing alcohol increased the risk of these behaviors, whereas drinking with parents and parents providing alcohol were protective. Perceptions regarding peer drinking, community norms, consequences for drinking, and drinking at a party did not influence clustering. Conclusions: These findings suggest that interventions to reduce underage risky drinking in communities should focus on the differential effects of the social context in which drinking occurs. PMID:23036206

Novel approaches to pin cluster synchronization on complex dynamical networks in Lur'e forms

NASA Astrophysics Data System (ADS)

Tang, Ze; Park, Ju H.; Feng, Jianwen

2018-04-01

This paper investigates the cluster synchronization of complex dynamical networks consisted of identical or nonidentical Lur'e systems. Due to the special topology structure of the complex networks and the existence of stochastic perturbations, a kind of randomly occurring pinning controller is designed which not only synchronizes all Lur'e systems in the same cluster but also decreases the negative influence among different clusters. Firstly, based on an extended integral inequality, the convex combination theorem and S-procedure, the conditions for cluster synchronization of identical Lur'e networks are derived in a convex domain. Secondly, randomly occurring adaptive pinning controllers with two independent Bernoulli stochastic variables are designed and then sufficient conditions are obtained for the cluster synchronization on complex networks consisted of nonidentical Lur'e systems. In addition, suitable control gains for successful cluster synchronization of nonidentical Lur'e networks are acquired by designing some adaptive updating laws. Finally, we present two numerical examples to demonstrate the validity of the control scheme and the theoretical analysis.

Power and money in cluster randomized trials: when is it worth measuring a covariate?

PubMed

Moerbeek, Mirjam

2006-08-15

The power to detect a treatment effect in cluster randomized trials can be increased by increasing the number of clusters. An alternative is to include covariates into the regression model that relates treatment condition to outcome. In this paper, formulae are derived in order to evaluate both strategies on basis of their costs. It is shown that the strategy that uses covariates is more cost-efficient in detecting a treatment effect when the costs to measure these covariates are small and the correlation between the covariates and outcome is sufficiently large. The minimum required correlation depends on the cluster size, and the costs to recruit a cluster and to measure the covariate, relative to the costs to recruit a person. Measuring a covariate that varies at the person level only is recommended when cluster sizes are small and the costs to recruit and measure a cluster are large. Measuring a cluster level covariate is recommended when cluster sizes are large and the costs to recruit and measure a cluster are small. An illustrative example shows the use of the formulae in a practical setting. Copyright 2006 John Wiley & Sons, Ltd.

Intrinsic alignments in redMaPPer clusters - I. Central galaxy alignments and angular segregation of satellites

NASA Astrophysics Data System (ADS)

Huang, Hung-Jin; Mandelbaum, Rachel; Freeman, Peter E.; Chen, Yen-Chi; Rozo, Eduardo; Rykoff, Eli; Baxter, Eric J.

2016-11-01

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.

Intrinsic alignments in redMaPPer clusters – I. Central galaxy alignments and angular segregation of satellites

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

Huang, Hung -Jin; Mandelbaum, Rachel; Freeman, Peter E.

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes andmore » the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Lastly, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.« less

Intrinsic alignments in redMaPPer clusters – I. Central galaxy alignments and angular segregation of satellites

DOE PAGES

Huang, Hung -Jin; Mandelbaum, Rachel; Freeman, Peter E.; ...

2016-08-11

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes andmore » the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Lastly, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.« less

Temporal clustering of tropical cyclones and its ecosystem impacts

PubMed Central

Mumby, Peter J.; Vitolo, Renato; Stephenson, David B.

2011-01-01

Tropical cyclones have massive economic, social, and ecological impacts, and models of their occurrence influence many planning activities from setting insurance premiums to conservation planning. Most impact models allow for geographically varying cyclone rates but assume that individual storm events occur randomly with constant rate in time. This study analyzes the statistical properties of Atlantic tropical cyclones and shows that local cyclone counts vary in time, with periods of elevated activity followed by relative quiescence. Such temporal clustering is particularly strong in the Caribbean Sea, along the coasts of Belize, Honduras, Costa Rica, Jamaica, the southwest of Haiti, and in the main hurricane development region in the North Atlantic between Africa and the Caribbean. Failing to recognize this natural nonstationarity in cyclone rates can give inaccurate impact predictions. We demonstrate this by exploring cyclone impacts on coral reefs. For a given cyclone rate, we find that clustered events have a less detrimental impact than independent random events. Predictions using a standard random hurricane model were overly pessimistic, predicting reef degradation more than a decade earlier than that expected under clustered disturbance. The presence of clustering allows coral reefs more time to recover to healthier states, but the impacts of clustering will vary from one ecosystem to another. PMID:22006300

Measuring Health Information Dissemination and Identifying Target Interest Communities on Twitter: Methods Development and Case Study of the @SafetyMD Network.

PubMed

Kandadai, Venk; Yang, Haodong; Jiang, Ling; Yang, Christopher C; Fleisher, Linda; Winston, Flaura Koplin

2016-05-05

Little is known about the ability of individual stakeholder groups to achieve health information dissemination goals through Twitter. This study aimed to develop and apply methods for the systematic evaluation and optimization of health information dissemination by stakeholders through Twitter. Tweet content from 1790 followers of @SafetyMD (July-November 2012) was examined. User emphasis, a new indicator of Twitter information dissemination, was defined and applied to retweets across two levels of retweeters originating from @SafetyMD. User interest clusters were identified based on principal component analysis (PCA) and hierarchical cluster analysis (HCA) of a random sample of 170 followers. User emphasis of keywords remained across levels but decreased by 9.5 percentage points. PCA and HCA identified 12 statistically unique clusters of followers within the @SafetyMD Twitter network. This study is one of the first to develop methods for use by stakeholders to evaluate and optimize their use of Twitter to disseminate health information. Our new methods provide preliminary evidence that individual stakeholders can evaluate the effectiveness of health information dissemination and create content-specific clusters for more specific targeted messaging.

Alcohol-Specific Parenting within a Cluster-Randomized Effectiveness Trial of a Swedish Primary Prevention Program

ERIC Educational Resources Information Center

Strandberg, Anna K.; Bodin, Maria C.

2011-01-01

Purpose: Within the framework of an ongoing cluster-randomized effectiveness trial of a parental prevention program, the aim of the present study is to investigate attitudes towards under-age drinking and use of program components, i.e. alcohol-specific parenting behaviors, in parents who did and did not take part in the programme.…

The YouthMood Project: A Cluster Randomized Controlled Trial of an Online Cognitive Behavioral Program with Adolescents

ERIC Educational Resources Information Center

Calear, Alison L.; Christensen, Helen; Mackinnon, Andrew; Griffiths, Kathleen M.; O'Kearney, Richard

2009-01-01

The aim in the current study was to investigate the effectiveness of an online, self-directed cognitive-behavioral therapy program (MoodGYM) in preventing and reducing the symptoms of anxiety and depression in an adolescent school-based population. A cluster randomized controlled trial was conducted with 30 schools (N = 1,477) from across…

Assessment Data-Informed Guidance to Individualize Kindergarten Reading Instruction: Findings from a Cluster-Randomized Control Field Trial

ERIC Educational Resources Information Center

Al Otaiba, Stephanie; Connor, Carol M.; Folsom, Jessica S.; Greulich, Luana; Meadows, Jane; Li, Zhi

2011-01-01

The purpose of this cluster-randomized control field trial was to examine whether kindergarten teachers could learn to differentiate classroom reading instruction using Individualized Student Instruction for Kindergarten (ISI-K) and to test the efficacy of differentiation on reading outcomes. The study involved 14 schools, 23 ISI-K (n = 305…

The Effects of Therapist Competence in Assigning Homework in Cognitive Therapy with Cluster C Personality Disorders: Results from a Randomized Controlled Trial

ERIC Educational Resources Information Center

Ryum, Truls; Stiles, Tore C.; Svartberg, Martin; McCullough, Leigh

2010-01-01

Therapist competence in assigning homework was used to predict mid- and posttreatment outcome for patients with Cluster C personality disorders in cognitive therapy (CT). Twenty-five patients that underwent 40 sessions of CT were taken from a randomized controlled trial (Svartberg, Stiles, & Seltzer, 2004). Therapist competence in assigning…

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

ERIC Educational Resources Information Center

Dong, Nianbo; Spybrook, Jessaca; Kelcey, Ben

2016-01-01

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

The Impact of Curriculum-Based Professional Development on Science Instruction: Results from a Cluster-Randomized Trial

ERIC Educational Resources Information Center

Taylor, Joseph; Kowalski, Susan; Getty, Stephen; Wilson, Christopher; Carlson, Janet

2011-01-01

This research is part of a larger, IES-funded study titled: "Measuring the Efficacy and Student Achievement of Research-based Instructional Materials in High School Multidisciplinary Science" (Award # R305K060142). The larger study seeks to use a cluster-randomized trial design, with schools as the unit of assignment, to make causal…

A Clustered Randomized Controlled Trial to Determine Impacts of the Harvest of the Month Program

ERIC Educational Resources Information Center

LaChausse, Robert G.

2017-01-01

The study purpose was to examine the impact of the Harvest of the Month (HOTM) program on fruit and vegetable (FV) consumption, FV preferences, other eating behaviors, physical activity and other variables related to healthy eating. A clustered randomized controlled trial was employed in 28 elementary schools. After parental consent was obtained,…

Impact of a Social-Emotional and Character Development Program on School-Level Indicators of Academic Achievement, Absenteeism, and Disciplinary Outcomes: A Matched-Pair, Cluster-Randomized, Controlled Trial

ERIC Educational Resources Information Center

Snyder, Frank; Flay, Brian; Vuchinich, Samuel; Acock, Alan; Washburn, Isaac; Beets, Michael; Li, Kin-Kit

2010-01-01

This article reports the effects of a comprehensive elementary school-based social-emotional and character education program on school-level achievement, absenteeism, and disciplinary outcomes utilizing a matched-pair, cluster-randomized, controlled design. The "Positive Action" Hawai'i trial included 20 racially/ethnically diverse…

Cluster Randomized-Controlled Trial of Interventions to Improve Health for Adults with Intellectual Disability Who Live in Private Dwellings

ERIC Educational Resources Information Center

Lennox, Nicholas; Bain, Chris; Rey-Conde, Therese; Taylor, Miriam; Boyle, Frances M.; Purdie, David M.; Ware, Robert S.

2010-01-01

Background: People with intellectual disability who live in the community often have poor health and healthcare, partly as a consequence of poor communication, recall difficulties and incomplete patient health information. Materials and Methods: A cluster randomized-controlled trial with 2 x 2 factorial design was conducted with adults with…

Pathways to Health: A Cluster Randomized Trial of Nicotine Gum and Motivational Interviewing for Smoking Cessation in Low-Income Housing

ERIC Educational Resources Information Center

Okuyemi, Kolawole S.; James, Aimee S.; Mayo, Matthew S.; Nollen, Nicole; Catley, Delwyn; Choi, Won S.; Ahluwalia, Jasjit S.

2007-01-01

Despite high smoking rates among those living in poverty, few cessation studies are conducted in these populations. This cluster-randomized trial tested nicotine gum plus motivational interviewing (MI) for smoking cessation in 20 low-income housing developments (HDs). Intervention participants (10 HDs, n = 66) received educational materials, 8…

Genetic diversity study of Chromobacterium violaceum isolated from Kolli Hills by amplified ribosomal DNA restriction analysis (ARDRA) and random amplified polymorphic DNA (RAPD).

PubMed

Ponnusamy, K; Jose, S; Savarimuthu, I; Michael, G P; Redenbach, M

2011-09-01

Chromobacterium are saprophytes that cause highly fatal opportunistic infections. Identification and strain differentiation were performed to identify the strain variability among the environmental samples. We have evaluated the suitability of individual and combined methods to detect the strain variations of the samples collected in different seasons. Amplified ribosomal DNA restriction analysis (ARDRA) and random amplified polymorphic DNA (RAPD) profiles were obtained using four different restriction enzyme digestions (AluI, HaeIII, MspI and RsaI) and five random primers. A matrix of dice similarity coefficients was calculated and used to compare these restriction patterns. ARDRA showed rapid differentiation of strains based on 16S rDNA, but the combined RAPD and ARDRA gave a more reliable differentiation than when either of them was analysed individually. A high level of genetic diversity was observed, which indicates that the Kolli Hills' C. violaceum isolates would fall into at least three new clusters. Results showed a noteworthy bacterial variation and genetic diversity of C. violaceum in the unexplored, virgin forest area. © 2011 The Authors. Letters in Applied Microbiology © 2011 The Society for Applied Microbiology.

Transportability of an Evidence-Based Early Childhood Intervention in a Low-Income African Country: Results of a Cluster Randomized Controlled Study.

PubMed

Huang, Keng-Yen; Nakigudde, Janet; Rhule, Dana; Gumikiriza-Onoria, Joy Louise; Abura, Gloria; Kolawole, Bukky; Ndyanabangi, Sheila; Kim, Sharon; Seidman, Edward; Ogedegbe, Gbenga; Brotman, Laurie Miller

2017-11-01

Children in Sub-Saharan Africa (SSA) are burdened by significant unmet mental health needs. Despite the successes of numerous school-based interventions for promoting child mental health, most evidence-based interventions (EBIs) are not available in SSA. This study investigated the implementation quality and effectiveness of one component of an EBI from a developed country (USA) in a SSA country (Uganda). The EBI component, Professional Development, was provided by trained Ugandan mental health professionals to Ugandan primary school teachers. It included large-group experiential training and small-group coaching to introduce and support a range of evidence-based practices (EBPs) to create nurturing and predictable classroom experiences. The study was guided by the Consolidated Framework for Implementation Research, the Teacher Training Implementation Model, and the RE-AIM evaluation framework. Effectiveness outcomes were studied using a cluster randomized design, in which 10 schools were randomized to intervention and wait-list control conditions. A total of 79 early childhood teachers participated. Teacher knowledge and the use of EBPs were assessed at baseline and immediately post-intervention (4-5 months later). A sample of 154 parents was randomly selected to report on child behavior at baseline and post-intervention. Linear mixed effect modeling was applied to examine effectiveness outcomes. Findings support the feasibility of training Ugandan mental health professionals to provide Professional Development for Ugandan teachers. Professional Development was delivered with high levels of fidelity and resulted in improved teacher EBP knowledge and the use of EBPs in the classroom, and child social competence.

Effect of Reassuring Information About Musculoskeletal and Mental Health Complaints at the Workplace: A Cluster Randomized Trial of the atWork Intervention.

PubMed

Johnsen, Tone Langjordet; Eriksen, Hege Randi; Baste, Valborg; Indahl, Aage; Odeen, Magnus; Tveito, Torill Helene

2018-05-21

Purpose The purpose of this study was to investigate the possible difference between the Modified atWork intervention (MAW) and the Original atWork intervention (OAW) on sick leave and other health related outcomes. atWork is a group intervention using the workplace as an arena for distribution of evidence-based knowledge about musculoskeletal and mental health complaints. Methods A cluster randomized controlled trial with 93 kindergartens, comprising a total of 1011 employees, was conducted. Kindergartens were stratified by county and size and randomly allocated to MAW (45 clusters, 324 respondents) or OAW (48 clusters, 313 respondents). The randomization and intervention allocation processes were concealed. There was no blinding to group allocation. Primary outcome was register data on sick leave at cluster level. Secondary outcomes were health complaints, job satisfaction, social support, coping, and beliefs about musculoskeletal and mental health complaints, measured at the individual level. Results The MAW group reduced sick leave by 5.7% during the intervention year, while the OAW group had a 7.5% increase. Overall, the changes were not statistically significant, and no difference was detected between groups, based on 45 and 47 kindergartens. Compared to the OAW group, the MAW group had a smaller reduction for two of the statements concerning faulty beliefs about back pain, but believed less in the hereditary nature of depression. Conclusions The MAW did not have a different effect on sick leave at cluster level compared to the OAW. Trial registration https://Clinicaltrials.gov/ : NCT02396797. Registered March 23th, 2015.

Cluster ensemble based on Random Forests for genetic data.

PubMed

Alhusain, Luluah; Hafez, Alaaeldin M

2017-01-01

Clustering plays a crucial role in several application domains, such as bioinformatics. In bioinformatics, clustering has been extensively used as an approach for detecting interesting patterns in genetic data. One application is population structure analysis, which aims to group individuals into subpopulations based on shared genetic variations, such as single nucleotide polymorphisms. Advances in DNA sequencing technology have facilitated the obtainment of genetic datasets with exceptional sizes. Genetic data usually contain hundreds of thousands of genetic markers genotyped for thousands of individuals, making an efficient means for handling such data desirable. Random Forests (RFs) has emerged as an efficient algorithm capable of handling high-dimensional data. RFs provides a proximity measure that can capture different levels of co-occurring relationships between variables. RFs has been widely considered a supervised learning method, although it can be converted into an unsupervised learning method. Therefore, RF-derived proximity measure combined with a clustering technique may be well suited for determining the underlying structure of unlabeled data. This paper proposes, RFcluE, a cluster ensemble approach for determining the underlying structure of genetic data based on RFs. The approach comprises a cluster ensemble framework to combine multiple runs of RF clustering. Experiments were conducted on high-dimensional, real genetic dataset to evaluate the proposed approach. The experiments included an examination of the impact of parameter changes, comparing RFcluE performance against other clustering methods, and an assessment of the relationship between the diversity and quality of the ensemble and its effect on RFcluE performance. This paper proposes, RFcluE, a cluster ensemble approach based on RF clustering to address the problem of population structure analysis and demonstrate the effectiveness of the approach. The paper also illustrates that applying a cluster ensemble approach, combining multiple RF clusterings, produces more robust and higher-quality results as a consequence of feeding the ensemble with diverse views of high-dimensional genetic data obtained through bagging and random subspace, the two key features of the RF algorithm.

Significant locations in auxiliary data as seeds for typical use cases of point clustering

NASA Astrophysics Data System (ADS)

Kröger, Johannes

2018-05-01

Random greedy clustering and grid-based clustering are highly susceptible by their initial parameters. When used for point data clustering in maps they often change the apparent distribution of the underlying data. We propose a process that uses precomputed weighted seed points for the initialization of clusters, for example from local maxima in population density data. Exemplary results from the clustering of a dataset of petrol stations are presented.

Composition, morphology, and growth of clusters in a gas of particles with random interactions

NASA Astrophysics Data System (ADS)

Azizi, Itay; Rabin, Yitzhak

2018-03-01

We use Langevin dynamics simulations to study the growth kinetics and the steady-state properties of condensed clusters in a dilute two-dimensional system of particles that are all different (APD) in the sense that each particle is characterized by a randomly chosen interaction parameter. The growth exponents, the transition temperatures, and the steady-state properties of the clusters and of the surrounding gas phase are obtained and compared with those of one-component systems. We investigate the fractionation phenomenon, i.e., how particles of different identities are distributed between the coexisting mother (gas) and daughter (clusters) phases. We study the local organization of particles inside clusters, according to their identity—neighbourhood identity ordering (NIO)—and compare the results with those of previous studies of NIO in dense APD systems.

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

PubMed

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.

Effects of core self-evaluations on the job burnout of nurses: the mediator of organizational commitment.

PubMed

Zhou, Yangen; Lu, Jiamei; Liu, Xianmin; Zhang, Pengcheng; Chen, Wuying

2014-01-01

To explore the impact of Core self-evaluations on job burnout of nurses, and especially to test and verify the mediator role of organizational commitment between the two variables. Random cluster sampling was used to pick up participants sample, which consisted of 445 nurses of a hospital in Shanghai. Core self-evaluations questionnaire, job burnout scale and organizational commitment scale were administrated to the study participants. There are significant relationships between Core self-evaluations and dimensions of job burnout and organizational commitment. There is a significant mediation effect of organizational commitment between Core self-evaluations and job burnout. To enhance nurses' Core self-evaluations can reduce the incidence of job burnout.

Knowledge Gains Following a Child Sexual Abuse Prevention Program Among Urban Students: A Cluster-Randomized Evaluation

PubMed Central

Dauber, Sarah; Tully, Brenda A.; Hamilton, Paige; Smith, Michael J.; Freeman, Katherine

2015-01-01

Objectives. We evaluated a school-based child sexual abuse (CSA) prevention program, Safe Touches, in a low–socioeconomic status, racially diverse sample. Methods. Participants were 492 second- and third-grade students at 6 public elementary schools in New York City. The study period spanned fall 2012 through summer 2014. We cluster-randomized classrooms to the Safe Touches intervention or control groups and assessed outcomes with the Children’s Knowledge of Abuse Questionnaire. Hierarchical models tested change in children’s knowledge of inappropriate and appropriate touch. Results. The intervention group showed significantly greater improvement than the control group on knowledge of inappropriate touch. Children in second grade and children in schools with a greater proportion of students in general (vs special) education showed greater gains than other participants in knowledge of inappropriate touch. We observed no significant change in knowledge of appropriate touch among control or intervention groups. Conclusions. Young children benefited from a school-based, 1-time CSA prevention program. Future research should explore the efficacy of CSA prevention programs with children before the second grade to determine optimal age for participation. PMID:25973809

The effects of an educational program on depression literacy and stigma among students of secondary schools in Jazan city, 2016: A cluster-randomized controlled trial study protocol.

PubMed

Darraj, Hussain; Mahfouz, Mohamed Salih; Al Sanosi, Rashad; Badedi, Mohammed; Sabai, Abdullah

2018-05-01

Depression is a serious mental health disorder and characterized by sadness, loss of interest in activities, and decreased energy. The aim of this study is to assess the effectiveness of the school intervention program on depression literacy and stigma among students of secondary schools. A cluster randomized trial will be conducted on sample of 360 students to assess the depression literacy and stigma towards depression before and after a designed intervention educational program. The intervention consists of a package of 2 lectures, 1 video contact, and group discussion of 5 myths about depression, posters, and brochure. The target population consists of all secondary school students in Jazan, where there are 13 secondary schools will be stratified according to sex (6 schools for boys and 7 schools for girls). The results of the study will provide evidence of the efficacy of educational intervention programs on increasing depression literacy among students of secondary schools in Jazan City. The expected outcome of this study is to increase the depression literacy rate among high school students in the intervention group.

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

Development of Botanical Composition in Maribaya Pasture, Brebes, Central Java

NASA Astrophysics Data System (ADS)

Umami, N.; Ngadiyono, N.; Panjono; Agus, F. N.; Shirothul, H. M.; Budisatria, I. G. S.; Hendrawati, Y.; Subroto, I.

2018-02-01

The research was aimed to observe the development of botanical composition in Maribaya pastures. The sampling method was cluster random sampling. The observed variables were the type of forages and the botanical composition in the pasture. Botanical composition was measured by using Line Intercept method and the production was measured by the estimation of botany production for each square meter using its dry matter measurement. The botani sampling was performed using square with size of 1×1 m2. The observation was performed before the pasture made (at 2015) and after the pasture made (at 2017). Based on the research result, it was found that there was significant difference between the forage type in the pasture at 2015 and at 2017. It happens due to the adjustment for the Jabres cattle feed.

Spatial distribution and cluster analysis of risky sexual behaviours and STDs reported by Chinese adults in Guangzhou, China: a representative population-based study

PubMed Central

Chen, Wen; Zhou, Fangjing; Hall, Brian J; Wang, Yu; Latkin, Carl; Ling, Li; Tucker, Joseph D

2016-01-01

Objectives To assess associations between residences location, risky sexual behaviours and sexually transmitted diseases (STDs) among adults living in Guangzhou, China. Methods Data were obtained from 751 Chinese adults aged 18–59 years in Guangzhou, China, using stratified random sampling by using spatial epidemiological methods. Face-to-face household interviews were conducted to collect self-report data on risky sexual behaviours and diagnosed STDs. Kulldorff’s spatial scan statistic was implemented to identify and detect spatial distribution and clusters of risky sexual behaviours and STDs. The presence and location of statistically significant clusters were mapped in the study areas using ArcGIS software. Results The prevalence of self-reported risky sexual behaviours was between 5.1% and 50.0%. The self-reported lifetime prevalence of diagnosed STDs was 7.06%. Anal intercourse clustered in an area located along the border within the rural–urban continuum (p=0.001). High rate clusters for alcohol or other drugs using before sex (p=0.008) and migrants who lived in Guangzhou <1 year (p=0.007) overlapped this cluster. Excess cases for unprotected sex (p=0.031) overlapped the cluster for college students (p<0.001). Five of nine (55.6%) students who had sexual experience during the last 12 months located in the cluster of unprotected sex. Conclusions Short-term migrants and college students reported greater risky sexual behaviours. Programmes to increase safer sex within these communities to reduce the risk of STDs are warranted in Guangzhou. Spatial analysis identified geographical clusters of risky sexual behaviours, which is critical for optimising surveillance and targeting control measures for these locations in the future. PMID:26843400

Socio-economic Status, Needs, and Utilization of Dental Services among Rural Adults in a Primary Health Center Area in Southern India

PubMed Central

Bommireddy, Vikram Simha; Pachava, Srinivas; Ravoori, Srinivas; Sanikommu, Suresh; Talluri, Devaki; Vinnakota, Narayana Rao

2014-01-01

Background: The oral disease burden in India is showing a steady increase in the recent years. Utilization of dental care being the major factor affecting the oral health status of the population is used as an important tool in oral health policy decision-making and is measured in terms of the number of dental visits per annum. Materials and Methods: A cross-sectional house to house questionnaire survey was conducted in three rural clusters which were randomly selected from a total of eight clusters served by a primary health center. Simple random sampling was used to select 100 houses from each cluster. Screening was done to examine the existing oral diseases. A total of 385 completed questionnaires were collected from 300 houses. Results: Of 385 study subjects, 183 have experienced previous dental problems. Major dental problem experienced by the study subjects was toothache (68.85%) and the treatment underwent was extraction (50.27%). Most preferred treatment centers by the study subjects were private dental hospital (68.25%) and reason identified was accessibility which constituted (45.24%) of all the reasons given. Negative attitude toward dental care is one of the important barriers; 50.8% of the non-utilizers felt dental treatment is not much important. Conclusion: Person’s attitude, lack of awareness, and affordability remain the barriers for utilization of dental services. Effective methods have to be exercised to breach such barriers. PMID:25628485

Improved dengue fever prevention through innovative intervention methods in the city of Salto, Uruguay.

PubMed

Basso, César; García da Rosa, Elsa; Romero, Sonnia; González, Cristina; Lairihoy, Rosario; Roche, Ingrid; Caffera, Ruben M; da Rosa, Ricardo; Calfani, Marisel; Alfonso-Sierra, Eduardo; Petzold, Max; Kroeger, Axel; Sommerfeld, Johannes

2015-02-01

Uruguay is located at the southern border of Aedes aegypti distribution on the South American sub-continent. The reported dengue cases in the country are all imported from surrounding countries. One of the cities at higher risk of local dengue transmission is Salto, a border city with heavy traffic from dengue endemic areas. We completed an intervention study using a cluster randomized trial design in 20 randomly selected 'clusters' in Salto. The clusters were located in neighborhoods of differing geography and economic, cultural and social aspects. Entomological surveys were carried out to measure the impact of the intervention on vector densities. Through participatory processes of all stakeholders, an appropriate ecosystem management intervention was defined. Residents collected the abundant small water holding containers and the Ministry of Public Health and the Municipality of Salto were responsible for collecting and eliminating them. Additional vector breeding places were large water tanks; they were either altered so that they could not hold water any more or covered so that oviposition by mosquitoes could not take place. The response from the community and national programme managers was encouraging. The intervention evidenced opportunities for cost savings and reducing dengue vector densities (although not to statistically significant levels). The observed low vector density limits the potential reduction due to the intervention. A larger sample size is needed to obtain a statistically significant difference. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

Dewetting and spreading transitions for active matter on random pinning substrates.

PubMed

Sándor, Cs; Libál, A; Reichhardt, C; Olson Reichhardt, C J

2017-05-28

We show that sterically interacting self-propelled disks in the presence of random pinning substrates exhibit transitions among a variety of different states. In particular, from a phase separated cluster state, the disks can spread out and homogeneously cover the substrate in what can be viewed as an example of an active matter wetting transition. We map the location of this transition as a function of activity, disk density, and substrate strength, and we also identify other phases including a cluster state, coexistence between a cluster and a labyrinth wetted phase, and a pinned liquid. Convenient measures of these phases include the cluster size, which dips at the wetting-dewetting transition, and the fraction of sixfold coordinated particles, which drops when dewetting occurs.

The asymptotic behavior in a reversible random coagulation-fragmentation polymerization process with sub-exponential decay

NASA Astrophysics Data System (ADS)

Dong, Siqun; Zhao, Dianli

2018-01-01

This paper studies the subcritical, near-critical and supercritical asymptotic behavior of a reversible random coagulation-fragmentation polymerization process as N → ∞, with the number of distinct ways to form a k-clusters from k units satisfying f(k) =(1 + o (1)) cr-ke-kαk-β, where 0 < α < 1 and β > 0. When the cluster size is small, its distribution is proved to converge to the Gaussian distribution. For the medium clusters, its distribution will converge to Poisson distribution in supercritical stage, and no large clusters exist in this stage. Furthermore, the largest length of polymers of size N is of order ln N in the subcritical stage under α ⩽ 1 / 2.

Implementation of a quantum random number generator based on the optimal clustering of photocounts

NASA Astrophysics Data System (ADS)

Balygin, K. A.; Zaitsev, V. I.; Klimov, A. N.; Kulik, S. P.; Molotkov, S. N.

2017-10-01

To implement quantum random number generators, it is fundamentally important to have a mathematically provable and experimentally testable process of measurements of a system from which an initial random sequence is generated. This makes sure that randomness indeed has a quantum nature. A quantum random number generator has been implemented with the use of the detection of quasi-single-photon radiation by a silicon photomultiplier (SiPM) matrix, which makes it possible to reliably reach the Poisson statistics of photocounts. The choice and use of the optimal clustering of photocounts for the initial sequence of photodetection events and a method of extraction of a random sequence of 0's and 1's, which is polynomial in the length of the sequence, have made it possible to reach a yield rate of 64 Mbit/s of the output certainly random sequence.

Occurrence of Radio Minihalos in a Mass-Limited Sample of Galaxy Clusters

NASA Technical Reports Server (NTRS)

Giacintucci, Simona; Markevitch, Maxim; Cassano, Rossella; Venturi, Tiziana; Clarke, Tracy E.; Brunetti, Gianfranco

2017-01-01

We investigate the occurrence of radio minihalos-diffuse radio sources of unknown origin observed in the cores of some galaxy clusters-in a statistical sample of 58 clusters drawn from the Planck Sunyaev-Zeldovich cluster catalog using a mass cut (M(sub 500) greater than 6 x 10(exp 14) solar mass). We supplement our statistical sample with a similarly sized nonstatistical sample mostly consisting of clusters in the ACCEPT X-ray catalog with suitable X-ray and radio data, which includes lower-mass clusters. Where necessary (for nine clusters), we reanalyzed the Very Large Array archival radio data to determine whether a minihalo is present. Our total sample includes all 28 currently known and recently discovered radio minihalos, including six candidates. We classify clusters as cool-core or non-cool-core according to the value of the specific entropy floor in the cluster center, rederived or newly derived from the Chandra X-ray density and temperature profiles where necessary (for 27 clusters). Contrary to the common wisdom that minihalos are rare, we find that almost all cool cores-at least 12 out of 15 (80%)-in our complete sample of massive clusters exhibit minihalos. The supplementary sample shows that the occurrence of minihalos may be lower in lower-mass cool-core clusters. No minihalos are found in non-cool cores or "warm cores." These findings will help test theories of the origin of minihalos and provide information on the physical processes and energetics of the cluster cores.

The female urinary microbiome in urgency urinary incontinence.

PubMed

Pearce, Meghan M; Zilliox, Michael J; Rosenfeld, Amy B; Thomas-White, Krystal J; Richter, Holly E; Nager, Charles W; Visco, Anthony G; Nygaard, Ingrid E; Barber, Matthew D; Schaffer, Joseph; Moalli, Pamela; Sung, Vivian W; Smith, Ariana L; Rogers, Rebecca; Nolen, Tracy L; Wallace, Dennis; Meikle, Susan F; Gai, Xiaowu; Wolfe, Alan J; Brubaker, Linda

2015-09-01

The purpose of this study was to characterize the urinary microbiota in women who are planning treatment for urgency urinary incontinence and to describe clinical associations with urinary symptoms, urinary tract infection, and treatment outcomes. Catheterized urine samples were collected from multisite randomized trial participants who had no clinical evidence of urinary tract infection; 16S ribosomal RNA gene sequencing was used to dichotomize participants as either DNA sequence-positive or sequence-negative. Associations with demographics, urinary symptoms, urinary tract infection risk, and treatment outcomes were determined. In sequence-positive samples, microbiotas were characterized on the basis of their dominant microorganisms. More than one-half (51.1%; 93/182) of the participants' urine samples were sequence-positive. Sequence-positive participants were younger (55.8 vs 61.3 years old; P = .0007), had a higher body mass index (33.7 vs 30.1 kg/m(2); P = .0009), had a higher mean baseline daily urgency urinary incontinence episodes (5.7 vs 4.2 episodes; P < .0001), responded better to treatment (decrease in urgency urinary incontinence episodes, -4.4 vs -3.3; P = .0013), and were less likely to experience urinary tract infection (9% vs 27%; P = .0011). In sequence-positive samples, 8 major bacterial clusters were identified; 7 clusters were dominated not only by a single genus, most commonly Lactobacillus (45%) or Gardnerella (17%), but also by other taxa (25%). The remaining cluster had no dominant genus (13%). DNA sequencing confirmed urinary bacterial DNA in many women with urgency urinary incontinence who had no signs of infection. Sequence status was associated with baseline urgency urinary incontinence episodes, treatment response, and posttreatment urinary tract infection risk. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluating the Implementation of a School-Based Emotional Well-Being Programme: A Cluster Randomized Controlled Trial of Zippy's Friends for Children in Disadvantaged Primary Schools

ERIC Educational Resources Information Center

Clarke, Aleisha M.; Bunting, Brendan; Barry, Margaret M.

2014-01-01

Schools are recognized as one of the most important settings for promoting social and emotional well-being among children and adolescents. This clustered randomized controlled trial evaluated Zippy's Friends, an international school-based emotional well-being programme, with 766 children from designated disadvantaged schools. The purpose of this…

Citywide cluster randomized trial to restore blighted vacant land and its effects on violence, crime, and fear

Treesearch

Charles C. Branas; Eugenia South; Michelle C. Kondo; Bernadette C. Hohl; Philippe Bourgois; Douglas J. Wiebe; John M. MacDonald

2018-01-01

Vacant and blighted urban land is a widespread and potentially risky environmental condition encountered by millions of people on a daily basis. About 15% of the land in US cities is deemed vacant or abandoned, an area roughly the size of Switzerland. In a citywide cluster randomized controlled trial, we investigated the effects of standardized, reproducible...

The Long-Term Effectiveness of a Selective, Personality-Targeted Prevention Program in Reducing Alcohol Use and Related Harms: A Cluster Randomized Controlled Trial

ERIC Educational Resources Information Center

Newton, Nicola C.; Conrod, Patricia J.; Slade, Tim; Carragher, Natacha; Champion, Katrina E.; Barrett, Emma L.; Kelly, Erin V.; Nair, Natasha K.; Stapinski, Lexine; Teesson, Maree

2016-01-01

Background: This study investigated the long-term effectiveness of Preventure, a selective personality-targeted prevention program, in reducing the uptake of alcohol, harmful use of alcohol, and alcohol-related harms over a 3-year period. Methods: A cluster randomized controlled trial was conducted to assess the effectiveness of Preventure.…

Reducing Tobacco Use among Low Socio-Economic Status Youth in Delhi, India: Outcomes from Project ACTIVITY, a Cluster Randomized Trial

ERIC Educational Resources Information Center

Harrell, Melissa B.; Arora, Monika; Bassi, Shalini; Gupta, Vinay K.; Perry, Cheryl L.; Reddy, K. Srinath

2016-01-01

To test the efficacy of an intervention to reduce tobacco use among youth (10-19 years old) in slum communities in Delhi, India. This community-based cluster-randomized trial included 14 slums composed of purposely built resettlement colonies and adjacent inhabitant-built Jhuggi Jhopris. Youth in the intervention received a 2 year…

Cluster-Randomized Controlled Trial Evaluating the Effectiveness of Computer-Assisted Intervention Delivered by Educators for Children with Speech Sound Disorders

ERIC Educational Resources Information Center

McLeod, Sharynne; Baker, Elise; McCormack, Jane; Wren, Yvonne; Roulstone, Sue; Crowe, Kathryn; Masso, Sarah; White, Paul; Howland, Charlotte

2017-01-01

Purpose: The aim was to evaluate the effectiveness of computer-assisted input-based intervention for children with speech sound disorders (SSD). Method: The Sound Start Study was a cluster-randomized controlled trial. Seventy-nine early childhood centers were invited to participate, 45 were recruited, and 1,205 parents and educators of 4- and…

Improving Elementary School Quality through the Use of a Social-Emotional and Character Development Program: A Matched-Pair, Cluster-Randomized, Controlled Trial in Hawai'i

ERIC Educational Resources Information Center

Snyder, Frank J.; Vuchinich, Samuel; Acock, Alan; Washburn, Isaac J.; Flay, Brian R.

2012-01-01

Background: School safety and quality affect student learning and success. This study examined the effects of a comprehensive elementary school-wide social-emotional and character education program, Positive Action, on teacher, parent, and student perceptions of school safety and quality utilizing a matched-pair, cluster-randomized, controlled…

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Inadequacy of ethical conduct and reporting of stepped wedge cluster randomized trials: Results from a systematic review.

PubMed

Taljaard, Monica; Hemming, Karla; Shah, Lena; Giraudeau, Bruno; Grimshaw, Jeremy M; Weijer, Charles

2017-08-01

Background/aims The use of the stepped wedge cluster randomized design is rapidly increasing. This design is commonly used to evaluate health policy and service delivery interventions. Stepped wedge cluster randomized trials have unique characteristics that complicate their ethical interpretation. The 2012 Ottawa Statement provides comprehensive guidance on the ethical design and conduct of cluster randomized trials, and the 2010 CONSORT extension for cluster randomized trials provides guidelines for reporting. Our aims were to assess the adequacy of the ethical conduct and reporting of stepped wedge trials to date, focusing on research ethics review and informed consent. Methods We conducted a systematic review of stepped wedge cluster randomized trials in health research published up to 2014 in English language journals. We extracted details of study intervention and data collection procedures, as well as reporting of research ethics review and informed consent. Two reviewers independently extracted data from each trial; discrepancies were resolved through discussion. We identified the presence of any research participants at the cluster level and the individual level. We assessed ethical conduct by tabulating reporting of research ethics review and informed consent against the presence of research participants. Results Of 32 identified stepped wedge trials, only 24 (75%) reported review by a research ethics committee, and only 16 (50%) reported informed consent from any research participants-yet, all trials included research participants at some level. In the subgroup of 20 trials with research participants at cluster level, only 4 (20%) reported informed consent from such participants; in 26 trials with individual-level research participants, only 15 (58%) reported their informed consent. Interventions (regardless of whether targeting cluster- or individual-level participants) were delivered at the group level in more than two-thirds of trials; nine trials (28%) had no identifiable data collected from any research participants. Overall, only three trials (9%) indicated that a waiver of consent had been granted by a research ethics committee. When considering the combined requirement of research ethics review and informed consent (or a waiver), only one in three studies were compliant. Conclusion The ethical conduct and reporting of key ethical protections in stepped wedge trials, namely, research ethics review and informed consent, are inadequate. We recommend that stepped wedge trials be classified as research and reviewed and approved by a research ethics committee. We also recommend that researchers appropriately identify research participants (which may include health professionals), seek informed consent or appeal to an ethics committee for a waiver of consent, and include explicit details of research ethics approval and informed consent in the trial report.

The ROSAT Brightest Cluster Sample - I. The compilation of the sample and the cluster log N-log S distribution

NASA Astrophysics Data System (ADS)

Ebeling, H.; Edge, A. C.; Bohringer, H.; Allen, S. W.; Crawford, C. S.; Fabian, A. C.; Voges, W.; Huchra, J. P.

1998-12-01

We present a 90 per cent flux-complete sample of the 201 X-ray-brightest clusters of galaxies in the northern hemisphere (delta>=0 deg), at high Galactic latitudes (|b|>=20 deg), with measured redshifts z<=0.3 and fluxes higher than 4.4x10^-12 erg cm^-2 s^-1 in the 0.1-2.4 keV band. The sample, called the ROSAT Brightest Cluster Sample (BCS), is selected from ROSAT All-Sky Survey data and is the largest X-ray-selected cluster sample compiled to date. In addition to Abell clusters, which form the bulk of the sample, the BCS also contains the X-ray-brightest Zwicky clusters and other clusters selected from their X-ray properties alone. Effort has been made to ensure the highest possible completeness of the sample and the smallest possible contamination by non-cluster X-ray sources. X-ray fluxes are computed using an algorithm tailored for the detection and characterization of X-ray emission from galaxy clusters. These fluxes are accurate to better than 15 per cent (mean 1sigma error). We find the cumulative logN-logS distribution of clusters to follow a power law kappa S^alpha with alpha=1.31^+0.06_-0.03 (errors are the 10th and 90th percentiles) down to fluxes of 2x10^-12 erg cm^-2 s^-1, i.e. considerably below the BCS flux limit. Although our best-fitting slope disagrees formally with the canonical value of -1.5 for a Euclidean distribution, the BCS logN-logS distribution is consistent with a non-evolving cluster population if cosmological effects are taken into account. Our sample will allow us to examine large-scale structure in the northern hemisphere, determine the spatial cluster-cluster correlation function, investigate correlations between the X-ray and optical properties of the clusters, establish the X-ray luminosity function for galaxy clusters, and discuss the implications of the results for cluster evolution.

An effectiveness study of an integrated, community-based package for maternal, newborn, child and HIV care in South Africa: study protocol for a randomized controlled trial

PubMed Central

2011-01-01

Background Progress towards MDG4 in South Africa will depend largely on scaling up effective prevention against mother to child transmission (PMTCT) of HIV and also addressing neonatal mortality. This imperative drives increasing focus on the neonatal period and particularly on the development and testing of appropriate models of sustainable, community-based care in South Africa in order to reach the poor. A number of key implementation gaps affecting progress have been identified. Implementation gaps for HIV prevention in neonates; implementation gaps for neonatal care especially home postnatal care; and implementation gaps for maternal mental health support. We have developed and are evaluating and costing an integrated and scaleable home visit package delivered by community health workers targeting pregnant and postnatal women and their newborns to provide essential maternal/newborn care as well as interventions for Prevention of Mother to Child Transmission (PMTCT) of HIV. Methods The trial is a cluster randomized controlled trial that is being implemented in Umlazi which is a peri-urban settlement with a total population of 1 million close to Durban in KwaZulu Natal, South Africa. The trial consists of 30 randomized clusters (15 in each arm). A baseline survey established the homogeneity of clusters and neither stratification nor matching was performed. Sample size was based on increasing HIV-free survival from 74% to 84%, and calculated to be 120 pregnant women per cluster. Primary outcomes are higher levels of HIV free survival and levels of exclusive and appropriate infant feeding at 12 weeks postnatally. The intervention is home based with community health workers delivering two antenatal visits, a postnatal visit within 48 hours of birth, and a further four visits during the first two months of the infants life. We are undertaking programmatic and cost effectiveness analysis to cost the intervention. Discussion The question is not merely to develop an efficacious package but also to identify and test delivery strategies that enable scaling up, which requires effectiveness studies in a health systems context, adapting and testing Asian community-based studies in various African contexts. Trial registration ISRCTN: ISRCTN41046462 PMID:22044553

MODEL-BASED CLUSTERING FOR CLASSIFICATION OF AQUATIC SYSTEMS AND DIAGNOSIS OF ECOLOGICAL STRESS

EPA Science Inventory

Clustering approaches were developed using the classification likelihood, the mixture likelihood, and also using a randomization approach with a model index. Using a clustering approach based on the mixture and classification likelihoods, we have developed an algorithm that...

A practical Bayesian stepped wedge design for community-based cluster-randomized clinical trials: The British Columbia Telehealth Trial.

PubMed

Cunanan, Kristen M; Carlin, Bradley P; Peterson, Kevin A

2016-12-01

Many clinical trial designs are impractical for community-based clinical intervention trials. Stepped wedge trial designs provide practical advantages, but few descriptions exist of their clinical implementational features, statistical design efficiencies, and limitations. Enhance efficiency of stepped wedge trial designs by evaluating the impact of design characteristics on statistical power for the British Columbia Telehealth Trial. The British Columbia Telehealth Trial is a community-based, cluster-randomized, controlled clinical trial in rural and urban British Columbia. To determine the effect of an Internet-based telehealth intervention on healthcare utilization, 1000 subjects with an existing diagnosis of congestive heart failure or type 2 diabetes will be enrolled from 50 clinical practices. Hospital utilization is measured using a composite of disease-specific hospital admissions and emergency visits. The intervention comprises online telehealth data collection and counseling provided to support a disease-specific action plan developed by the primary care provider. The planned intervention is sequentially introduced across all participating practices. We adopt a fully Bayesian, Markov chain Monte Carlo-driven statistical approach, wherein we use simulation to determine the effect of cluster size, sample size, and crossover interval choice on type I error and power to evaluate differences in hospital utilization. For our Bayesian stepped wedge trial design, simulations suggest moderate decreases in power when crossover intervals from control to intervention are reduced from every 3 to 2 weeks, and dramatic decreases in power as the numbers of clusters decrease. Power and type I error performance were not notably affected by the addition of nonzero cluster effects or a temporal trend in hospitalization intensity. Stepped wedge trial designs that intervene in small clusters across longer periods can provide enhanced power to evaluate comparative effectiveness, while offering practical implementation advantages in geographic stratification, temporal change, use of existing data, and resource distribution. Current population estimates were used; however, models may not reflect actual event rates during the trial. In addition, temporal or spatial heterogeneity can bias treatment effect estimates. © The Author(s) 2016.

Random Walk Quantum Clustering Algorithm Based on Space

NASA Astrophysics Data System (ADS)

Xiao, Shufen; Dong, Yumin; Ma, Hongyang

2018-01-01

In the random quantum walk, which is a quantum simulation of the classical walk, data points interacted when selecting the appropriate walk strategy by taking advantage of quantum-entanglement features; thus, the results obtained when the quantum walk is used are different from those when the classical walk is adopted. A new quantum walk clustering algorithm based on space is proposed by applying the quantum walk to clustering analysis. In this algorithm, data points are viewed as walking participants, and similar data points are clustered using the walk function in the pay-off matrix according to a certain rule. The walk process is simplified by implementing a space-combining rule. The proposed algorithm is validated by a simulation test and is proved superior to existing clustering algorithms, namely, Kmeans, PCA + Kmeans, and LDA-Km. The effects of some of the parameters in the proposed algorithm on its performance are also analyzed and discussed. Specific suggestions are provided.

Hierarchical modeling of cluster size in wildlife surveys

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-08-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics |*| the infamous |*|gastrophysics|*| in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

The Chandra Strong Lens Sample: Revealing Baryonic Physics In Strong Lensing Selected Clusters

NASA Astrophysics Data System (ADS)

Bayliss, Matthew

2017-09-01

We propose for Chandra imaging of the hot intra-cluster gas in a unique new sample of 29 galaxy clusters selected purely on their strong gravitational lensing signatures. This will be the first program targeting a purely strong lensing selected cluster sample, enabling new comparisons between the ICM properties and scaling relations of strong lensing and mass/ICM selected cluster samples. Chandra imaging, combined with high precision strong lens models, ensures powerful constraints on the distribution and state of matter in the cluster cores. This represents a novel angle from which we can address the role played by baryonic physics -- the infamous ``gastrophysics''-- in shaping the cores of massive clusters, and opens up an exciting new galaxy cluster discovery space with Chandra.

Evidence for a global seismic-moment release sequence

USGS Publications Warehouse

Bufe, C.G.; Perkins, D.M.

2005-01-01

Temporal clustering of the larger earthquakes (foreshock-mainshock-aftershock) followed by relative quiescence (stress shadow) are characteristic of seismic cycles along plate boundaries. A global seismic-moment release history, based on a little more than 100 years of instrumental earthquake data in an extended version of the catalog of Pacheco and Sykes (1992), illustrates similar behavior for Earth as a whole. Although the largest earthquakes have occurred in the circum-Pacific region, an analysis of moment release in the hemisphere antipodal to the Pacific plate shows a very similar pattern. Monte Carlo simulations confirm that the global temporal clustering of great shallow earthquakes during 1952-1964 at M ??? 9.0 is highly significant (4% random probability) as is the clustering of the events of M ??? 8.6 (0.2% random probability) during 1950-1965. We have extended the Pacheco and Sykes (1992) catalog from 1989 through 2001 using Harvard moment centroid data. Immediately after the 1950-1965 cluster, significant quiescence at and above M 8.4 begins and continues until 2001 (0.5% random probability). In alternative catalogs derived by correcting for possible random errors in magnitude estimates in the extended Pacheco-Sykes catalog, the clustering of M ??? 9 persists at a significant level. These observations indicate that, for great earthquakes, Earth behaves as a coherent seismotectonic system. A very-large-scale mechanism for global earthquake triggering and/or stress transfer is implied. There are several candidates, but so far only viscoelastic relaxation has been modeled on a global scale.

Merger types forming the Virgo cluster in recent gigayears

NASA Astrophysics Data System (ADS)

Olchanski, M.; Sorce, J. G.

2018-06-01

Context. As our closest cluster-neighbor, the Virgo cluster of galaxies is intensely studied by observers to unravel the mysteries of galaxy evolution within clusters. At this stage, cosmological numerical simulations of the cluster are useful to efficiently test theories and calibrate models. However, it is not trivial to select the perfect simulacrum of the Virgo cluster to fairly compare in detail its observed and simulated galaxy populations that are affected by the type and history of the cluster. Aims: Determining precisely the properties of Virgo for a later selection of simulated clusters becomes essential. It is still not clear how to access some of these properties, such as the past history of the Virgo cluster from current observations. Therefore, directly producing effective simulacra of the Virgo cluster is inevitable. Methods: Efficient simulacra of the Virgo cluster can be obtained via simulations that resemble the local Universe down to the cluster scale. In such simulations, Virgo-like halos form in the proper local environment and permit assessing the most probable formation history of the cluster. Studies based on these simulations have already revealed that the Virgo cluster has had a quiet merging history over the last seven gigayears and that the cluster accretes matter along a preferential direction. Results: This paper reveals that in addition such Virgo halos have had on average only one merger larger than about a tenth of their mass at redshift zero within the last four gigayears. This second branch (by opposition to main branch) formed in a given sub-region and merged recently (within the last gigayear). These properties are not shared with a set of random halos within the same mass range. Conclusions: This study extends the validity of the scheme used to produce the Virgo simulacra down to the largest sub-halos of the Virgo cluster. It opens up great prospects for detailed comparisons with observations, including substructures and markers of past history, to be conducted with a large sample of high resolution "Virgos" and including baryons, in the near future.

A fast learning method for large scale and multi-class samples of SVM

NASA Astrophysics Data System (ADS)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

Psychological effects of chemical weapons: a follow-up study of First World War veterans.

PubMed

Jones, E; Everitt, B; Ironside, S; Palmer, I; Wessely, S

2008-10-01

Chemical weapons exercise an enduring and often powerful psychological effect. This had been recognized during the First World War when it was shown that the symptoms of stress mimicked those of mild exposure to gas. Debate about long-term effects followed the suggestion that gassing triggered latent tuberculosis. A random sample of 103 First World War servicemen awarded a war pension for the effects of gas, but without evidence of chronic respiratory pathology, were subjected to cluster analysis using 25 common symptoms. The consistency of symptom reporting was also investigated across repeated follow-ups. Cluster analysis identified four groups: one (n=56) with a range of somatic symptoms, a second (n=30) with a focus on the respiratory system, a third (n=12) with a predominance of neuropsychiatric symptoms, and a fourth (n=5) with a narrow band of symptoms related to the throat and breathing difficulties. Veterans from the neuropsychiatric cluster had multiple diagnoses including neurasthenia and disordered action of the heart, and reported many more symptoms than those in the three somatic clusters. Mild or intermittent respiratory disorders in the post-war period supported beliefs about the damaging effects of gas in the three somatic clusters. By contrast, the neuropsychiatric group did not report new respiratory illnesses. For this cluster, the experience of gassing in a context of extreme danger may have been responsible for the intensity of their symptoms, which showed no sign of diminution over the 12-year follow-up.

An insight into the distribution, genetic diversity, and mycotoxin production of Aspergillus section Flavi in soils of pistachio orchards.

PubMed

Jamali, Mojdeh; Ebrahimi, Mohammad-Ali; Karimipour, Morteza; Shams-Ghahfarokhi, Masoomeh; Dinparast-Djadid, Navid; Kalantari, Sanaz; Pilehvar-Soltanahmadi, Yones; Amani, Akram; Razzaghi-Abyaneh, Mehdi

2012-01-01

In the present study, 193 Aspergillus strains were isolated from a total of 100 soil samples of pistachio orchards, which all of them were identified as Aspergillus flavus as the most abundant species of Aspergillus section Flavi existing in the environment. Approximately 59%, 81%, and 61% of the isolates were capable of producing aflatoxins (AFs), cyclopiazonic acid (CPA), and sclerotia, respectively. The isolates were classified into four chemotypes (I to IV) based on the ability to produce AFs and CPA. The resulting dendrogram of random amplified polymorphic DNA (RAPD) analysis of 24 selected A. flavus isolates demonstrated the formation of two separate clusters. Cluster 1 contained both aflatoxigenic and non-aflatoxigenic isolates (17 isolates), whereas cluster 2 comprised only aflatoxigenic isolates (7 isolates). All the isolates of cluster 2 produced significantly higher levels of AFs than those of cluster 1 and the isolates that produced both AFB(1) and AFB(2) were found only in cluster 2. RAPD genotyping allowed the differentiation of A. flavus from Aspergillus parasiticus as a closely related species within section Flavi. The present study has provided for the first time the relevant information on distribution and genetic diversity of different A. flavus populations from nontoxigenic to highly toxigenic enable to produce hazardous amounts of AFB(1) and CPA in soils of pistachio orchards. These fungi, either toxigenic or not-toxigenic, should be considered as potential threats for agriculture and public health.

Effect and Process Evaluation of a Cluster Randomized Control Trial on Water Intake and Beverage Consumption in Preschoolers from Six European Countries: The ToyBox-Study

PubMed Central

Pinket, An-Sofie; Van Lippevelde, Wendy; De Bourdeaudhuij, Ilse; Deforche, Benedicte; Cardon, Greet; Androutsos, Odysseas; Koletzko, Berthold; Moreno, Luis A.; Socha, Piotr; Iotova, Violeta; Manios, Yannis; De Craemer, Marieke

2016-01-01

Background Within the ToyBox-study, a kindergarten-based, family-involved intervention was developed to prevent overweight and obesity in European preschoolers, targeting four key behaviours related to early childhood obesity, including water consumption. The present study aimed to examine the effect of the ToyBox-intervention (cluster randomized controlled trial) on water intake and beverage consumption in European preschoolers and to investigate if the intervention effects differed by implementation score of kindergartens and parents/caregivers. Method A sample of 4964 preschoolers (4.7±0.4 years; 51.5% boys) from six European countries (Belgium, Bulgaria, Germany, Greece, Poland, Spain) was included in the data analyses. A standardized protocol was used and parents/caregivers filled in socio-demographic data and a food-frequency questionnaire. To assess intervention effects, multilevel repeated measures analyses were conducted for the total sample and for the six country-specific samples. Based on the process evaluation questionnaire of teachers and parents/caregivers, an implementation score was constructed. To assess differences in water intake and beverage consumption by implementation score in the total sample, multilevel repeated measures analyses were performed. Results Limited intervention effects on water intake from beverages and overall beverage consumption were found. However, important results were found on prepacked fruit juice consumption, with a larger decrease in the intervention group compared to the control group. However, also a decline in plain milk consumption was found. Implementation scores were rather low in both kindergartens and parents/caregivers. Nevertheless, more favorable effects on beverage choices were found in preschoolers whose parents/caregivers and kindergarten teachers had higher implementation scores compared to those with lower implementation scores. Conclusion The ToyBox-intervention can provide the basis for the development of more tailor-made interventions. However, new strategies to improve implementation of interventions should be created. PMID:27064274

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

PubMed

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

2017-06-01

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

Review of Recent Methodological Developments in Group-Randomized Trials: Part 2-Analysis.

PubMed

Turner, Elizabeth L; Prague, Melanie; Gallis, John A; Li, Fan; Murray, David M

2017-07-01

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have updated that review with developments in analysis of the past 13 years, with a companion article to focus on developments in design. We discuss developments in the topics of the earlier review (e.g., methods for parallel-arm GRTs, individually randomized group-treatment trials, and missing data) and in new topics, including methods to account for multiple-level clustering and alternative estimation methods (e.g., augmented generalized estimating equations, targeted maximum likelihood, and quadratic inference functions). In addition, we describe developments in analysis of alternative group designs (including stepped-wedge GRTs, network-randomized trials, and pseudocluster randomized trials), which require clustering to be accounted for in their design and analysis.

Cluster-Glass Phase in Pyrochlore X Y Antiferromagnets with Quenched Disorder

NASA Astrophysics Data System (ADS)

Andrade, Eric C.; Hoyos, José A.; Rachel, Stephan; Vojta, Matthias

2018-03-01

We study the impact of quenched disorder (random exchange couplings or site dilution) on easy-plane pyrochlore antiferromagnets. In the clean system, order by disorder selects a magnetically ordered state from a classically degenerate manifold. In the presence of randomness, however, different orders can be chosen locally depending on details of the disorder configuration. Using a combination of analytical considerations and classical Monte Carlo simulations, we argue that any long-range-ordered magnetic state is destroyed beyond a critical level of randomness where the system breaks into magnetic domains due to random exchange anisotropies, becoming, therefore, a glass of spin clusters, in accordance with the available experimental data. These random anisotropies originate from off-diagonal exchange couplings in the microscopic Hamiltonian, establishing their relevance to other magnets with strong spin-orbit coupling.

Cluster: A New Application for Spatial Analysis of Pixelated Data for Epiphytotics.

PubMed

Nelson, Scot C; Corcoja, Iulian; Pethybridge, Sarah J

2017-12-01

Spatial analysis of epiphytotics is essential to develop and test hypotheses about pathogen ecology, disease dynamics, and to optimize plant disease management strategies. Data collection for spatial analysis requires substantial investment in time to depict patterns in various frames and hierarchies. We developed a new approach for spatial analysis of pixelated data in digital imagery and incorporated the method in a stand-alone desktop application called Cluster. The user isolates target entities (clusters) by designating up to 24 pixel colors as nontargets and moves a threshold slider to visualize the targets. The app calculates the percent area occupied by targeted pixels, identifies the centroids of targeted clusters, and computes the relative compass angle of orientation for each cluster. Users can deselect anomalous clusters manually and/or automatically by specifying a size threshold value to exclude smaller targets from the analysis. Up to 1,000 stochastic simulations randomly place the centroids of each cluster in ranked order of size (largest to smallest) within each matrix while preserving their calculated angles of orientation for the long axes. A two-tailed probability t test compares the mean inter-cluster distances for the observed versus the values derived from randomly simulated maps. This is the basis for statistical testing of the null hypothesis that the clusters are randomly distributed within the frame of interest. These frames can assume any shape, from natural (e.g., leaf) to arbitrary (e.g., a rectangular or polygonal field). Cluster summarizes normalized attributes of clusters, including pixel number, axis length, axis width, compass orientation, and the length/width ratio, available to the user as a downloadable spreadsheet. Each simulated map may be saved as an image and inspected. Provided examples demonstrate the utility of Cluster to analyze patterns at various spatial scales in plant pathology and ecology and highlight the limitations, trade-offs, and considerations for the sensitivities of variables and the biological interpretations of results. The Cluster app is available as a free download for Apple computers at iTunes, with a link to a user guide website.

The Mass Function of Abell Clusters

NASA Astrophysics Data System (ADS)

Chen, J.; Huchra, J. P.; McNamara, B. R.; Mader, J.

1998-12-01

The velocity dispersion and mass functions for rich clusters of galaxies provide important constraints on models of the formation of Large-Scale Structure (e.g., Frenk et al. 1990). However, prior estimates of the velocity dispersion or mass function for galaxy clusters have been based on either very small samples of clusters (Bahcall and Cen 1993; Zabludoff et al. 1994) or large but incomplete samples (e.g., the Girardi et al. (1998) determination from a sample of clusters with more than 30 measured galaxy redshifts). In contrast, we approach the problem by constructing a volume-limited sample of Abell clusters. We collected individual galaxy redshifts for our sample from two major galaxy velocity databases, the NASA Extragalactic Database, NED, maintained at IPAC, and ZCAT, maintained at SAO. We assembled a database with velocity information for possible cluster members and then selected cluster members based on both spatial and velocity data. Cluster velocity dispersions and masses were calculated following the procedures of Danese, De Zotti, and di Tullio (1980) and Heisler, Tremaine, and Bahcall (1985), respectively. The final velocity dispersion and mass functions were analyzed in order to constrain cosmological parameters by comparison to the results of N-body simulations. Our data for the cluster sample as a whole and for the individual clusters (spatial maps and velocity histograms) in our sample is available on-line at http://cfa-www.harvard.edu/ huchra/clusters. This website will be updated as more data becomes available in the master redshift compilations, and will be expanded to include more clusters and large groups of galaxies.

The co-occurrence of childhood sexual abuse, adult sexual assault, intimate partner violence, and sexual harassment: a mediational model of posttraumatic stress disorder and physical health outcomes.

PubMed

Campbell, Rebecca; Greeson, Megan R; Bybee, Deborah; Raja, Sheela

2008-04-01

This study examined the co-occurrence of childhood sexual abuse, adult sexual assault, intimate partner violence, and sexual harassment in a predominantly African American sample of 268 female veterans, randomly sampled from an urban Veterans Affairs hospital women's clinic. A combination of hierarchical and iterative cluster analysis was used to identify 4 patterns of women's lifetime experiences of violence co-occurrence. The 1st cluster experienced relatively low levels of all 4 forms of violence; the 2nd group, high levels of all 4 forms; the 3rd, sexual revictimization across the lifespan with adult sexual harassment; and the 4th, high intimate partner violence with sexual harassment. This cluster solution was validated in a theoretically driven model that examined the role of posttraumatic stress disorder (PTSD) as a mediator of physical health symptomatology. Structural equation modeling analyses revealed that PTSD fully mediated the relationship between violence and physical health symptomatology. Consistent with a bio-psycho-immunologic theoretical model, PTSD levels more strongly predicted pain-related physical health symptoms compared to nonpain health problems. Implications for clinical interventions to prevent PTSD and to screen women for histories of violence in health care settings are discussed. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Prevalence of forced sex and associated factors among women and men in Kisumu, Kenya.

PubMed

Adudans, Maureen K; Montandon, Michele; Kwena, Zachary; Bukusi, Elizabeth A; Cohen, Craig R

2011-12-01

Sexual violence is a well-recognized global health problem, albeit with limited population-based data available from sub-Saharan Africa. We sought to measure the prevalence of forced sex in Kisumu, Kenya, and identify its associated factors. The data were drawn from a population-based cross-sectional survey. A two-stage sampling design was used: 40 clusters within Kisumu municipality were enumerated and households within each cluster selected by systematic random sampling. Demographic and sexual histories, including questions on forced sex, were collected privately using a structured questionnaire. The prevalence of forced sex was 13% (women) and 4.5% (men). After adjusting for age and cluster, forced sex among women was associated with transactional sex (OR 2.33; 95%CI 1.38-3.95), having more than two lifetime partners (OR 1.9; 95%CI 1.20-3.30), having postprimary education (OR 1.49; 95%CI 1.04-2.14) and a high economic status (OR 1.87; 95%CI 1.2-2.9). No factors were significantly associated with forced sex among the male respondents. Intimate partners were the most common perpetrators of forced sex among both women (50%) and men (62.1%). Forced sex prevention programs need to target the identified associated factors, and educate the public on the high rate of forced sex perpetrated by intimate partners.

Metabolic and structural response of hyporheic microbial communities to variations in supply of dissolved organic matter

USGS Publications Warehouse

Findlay, S.E.G.; Sinsabaugh, R. L.; Sobczak, W.V.; Hoostal, M.

2003-01-01

Hyporheic sediment bacterial communities were exposed to dissolved organic matter (DOM) from a variety of sources to assess the interdependence of bacterial metabolism and community composition. Experiments ranged from small-scale core perfusions with defined compounds (glucose, bovine serum albumin) to mesocosms receiving natural leaf leachate or water from different streams. Response variables included bacterial production, oxygen consumption, extracellular enzyme activity, and community similarity as manifest by changes in banding patterns of randomly amplified polymorphic DNA (RAPD). All DOM manipulations generated responses in at least one metabolic variable. Additions of both labile and recalcitrant materials increased either oxygen consumption, production, or both depending on background DOM. Enzyme activities were affected by both types of carbon addition with largest effects from the labile mixture. Cluster analysis of RAPD data showed strong divergence of communities exposed to labile versus recalcitrant DOM. Additions of leaf leachate to mesocosms representing hyporheic flow-paths caused increases in oxygen consumption and some enzyme activities with weaker effects on production. Community structure yeas strongly affected; samples from the leachate-amended mesocosms clustered separately from the control samples. In mesocosms receiving water from streams ranging in DOC (0.5-4.5 mg L-1), there were significant differences in bacterial growth, oxygen consumption, and enzyme activities. RAPD analysis showed strongest clustering of samples by stream type with more subtle effects of position along the flowpaths. Responses in community metabolism were always accompanied by shifts in community composition, suggesting carbon supply affects both functional and structural attributes of hyporheic bacterial communities.

Clustered mixed nonhomogeneous Poisson process spline models for the analysis of recurrent event panel data.

PubMed

Nielsen, J D; Dean, C B

2008-09-01

A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.

A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

PubMed Central

Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

2016-01-01

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks. PMID:27754380

A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks.

PubMed

Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

2016-10-13

The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks.

Healthy Learning Mind - a school-based mindfulness and relaxation program: a study protocol for a cluster randomized controlled trial.

PubMed

Volanen, Salla-Maarit; Lassander, Maarit; Hankonen, Nelli; Santalahti, Päivi; Hintsanen, Mirka; Simonsen, Nina; Raevuori, Anu; Mullola, Sari; Vahlberg, Tero; But, Anna; Suominen, Sakari

2016-07-11

Mindfulness has shown positive effects on mental health, mental capacity and well-being among adult population. Among children and adolescents, previous research on the effectiveness of mindfulness interventions on health and well-being has shown promising results, but studies with methodologically sound designs have been called for. Few intervention studies in this population have compared the effectiveness of mindfulness programs to alternative intervention programs with adequate sample sizes. Our primary aim is to explore the effectiveness of a school-based mindfulness intervention program compared to a standard relaxation program among a non-clinical children and adolescent sample, and a non-treatment control group in school context. In this study, we systematically examine the effects of mindfulness intervention on mental well-being (primary outcomes being resilience; existence/absence of depressive symptoms; experienced psychological strengths and difficulties), cognitive functions, psychophysiological responses, academic achievements, and motivational determinants of practicing mindfulness. The design is a cluster randomized controlled trial with three arms (mindfulness intervention group, active control group, non-treatment group) and the sample includes 59 Finnish schools and approx. 3 000 students aged 12-15 years. Intervention consists of nine mindfulness based lessons, 45 mins per week, for 9 weeks, the dose being identical in active control group receiving standard relaxation program called Relax. The programs are delivered by 14 educated facilitators. Students, their teachers and parents will fill-in the research questionnaires before and after the intervention, and they will all be followed up 6 months after baseline. Additionally, students will be followed 12 months after baseline. For longer follow-up, consent to linking the data to the main health registers has been asked from students and their parents. The present study examines systematically the effectiveness of a school-based mindfulness program compared to a standard relaxation program, and a non-treatment control group. A strength of the current study lies in its methodologically rigorous, randomized controlled study design, which allows novel evidence on the effectiveness of mindfulness over and above a standard relaxation program. ISRCTN18642659 . Retrospectively registered 13 October 2015.

Evaluation of primary immunization coverage of infants under universal immunization programme in an urban area of bangalore city using cluster sampling and lot quality assurance sampling techniques.

PubMed

K, Punith; K, Lalitha; G, Suman; Bs, Pradeep; Kumar K, Jayanth

2008-07-01

Is LQAS technique better than cluster sampling technique in terms of resources to evaluate the immunization coverage in an urban area? To assess and compare the lot quality assurance sampling against cluster sampling in the evaluation of primary immunization coverage. Population-based cross-sectional study. Areas under Mathikere Urban Health Center. Children aged 12 months to 23 months. 220 in cluster sampling, 76 in lot quality assurance sampling. Percentages and Proportions, Chi square Test. (1) Using cluster sampling, the percentage of completely immunized, partially immunized and unimmunized children were 84.09%, 14.09% and 1.82%, respectively. With lot quality assurance sampling, it was 92.11%, 6.58% and 1.31%, respectively. (2) Immunization coverage levels as evaluated by cluster sampling technique were not statistically different from the coverage value as obtained by lot quality assurance sampling techniques. Considering the time and resources required, it was found that lot quality assurance sampling is a better technique in evaluating the primary immunization coverage in urban area.