A new model of sperm nuclear architecture following assessment of the organization of centromeres and telomeres in three-dimensions

PubMed Central

Ioannou, Dimitrios; Millan, Nicole M.; Jordan, Elizabeth; Tempest, Helen G.

2017-01-01

The organization of chromosomes in sperm nuclei has been proposed to possess a unique “hairpin-loop” arrangement, which is hypothesized to aid in the ordered exodus of the paternal genome following fertilization. This study simultaneously assessed the 3D and 2D radial and longitudinal organization of telomeres, centromeres, and investigated whether chromosomes formed the same centromere clusters in sperm cells. Reproducible radial and longitudinal non-random organization was observed for all investigated loci using both 3D and 2D approaches in multiple subjects. We report novel findings, with telomeres and centromeres being localized throughout the nucleus but demonstrating roughly a 1:1 distribution in the nuclear periphery and the intermediate regions with <15% occupying the nuclear interior. Telomeres and centromeres were observed to aggregate in sperm nuclei, forming an average of 20 and 7 clusters, respectively. Reproducible longitudinal organization demonstrated preferential localization of telomeres and centromeres in the mid region of the sperm cell. Preliminary evidence is also provided to support the hypothesis that specific chromosomes preferentially form the same centromere clusters. The more segmental distribution of telomeres and centromeres as described in this study could more readily accommodate and facilitate the sequential exodus of paternal chromosomes following fertilization. PMID:28139771

Vascular risk factors and neuropsychiatric symptoms in Alzheimer's disease: the Cache County Study.

PubMed

Steinberg, Martin; Hess, Kyle; Corcoran, Chris; Mielke, Michelle M; Norton, Maria; Breitner, John; Green, Robert; Leoutsakos, Jeannie; Welsh-Bohmer, Kathleen; Lyketsos, Constantine; Tschanz, Joann

2014-02-01

Knowledge of potentially modifiable risk factors for neuropsychiatric symptoms (NPS) in Alzheimer's disease (AD) is important. This study longitudinally explores modifiable vascular risk factors for NPS in AD. Participants enrolled in the Cache County Study on Memory in Aging with no dementia at baseline were subsequently assessed over three additional waves, and those with incident (new onset) dementia were invited to join the Dementia Progression Study for longitudinal follow-up. A total of 327 participants with incident AD were identified and assessed for the following vascular factors: atrial fibrillation, hypertension, diabetes mellitus, angina, coronary artery bypass surgery, myocardial infarction, cerebrovascular accident, and use of antihypertensive or diabetes medicines. A vascular index (VI) was also calculated. NPS were assessed over time using the Neuropsychiatric Inventory (NPI). Affective and Psychotic symptom clusters were assessed separately. The association between vascular factors and change in NPI total score was analyzed using linear mixed model and in symptom clusters using a random effects model. No individual vascular risk factors or the VI significantly predicted change in any individual NPS. The use of antihypertensive medications more than four times per week was associated with higher total NPI and Affective cluster scores. Use of antihypertensive medication was associated with higher total NPI and Affective cluster scores. The results of this study do not otherwise support vascular risk factors as modifiers of longitudinal change in NPS in AD. Copyright © 2013 John Wiley & Sons, Ltd.

Applying New Methods to the Measurement of Fidelity of Implementation: Examining the Critical Ingredients of the Responsive Classroom Approach in Relation to Mathematics Achievement

ERIC Educational Resources Information Center

Abry, Tashia D. S.; Rimm-Kaufman, Sara E.; Larsen, Ross A.; Brewer, Alix J.

2011-01-01

The present study examines data collected during the second year of a three-year longitudinal cluster randomized controlled trial, the Responsive Classroom Efficacy Study (RCES). In the context of and RCT, the research questions address naturally occurring variability in the independent variables of interest (i.e., teachers' (fidelity of…

"Learn Young, Learn Fair", a Stress Management Program for Fifth and Sixth Graders: Longitudinal Results from an Experimental Study

ERIC Educational Resources Information Center

Kraag, Gerda; Van Breukelen, Gerard J. P.; Kok, Gerjo; Hosman, Clemens

2009-01-01

Background: This study examined the effects of a universal stress management program (Learn Young, Learn Fair) on stress, coping, anxiety and depression in fifth and sixth grade children. Methods: Fifty-two schools (1467 children) participated in a clustered randomized controlled trial. Data was collected in the fall of 2002, the spring of 2003,…

Causal mediation analysis for longitudinal data with exogenous exposure

PubMed Central

Bind, M.-A. C.; Vanderweele, T. J.; Coull, B. A.; Schwartz, J. D.

2016-01-01

Mediation analysis is a valuable approach to examine pathways in epidemiological research. Prospective cohort studies are often conducted to study biological mechanisms and often collect longitudinal measurements on each participant. Mediation formulae for longitudinal data have been developed. Here, we formalize the natural direct and indirect effects using a causal framework with potential outcomes that allows for an interaction between the exposure and the mediator. To allow different types of longitudinal measures of the mediator and outcome, we assume two generalized mixed-effects models for both the mediator and the outcome. The model for the mediator has subject-specific random intercepts and random exposure slopes for each cluster, and the outcome model has random intercepts and random slopes for the exposure, the mediator, and their interaction. We also expand our approach to settings with multiple mediators and derive the mediated effects, jointly through all mediators. Our method requires the absence of time-varying confounding with respect to the exposure and the mediator. This assumption is achieved in settings with exogenous exposure and mediator, especially when exposure and mediator are not affected by variables measured at earlier time points. We apply the methodology to data from the Normative Aging Study and estimate the direct and indirect effects, via DNA methylation, of air pollution, and temperature on intercellular adhesion molecule 1 (ICAM-1) protein levels. Our results suggest that air pollution and temperature have a direct effect on ICAM-1 protein levels (i.e. not through a change in ICAM-1 DNA methylation) and that temperature has an indirect effect via a change in ICAM-1 DNA methylation. PMID:26272993

Non-random distribution and co-localization of purine/pyrimidine-encoded information and transcriptional regulatory domains.

PubMed

Povinelli, C M

1992-01-01

In order to detect sequence-based information predictive for the location of eukaryotic transcriptional regulatory domains, the frequencies and distributions of the 36 possible purine/pyrimidine reverse complement hexamer pairs was determined for test sets of real and random sequences. The distribution of one of the hexamer pairs (RRYYRR/YYRRYY, referred to as M1) was further examined in a larger set of sequences (> 32 genes, 230 kb). Predominant clusters of M1 and the locations of eukaryotic transcriptional regulatory domains were found to be associated and non-randomly distributed along the DNA consistent with a periodicity of approximately 1.2 kb. In the context of higher ordered chromatin this would align promoters, enhancers and the predominant clusters of M1 longitudinally along one face of a 30 nm fiber. Using only information about the distribution of the M1 motif, 50-70% of a sequence could be eliminated as being unlikely to contain transcriptional regulatory domains with an 87% recovery of the regulatory domains present.

Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth.

PubMed

Zhang, Zhaoyang; Fang, Hua; Wang, Honggang

2016-06-01

Web-delivered trials are an important component in eHealth services. These trials, mostly behavior-based, generate big heterogeneous data that are longitudinal, high dimensional with missing values. Unsupervised learning methods have been widely applied in this area, however, validating the optimal number of clusters has been challenging. Built upon our multiple imputation (MI) based fuzzy clustering, MIfuzzy, we proposed a new multiple imputation based validation (MIV) framework and corresponding MIV algorithms for clustering big longitudinal eHealth data with missing values, more generally for fuzzy-logic based clustering methods. Specifically, we detect the optimal number of clusters by auto-searching and -synthesizing a suite of MI-based validation methods and indices, including conventional (bootstrap or cross-validation based) and emerging (modularity-based) validation indices for general clustering methods as well as the specific one (Xie and Beni) for fuzzy clustering. The MIV performance was demonstrated on a big longitudinal dataset from a real web-delivered trial and using simulation. The results indicate MI-based Xie and Beni index for fuzzy-clustering are more appropriate for detecting the optimal number of clusters for such complex data. The MIV concept and algorithms could be easily adapted to different types of clustering that could process big incomplete longitudinal trial data in eHealth services.

Multiple Imputation based Clustering Validation (MIV) for Big Longitudinal Trial Data with Missing Values in eHealth

PubMed Central

Zhang, Zhaoyang; Wang, Honggang

2016-01-01

Web-delivered trials are an important component in eHealth services. These trials, mostly behavior-based, generate big heterogeneous data that are longitudinal, high dimensional with missing values. Unsupervised learning methods have been widely applied in this area, however, validating the optimal number of clusters has been challenging. Built upon our multiple imputation (MI) based fuzzy clustering, MIfuzzy, we proposed a new multiple imputation based validation (MIV) framework and corresponding MIV algorithms for clustering big longitudinal eHealth data with missing values, more generally for fuzzy-logic based clustering methods. Specifically, we detect the optimal number of clusters by auto-searching and -synthesizing a suite of MI-based validation methods and indices, including conventional (bootstrap or cross-validation based) and emerging (modularity-based) validation indices for general clustering methods as well as the specific one (Xie and Beni) for fuzzy clustering. The MIV performance was demonstrated on a big longitudinal dataset from a real web-delivered trial and using simulation. The results indicate MI-based Xie and Beni index for fuzzy-clustering is more appropriate for detecting the optimal number of clusters for such complex data. The MIV concept and algorithms could be easily adapted to different types of clustering that could process big incomplete longitudinal trial data in eHealth services. PMID:27126063

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.

Causal mediation analysis for longitudinal data with exogenous exposure.

PubMed

Bind, M-A C; Vanderweele, T J; Coull, B A; Schwartz, J D

2016-01-01

Mediation analysis is a valuable approach to examine pathways in epidemiological research. Prospective cohort studies are often conducted to study biological mechanisms and often collect longitudinal measurements on each participant. Mediation formulae for longitudinal data have been developed. Here, we formalize the natural direct and indirect effects using a causal framework with potential outcomes that allows for an interaction between the exposure and the mediator. To allow different types of longitudinal measures of the mediator and outcome, we assume two generalized mixed-effects models for both the mediator and the outcome. The model for the mediator has subject-specific random intercepts and random exposure slopes for each cluster, and the outcome model has random intercepts and random slopes for the exposure, the mediator, and their interaction. We also expand our approach to settings with multiple mediators and derive the mediated effects, jointly through all mediators. Our method requires the absence of time-varying confounding with respect to the exposure and the mediator. This assumption is achieved in settings with exogenous exposure and mediator, especially when exposure and mediator are not affected by variables measured at earlier time points. We apply the methodology to data from the Normative Aging Study and estimate the direct and indirect effects, via DNA methylation, of air pollution, and temperature on intercellular adhesion molecule 1 (ICAM-1) protein levels. Our results suggest that air pollution and temperature have a direct effect on ICAM-1 protein levels (i.e. not through a change in ICAM-1 DNA methylation) and that temperature has an indirect effect via a change in ICAM-1 DNA methylation. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.

PubMed

Hedeker, D; Gibbons, R D

1996-05-01

MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.

Reducing diarrhoea in Guatemalan children: randomized controlled trial of flocculant-disinfectant for drinking-water.

PubMed

Chiller, Tom M; Mendoza, Carlos E; Lopez, M Beatriz; Alvarez, Maricruz; Hoekstra, Robert M; Keswick, Bruce H; Luby, Stephen P

2006-01-01

To examine the effect of a new point-of-use treatment for drinking-water, a commercially developed flocculant-disinfectant, on the prevalence of diarrhoea in children. We conducted a randomized controlled trial among 514 rural Guatemalan households, divided into 42 neighbourhood clusters, for 13 weeks, from 4 November 2002 through 31 January 2003. Clusters assigned to water treatment with the flocculant-disinfectant were compared with those using their usual water-handling practices. The longitudinal prevalence of diarrhoea was calculated as the proportion of total days with diarrhoea divided by the total number of days of observation. The prevalence of diarrhoea was compared using the Wilcoxon rank-sum test. The 1702 people in households receiving the disinfectant had a prevalence of diarrhoea that was 40% lower than that among the 1699 people using standard water-handling practices (0.9% versus 1.5%; P = 0.001). In households using the flocculant-disinfectant, children < 1 year of age had a 39% lower prevalence of diarrhoea than those in households using their standard practices (3.7% versus 6.0%; P = 0.005). In settings where families rarely treat drinking-water, we introduced a novel flocculant-disinfectant that reduced the longitudinal prevalence of diarrhoea, especially among children aged < 1 year, among whom diarrhoea has been strongly associated with mortality. Successful introduction and use of this product could contribute to preventing diarrhoeal disease globally.

Evolution and Determinants of Health-Related Quality-of-Life in Kidney Transplant Patients Over the First 3 Years After Transplantation.

PubMed

Villeneuve, Claire; Laroche, Marie-Laure; Essig, Marie; Merville, Pierre; Kamar, Nassim; Coubret, Anne; Lacroix, Isabelle; Bouchet, Stéphane; Fruit, Dorothée; Marquet, Pierre; Rousseau, Annick

2016-03-01

Health-related quality of life (HRQOL) usually improved after kidney transplantation; however, a non-negligible number of patients did not benefit from transplantation in HRQOL. The aims of this cohort study were to describe the evolution of HRQOL in kidney transplant recipients to search for subgroups with distinct time profiles and to investigate these determinants. Three hundred thirty-seven adult patients were followed up from 1 to 36 months after kidney transplantation. Each patient completed repeated HRQOL assessments (median, 5; range, 2-9). K-means for longitudinal data was used to identify homogeneous clusters of HRQOL time profiles obtained for the mental and physical composite scores (MCS and PCS) and for the 8 dimensions of the short-form 36 scale. Covariates associated with these clusters were investigated using random forest analysis. Magnitude and shape of the HRQOL variations over time were investigated using linear regression mixed models. Two longitudinal clusters were identified for the time profiles of PCS and MCS. Patients classified in the higher cluster (ie, 60% of the population) exhibited a steady-state HRQOL, similar on average to the general population, whereas in the lower cluster, PCS and MCS scores were significantly lower than in the general population. Muscular weakness in the first year after transplantation explained 19% of the interpatient variability of PCS 3 months after transplantation, whereas associated with anxiety, it explained 24% of interpatient MCS variability. This work suggests to promote (i) physical rehabilitation programs after transplantation to curb the muscular loss and (ii) systematic attention to the patient's anxiety.

Cluster Analysis in Sociometric Research: A Pattern-Oriented Approach to Identifying Temporally Stable Peer Status Groups of Girls

ERIC Educational Resources Information Center

Zettergren, Peter

2007-01-01

A modern clustering technique was applied to age-10 and age-13 sociometric data with the purpose of identifying longitudinally stable peer status clusters. The study included 445 girls from a Swedish longitudinal study. The identified temporally stable clusters of rejected, popular, and average girls were essentially larger than corresponding…

Community-based intermittent mass testing and treatment for malaria in an area of high transmission intensity, western Kenya: study design and methodology for a cluster randomized controlled trial.

PubMed

Samuels, Aaron M; Awino, Nobert; Odongo, Wycliffe; Abong'o, Benard; Gimnig, John; Otieno, Kephas; Shi, Ya Ping; Were, Vincent; Allen, Denise Roth; Were, Florence; Sang, Tony; Obor, David; Williamson, John; Hamel, Mary J; Patrick Kachur, S; Slutsker, Laurence; Lindblade, Kim A; Kariuki, Simon; Desai, Meghna

2017-06-07

Most human Plasmodium infections in western Kenya are asymptomatic and are believed to contribute importantly to malaria transmission. Elimination of asymptomatic infections requires active treatment approaches, such as mass testing and treatment (MTaT) or mass drug administration (MDA), as infected persons do not seek care for their infection. Evaluations of community-based approaches that are designed to reduce malaria transmission require careful attention to study design to ensure that important effects can be measured accurately. This manuscript describes the study design and methodology of a cluster-randomized controlled trial to evaluate a MTaT approach for malaria transmission reduction in an area of high malaria transmission. Ten health facilities in western Kenya were purposively selected for inclusion. The communities within 3 km of each health facility were divided into three clusters of approximately equal population size. Two clusters around each health facility were randomly assigned to the control arm, and one to the intervention arm. Three times per year for 2 years, after the long and short rains, and again before the long rains, teams of community health volunteers visited every household within the intervention arm, tested all consenting individuals with malaria rapid diagnostic tests, and treated all positive individuals with an effective anti-malarial. The effect of mass testing and treatment on malaria transmission was measured through population-based longitudinal cohorts, outpatient visits for clinical malaria, periodic population-based cross-sectional surveys, and entomological indices.

Reducing diarrhoea in Guatemalan children: randomized controlled trial of flocculant-disinfectant for drinking-water.

PubMed Central

Chiller, Tom M.; Mendoza, Carlos E.; Lopez, M. Beatriz; Alvarez, Maricruz; Hoekstra, Robert M.; Keswick, Bruce H.; Luby, Stephen P.

2006-01-01

OBJECTIVE: To examine the effect of a new point-of-use treatment for drinking-water, a commercially developed flocculant-disinfectant, on the prevalence of diarrhoea in children. METHODS: We conducted a randomized controlled trial among 514 rural Guatemalan households, divided into 42 neighbourhood clusters, for 13 weeks, from 4 November 2002 through 31 January 2003. Clusters assigned to water treatment with the flocculant-disinfectant were compared with those using their usual water-handling practices. The longitudinal prevalence of diarrhoea was calculated as the proportion of total days with diarrhoea divided by the total number of days of observation. The prevalence of diarrhoea was compared using the Wilcoxon rank-sum test. FINDINGS: The 1702 people in households receiving the disinfectant had a prevalence of diarrhoea that was 40% lower than that among the 1699 people using standard water-handling practices (0.9% versus 1.5%; P = 0.001). In households using the flocculant-disinfectant, children < 1 year of age had a 39% lower prevalence of diarrhoea than those in households using their standard practices (3.7% versus 6.0%; P = 0.005). CONCLUSION: In settings where families rarely treat drinking-water, we introduced a novel flocculant-disinfectant that reduced the longitudinal prevalence of diarrhoea, especially among children aged < 1 year, among whom diarrhoea has been strongly associated with mortality. Successful introduction and use of this product could contribute to preventing diarrhoeal disease globally. PMID:16501712

Clustering of diet, physical activity and sedentary behaviour among Australian children: cross-sectional and longitudinal associations with overweight and obesity.

PubMed

Leech, R M; McNaughton, S A; Timperio, A

2015-07-01

Evidence suggests diet, physical activity (PA) and sedentary behaviour cluster together in children, but research supporting an association with overweight/obesity is equivocal. Furthermore, the stability of clusters over time is unknown. The aim of this study was to examine the clustering of diet, PA and sedentary behaviour in Australian children and cross-sectional and longitudinal associations with overweight/obesity. Stability of obesity-related clusters over 3 years was also examined. Data were drawn from the baseline (T1: 2002/2003) and follow-up waves (T2: 2005/2006) of the Health Eating and Play Study. Parents of Australian children aged 5-6 (n=87) and 10-12 years (n=123) completed questionnaires. Children wore accelerometers and height and weight were measured. Obesity-related clusters were determined using K-medians cluster analysis. Multivariate regression models assessed cross-sectional and longitudinal associations between cluster membership, and body mass index (BMI) Z-score and weight status. Kappa statistics assessed cluster stability over time. Three clusters, labelled 'most healthy', 'energy-dense (ED) consumers who watch TV' and 'high sedentary behaviour/low moderate-to-vigorous PA' were identified at baseline and at follow-up. No cross-sectional associations were found between cluster membership, and BMI Z-score or weight status at baseline. Longitudinally, children in the 'ED consumers who watch TV' cluster had a higher odds of being overweight/obese at follow-up (odds ratio=2.8; 95% confidence interval: 1.1, 6.9; P<0.05). Tracking of cluster membership was fair to moderate in younger (K=0.24; P=0.0001) and older children (K=0.46; P<0.0001). This study identified an unhealthy cluster of TV viewing with ED food/drink consumption, which predicted overweight/obesity in a small longitudinal sample of Australian children. Cluster stability was fair to moderate over 3 years and is a novel finding. Prospective research in larger samples is needed to examine how obesity-related clusters track over time and influence the development of overweight and obesity.

Subgroups of advanced cancer patients clustered by their symptom profiles: quality-of-life outcomes.

PubMed

Husain, Amna; Myers, Jeff; Selby, Debbie; Thomson, Barbara; Chow, Edward

2011-11-01

Symptom cluster analysis is a new frontier of research in symptom management. This study clustered patients by their symptom profiles to identify subgroups that may be at higher risk for poor quality of life (QOL) and that may, therefore, benefit most from targeted interventions. Longitudinal study of metastatic cancer patients using the Edmonton Symptom Assessment Scale (ESAS). We generated two-, three-, and four-cluster subgroups and examined the relationship of cluster membership with patient outcomes. To address the problem of missing longitudinal data, we developed a novel outcome variable (QualTime) that measures both QOL and time in study. Two hundred and twenty-one patients with a mean Palliative Performance Scale (PPS) of 59.1 were enrolled. The three-cluster model was chosen for further analysis. The low-burden subgroup had all low severity symptom scores. The intermediate subgroup separates from the low-burden group on the "debility" profile of fatigue, drowsiness, appetite, and well-being. The high-burden group separates from the intermediate-burden group on pain, depression, and anxiety. At baseline, PPS (p=0.0003) and cluster membership (p<0.0001) contributed significantly to global QOL. In univariate analysis, cluster membership was related to the longitudinal outcome, QualTime. In a multivariate model, the relationship of PPS to QualTime was still significant (p=0.0002), but subgroup membership was no longer significant (p=0.1009). PPS is a stronger predictor of the longitudinal variable than cluster subgroups; however, cluster subgroups provide a target for clinical interventions that may improve QOL.

Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

PubMed

Chan, Jennifer S K

2016-05-01

Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Long-term analysis of health status and preventive behavior in music students across an entire university program.

PubMed

Spahn, Claudia; Nusseck, Manfred; Zander, Mark

2014-03-01

The aim of this investigation was to analyze longitudinal data concerning physical and psychological health, playing-related problems, and preventive behavior among music students across their complete 4- to 5-year study period. In a longitudinal, observational study, we followed students during their university training and measured their psychological and physical health status and preventive behavior using standardized questionnaires at four different times. The data were in accordance with previous findings. They demonstrated three groups of health characteristics observed in beginners of music study: healthy students (cluster 1), students with preclinical symptoms (cluster 2), and students who are clinically symptomatic (cluster 3). In total, 64% of all students remained in the same cluster group during their whole university training. About 10% of the students showed considerable health problems and belonged to the third cluster group. The three clusters of health characteristics found in this longitudinal study with music students necessitate that prevention programs for musicians must be adapted to the target audience.

Hurdle models for multilevel zero-inflated data via h-likelihood.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2010-12-30

Count data often exhibit overdispersion. One type of overdispersion arises when there is an excess of zeros in comparison with the standard Poisson distribution. Zero-inflated Poisson and hurdle models have been proposed to perform a valid likelihood-based analysis to account for the surplus of zeros. Further, data often arise in clustered, longitudinal or multiple-membership settings. The proper analysis needs to reflect the design of a study. Typically random effects are used to account for dependencies in the data. We examine the h-likelihood estimation and inference framework for hurdle models with random effects for complex designs. We extend the h-likelihood procedures to fit hurdle models, thereby extending h-likelihood to truncated distributions. Two applications of the methodology are presented. Copyright © 2010 John Wiley & Sons, Ltd.

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

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

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

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.

Effectiveness of a community-based nutrition programme to improve child growth in rural Ethiopia: a cluster randomized trial.

PubMed

Kang, Yunhee; Kim, Sungtae; Sinamo, Sisay; Christian, Parul

2017-01-01

Few trials have shown that promoting complementary feeding among young children is effective in improving child linear growth in resource-challenged settings. We designed a community-based participatory nutrition promotion (CPNP) programme adapting a Positive Deviance/Hearth approach that engaged mothers in 2-week nutrition sessions using the principles of 'learning by doing' around child feeding. We aimed to test the effectiveness of the CPNP for improving child growth in rural Ethiopia. A cluster randomized trial was implemented by adding the CPNP to the existing government nutrition programmes (six clusters) vs. government programmes only (six clusters). A total of 1790 children aged 6 to 12 months (876 in the intervention and 914 in the control areas) were enrolled and assessed on anthropometry every 3 months for a year. Multi-level mixed-effect regression analysis of longitudinal outcome data (n = 1475) examined the programme impact on growth, adjusting for clustering and enrollment characteristics. Compared with children 6 to 24 months of age in the control area, those in the intervention area had a greater increase in z scores for length-for-age [difference (diff): 0.021 z score/month, 95% CI: 0.008, 0.034] and weight-for-length (diff: 0.042 z score/month, 95% CI: 0.024, 0.059). At the end of the 12-month follow-up, children in the intervention area showed an 8.1% (P = 0.02) and 6.3% (P = 0.046) lower prevalence of stunting and underweight, respectively, after controlling for differences in the prevalence at enrollment, compared with the control group. A novel CPNP programme was effective in improving child growth and reducing undernutrition in this setting. © 2016 John Wiley & Sons Ltd. © 2016 John Wiley & Sons Ltd.

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.

Revisiting typhoid fever surveillance in low and middle income countries: lessons from systematic literature review of population-based longitudinal studies.

PubMed

Mogasale, Vittal; Mogasale, Vijayalaxmi V; Ramani, Enusa; Lee, Jung Seok; Park, Ju Yeon; Lee, Kang Sung; Wierzba, Thomas F

2016-01-29

The control of typhoid fever being an important public health concern in low and middle income countries, improving typhoid surveillance will help in planning and implementing typhoid control activities such as deployment of new generation Vi conjugate typhoid vaccines. We conducted a systematic literature review of longitudinal population-based blood culture-confirmed typhoid fever studies from low and middle income countries published from 1(st) January 1990 to 31(st) December 2013. We quantitatively summarized typhoid fever incidence rates and qualitatively reviewed study methodology that could have influenced rate estimates. We used meta-analysis approach based on random effects model in summarizing the hospitalization rates. Twenty-two papers presented longitudinal population-based and blood culture-confirmed typhoid fever incidence estimates from 20 distinct sites in low and middle income countries. The reported incidence and hospitalizations rates were heterogeneous as well as the study methodology across the sites. We elucidated how the incidence rates were underestimated in published studies. We summarized six categories of under-estimation biases observed in these studies and presented potential solutions. Published longitudinal typhoid fever studies in low and middle income countries are geographically clustered and the methodology employed has a potential for underestimation. Future studies should account for these limitations.

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),…

A Longitudinal Investigation of Morpho-Syntax in Children with Speech Sound Disorders

ERIC Educational Resources Information Center

Mortimer, Jennifer; Rvachew, Susan

2010-01-01

Purpose: The intent of this study was to examine the longitudinal morpho-syntactic progression of children with Speech Sound Disorders (SSD) grouped according to Mean Length of Utterance (MLU) scores. Methods: Thirty-seven children separated into four clusters were assessed in their pre-kindergarten and Grade 1 years. Cluster 1 were children with…

Local drinking water filters reduce diarrheal disease in Cambodia: a randomized, controlled trial of the ceramic water purifier.

PubMed

Brown, Joe; Sobsey, Mark D; Loomis, Dana

2008-09-01

A randomized, controlled intervention trial of two household-scale drinking water filters was conducted in a rural village in Cambodia. After collecting four weeks of baseline data on household water quality, diarrheal disease, and other data related to water use and handling practices, households were randomly assigned to one of three groups of 60 households: those receiving a ceramic water purifier (CWP), those receiving a second filter employing an iron-rich ceramic (CWP-Fe), and a control group receiving no intervention. Households were followed for 18 weeks post-baseline with biweekly follow-up. Households using either filter reported significantly less diarrheal disease during the study compared with a control group of households without filters as indicated by longitudinal prevalence ratios CWP: 0.51 (95% confidence interval [CI]: 0.41-0.63); CWP-Fe: 0.58 (95% CI: 0.47-0.71), an effect that was observed in all age groups and both sexes after controlling for clustering within households and within individuals over time.

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.

Designing and evaluating health systems level hypertension control interventions for African-Americans: lessons from a pooled analysis of three cluster randomized trials.

PubMed

Pavlik, Valory N; Chan, Wenyaw; Hyman, David J; Feldman, Penny; Ogedegbe, Gbenga; Schwartz, Joseph E; McDonald, Margaret; Einhorn, Paula; Tobin, Jonathan N

2015-01-01

African-Americans (AAs) have a high prevalence of hypertension and their blood pressure (BP) control on treatment still lags behind other groups. In 2004, NHLBI funded five projects that aimed to evaluate clinically feasible interventions to effect changes in medical care delivery leading to an increased proportion of AA patients with controlled BP. Three of the groups performed a pooled analysis of trial results to determine: 1) the magnitude of the combined intervention effect; and 2) how the pooled results could inform the methodology for future health-system level BP interventions. Using a cluster randomized design, the trials enrolled AAs with uncontrolled hypertension to test interventions targeting a combination of patient and clinician behaviors. The 12-month Systolic BP (SBP) and Diastolic BP (DBP) effects of intervention or control cluster assignment were assessed using mixed effects longitudinal regression modeling. 2,015 patients representing 352 clusters participated across the three trials. Pooled BP slopes followed a quadratic pattern, with an initial decline, followed by a rise toward baseline, and did not differ significantly between intervention and control clusters: SBP linear coefficient = -2.60±0.21 mmHg per month, p<0.001; quadratic coefficient = 0.167± 0.02 mmHg/month, p<0.001; group by time interaction group by time group x linear time coefficient=0.145 ± 0.293, p=0.622; group x quadratic time coefficient= -0.017 ± 0.026, p=0.525). RESULTS were similar for DBP. The individual sites did not have significant intervention effects when analyzed separately. Investigators planning behavioral trials to improve BP control in health systems serving AAs should plan for small effect sizes and employ a "run-in" period in which BP can be expected to improve in both experimental and control clusters.

Effect of an environmental school-based obesity prevention program on changes in body fat and body weight: a randomized trial.

PubMed

Williamson, Donald A; Champagne, Catherine M; Harsha, David W; Han, Hongmei; Martin, Corby K; Newton, Robert L; Sothern, Melinda S; Stewart, Tiffany M; Webber, Larry S; Ryan, Donna H

2012-08-01

This study tested the efficacy of two school-based programs for prevention of body weight/fat gain in comparison to a control group, in all participants and in overweight children. The Louisiana (LA) Health study utilized a longitudinal, cluster randomized three-arm controlled design, with 28 months of follow-up. Children (N = 2,060; mean age = 10.5 years, SD = 1.2) from rural communities in grades 4-6 participated in the study. Seventeen school clusters (mean = 123 children/cluster) were randomly assigned to one of three prevention arms: (i) primary prevention (PP), an environmental modification (EM) program, (ii) primary + secondary prevention (PP+SP), the environmental program with an added classroom and internet education component, or (iii) control (C). Primary outcomes were changes in percent body fat and BMI z scores. Secondary outcomes were changes in behaviors related to energy balance. Comparisons of PP, PP+SP, and C on changes in body fat and BMI z scores found no differences. PP and PP+SP study arms were combined to create an EM arm. Relative to C, EM decreased body fat for boys (-1.7 ± 0.38% vs. -0.14 ± 0.69%) and attenuated fat gain for girls (2.9 ± 0.22% vs. 3.93 ± 0.37%), but standardized effect sizes were relatively small (<0.30). In conclusion, this school-based EM programs had modest beneficial effects on changes in percent body fat. Addition of a classroom/internet program to the environmental program did not enhance weight/fat gain prevention, but did impact physical activity and social support in overweight children.

Effect of an Environmental School-based Obesity Prevention Program On Changes in Body Fat and Body Weight: A Randomized Trial

PubMed Central

Williamson, D.A.; Champagne, C.M.; Harsha, D.; Han, H.; Martin, C.K.; Newton, R.L.; Sothern, M.; Stewart, T.M.; Webber, L.S.; Ryan, D.

2012-01-01

This study tested the efficacy of two school-based programs for prevention of body weight/fat gain in comparison to a control group, in all participants and in overweight children. The Louisiana (LA) Health study utilized a longitudinal, cluster randomized 3-arm controlled design, with 28 months of follow-up. Children (N=2060; M age = 10.5 years, SD = 1.2) from rural communities in Grades 4 to 6 participated in the study. 17 school clusters (M = 123 children/cluster) were randomly assigned to one of three prevention arms: 1) Primary Prevention (PP), an environmental modification program, 2) Primary + Secondary Prevention (PP+SP), the environmental program with an added classroom and internet education component, or 3) Control (C). Primary outcomes were changes in percent body fat and body mass index z scores. Secondary outcomes were changes in behaviors related to energy balance. Comparisons of PP, PP+SP, and C on changes in body fat and BMI z scores found no differences. PP and PP+SP study arms were combined to create an environmental modification arm (EM). Relative to C, EM decreased body fat for boys (−1.7% ± 0.38% versus −0.14% ± 0.69%) and attenuated fat gain for girls (2.9% ± 0.22% versus 3.93% ± 0.37%), but standardized effect sizes were relatively small (< 0.30). In conclusion, this school-based environmental modification programs had modest beneficial effects on changes in percent body fat. Addition of a classroom/internet program to the environmental program did not enhance weight/fat gain prevention, but did impact physical activity and social support in overweight children. PMID:22402733

Tissue Probability Map Constrained 4-D Clustering Algorithm for Increased Accuracy and Robustness in Serial MR Brain Image Segmentation

PubMed Central

Xue, Zhong; Shen, Dinggang; Li, Hai; Wong, Stephen

2010-01-01

The traditional fuzzy clustering algorithm and its extensions have been successfully applied in medical image segmentation. However, because of the variability of tissues and anatomical structures, the clustering results might be biased by the tissue population and intensity differences. For example, clustering-based algorithms tend to over-segment white matter tissues of MR brain images. To solve this problem, we introduce a tissue probability map constrained clustering algorithm and apply it to serial MR brain image segmentation, i.e., a series of 3-D MR brain images of the same subject at different time points. Using the new serial image segmentation algorithm in the framework of the CLASSIC framework, which iteratively segments the images and estimates the longitudinal deformations, we improved both accuracy and robustness for serial image computing, and at the mean time produced longitudinally consistent segmentation and stable measures. In the algorithm, the tissue probability maps consist of both the population-based and subject-specific segmentation priors. Experimental study using both simulated longitudinal MR brain data and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data confirmed that using both priors more accurate and robust segmentation results can be obtained. The proposed algorithm can be applied in longitudinal follow up studies of MR brain imaging with subtle morphological changes for neurological disorders. PMID:26566399

Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies.

PubMed

Huang, Yangxin; Lu, Xiaosun; Chen, Jiaqing; Liang, Juan; Zangmeister, Miriam

2017-10-27

Longitudinal and time-to-event data are often observed together. Finite mixture models are currently used to analyze nonlinear heterogeneous longitudinal data, which, by releasing the homogeneity restriction of nonlinear mixed-effects (NLME) models, can cluster individuals into one of the pre-specified classes with class membership probabilities. This clustering may have clinical significance, and be associated with clinically important time-to-event data. This article develops a joint modeling approach to a finite mixture of NLME models for longitudinal data and proportional hazard Cox model for time-to-event data, linked by individual latent class indicators, under a Bayesian framework. The proposed joint models and method are applied to a real AIDS clinical trial data set, followed by simulation studies to assess the performance of the proposed joint model and a naive two-step model, in which finite mixture model and Cox model are fitted separately.

Determinants of Anemia and Hemoglobin Concentration in Haitian School-Aged Children

PubMed Central

Iannotti, Lora L.; Delnatus, Jacques R.; Odom, Audrey R.; Eaton, Jacob C.; Griggs, Jennifer J.; Brown, Sarah; Wolff, Patricia B.

2015-01-01

Anemia diminishes oxygen transport in the body, resulting in potentially irreversible growth and developmental consequences for children. Limited evidence for determinants of anemia exists for school-aged children. We conducted a cluster randomized controlled trial in Haiti from 2012 to 2013 to test the efficacy of a fortified school snack. Children (N = 1,047) aged 3–13 years were followed longitudinally at three time points for hemoglobin (Hb) concentrations, anthropometry, and bioelectrical impedance measures. Dietary intakes, infectious disease morbidities, and socioeconomic and demographic factors were collected at baseline and endline. Longitudinal regression modeling with generalized least squares and logit models with random effects identified anemia risk factors beyond the intervention effect. At baseline, 70.6% of children were anemic and 2.6% were severely anemic. Stunting increased the odds of developing anemia (adjusted odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.05–2.08) and severe anemia (adjusted OR: 2.47, 95% CI: 1.30–4.71). Parent-reported vitamin A supplementation and deworming were positively associated with Hb concentrations, whereas fever and poultry ownership showed a negative relationship with Hb concentration and increased odds of severe anemia, respectively. Further research should explore the full spectrum of anemia etiologies in school children, including genetic causes. PMID:26350448

The PULSAR Specialist Care protocol: a stepped-wedge cluster randomized control trial of a training intervention for community mental health teams in recovery-oriented practice.

PubMed

Shawyer, Frances; Enticott, Joanne C; Brophy, Lisa; Bruxner, Annie; Fossey, Ellie; Inder, Brett; Julian, John; Kakuma, Ritsuko; Weller, Penelope; Wilson-Evered, Elisabeth; Edan, Vrinda; Slade, Mike; Meadows, Graham N

2017-05-08

Recovery features strongly in Australian mental health policy; however, evidence is limited for the efficacy of recovery-oriented practice at the service level. This paper describes the Principles Unite Local Services Assisting Recovery (PULSAR) Specialist Care trial protocol for a recovery-oriented practice training intervention delivered to specialist mental health services staff. The primary aim is to evaluate whether adult consumers accessing services where staff have received the intervention report superior recovery outcomes compared to adult consumers accessing services where staff have not yet received the intervention. A qualitative sub-study aims to examine staff and consumer views on implementing recovery-oriented practice. A process evaluation sub-study aims to articulate important explanatory variables affecting the interventions rollout and outcomes. The mixed methods design incorporates a two-step stepped-wedge cluster randomized controlled trial (cRCT) examining cross-sectional data from three phases, and nested qualitative and process evaluation sub-studies. Participating specialist mental health care services in Melbourne, Victoria are divided into 14 clusters with half randomly allocated to receive the staff training in year one and half in year two. Research participants are consumers aged 18-75 years who attended the cluster within a previous three-month period either at baseline, 12 (step 1) or 24 months (step 2). In the two nested sub-studies, participation extends to cluster staff. The primary outcome is the Questionnaire about the Process of Recovery collected from 756 consumers (252 each at baseline, step 1, step 2). Secondary and other outcomes measuring well-being, service satisfaction and health economic impact are collected from a subset of 252 consumers (63 at baseline; 126 at step 1; 63 at step 2) via interviews. Interview-based longitudinal data are also collected 12 months apart from 88 consumers with a psychotic disorder diagnosis (44 at baseline, step 1; 44 at step 1, step 2). cRCT data will be analyzed using multilevel mixed-effects modelling to account for clustering and some repeated measures, supplemented by thematic analysis of qualitative interview data. The process evaluation will draw on qualitative, quantitative and documentary data. Findings will provide an evidence-base for the continued transformation of Australian mental health service frameworks toward recovery. Australian and New Zealand Clinical Trial Registry: ACTRN12614000957695 . Date registered: 8 September 2014.

The dysregulated cluster in personality profiling research: Longitudinal stability and associations with bulimic behaviors and correlates

PubMed Central

Slane, Jennifer D.; Klump, Kelly L.; Donnellan, M. Brent; McGue, Matthew; Iacono, William G.

2013-01-01

Among cluster analytic studies of the personality profiles associated with bulimia nervosa, a group of individuals characterized by emotional lability and behavioral dysregulation (i.e., a dysregulated cluster) has emerged most consistently. However, previous studies have all been cross-sectional and mostly used clinical samples. This study aimed to replicate associations between the dysregulated personality cluster and bulimic symptoms and related characteristics using a longitudinal, population-based sample. Participants were females assessed at ages 17 and 25 from the Minnesota Twin Family Study, clustered based on their personality traits. The Dysregulated cluster was successfully identified at both time points and was more stable across time than either the Resilient or Sensation Seeking clusters. Rates of bulimic symptoms and related behaviors (e.g., alcohol use problems) were also highest in the dysregulated group. Findings suggest that the dysregulated cluster is a relatively stable and robust profile that is associated with bulimic symptoms. PMID:23398096

Low and Increasing Trajectories of Perpetration of Physical Dating Violence: 7-Year Associations with Suicidal Ideation, Weapons, and Substance Use.

PubMed

Orpinas, Pamela; Nahapetyan, Lusine; Truszczynski, Natalia

2017-05-01

Understanding the interrelation among problem behaviors and their change over time is fundamental for prevention research. The Healthy Teens Longitudinal Study followed a cohort of adolescents from Grades 6-12. Prior research identified two distinct trajectories of perpetration of physical dating violence: Low and Increasing. The purpose of this study was to examine whether adolescents in these two trajectories differed longitudinally on other problem behaviors: (1) suicidal ideation and attempts, (2) weapon-carrying and threats with a weapon, and (3) substance use, particularly alcohol and marijuana. The sample consisted of 588 randomly-selected students (52% males; 49% White, 36% Black, 12% Latino). Students completed a self-reported, computer-based survey each spring from Grades 6-12. To examine significant differences by perpetration of physical dating violence trajectory, we used Chi-square test and generalized estimating equations modeling. Across most grades, significantly more students in Increasing than in the Low trajectory reported suicidal ideation and attempts, carried a weapon, and threatened someone with a weapon. Adolescents in the Increasing trajectory also had higher trajectories of alcohol use, being drunk, and marijuana use than those in the Low trajectory. All differences were already significant in Grade 6. The difference in the rate of change between groups was not significant. This longitudinal study highlights that problem behaviors-physical dating violence, suicidal ideation and attempts, weapon carrying and threats, marijuana and alcohol use-cluster together as early as sixth grade and the clustering persists over time. The combination of these behaviors poses a great public health concern and highlight the need for early interventions.

Using social-emotional and character development to improve academic outcomes: a matched-pair, cluster-randomized controlled trial in low-income, urban schools

PubMed Central

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

2013-01-01

BACKGROUND School-based social-emotional and character development (SECD) programs can influence not only SECD, but also academic-related outcomes. This study evaluated the impact of one SECD program, Positive Action (PA), on educational outcomes among low-income, urban youth. METHODS The longitudinal study used a matched-pair, cluster-randomized controlled design. Student-reported disaffection with learning and academic grades, and teacher ratings of academic ability and motivation were assessed for a cohort followed from grades 3 to 8. Aggregate school records were used to assess standardized test performance (for entire school, cohort, and demographic subgroups) and absenteeism (entire school). Multilevel growth-curve analyses tested program effects. RESULTS PA significantly improved growth in academic motivation and mitigated disaffection with learning. There was a positive impact of PA on absenteeism and marginally significant impact on math performance of all students. There were favorable program effects on reading for African American boys and cohort students transitioning between grades 7 and 8, and on math for girls and low-income students. CONCLUSIONS A school-based SECD program was found to influence academic outcomes among students living in low-income, urban communities. Future research should examine mechanisms by which changes in SECD influence changes in academic outcomes. PMID:24138347

Using social-emotional and character development to improve academic outcomes: a matched-pair, cluster-randomized controlled trial in low-income, urban schools.

PubMed

Bavarian, Niloofar; Lewis, Kendra M; Dubois, David L; Acock, Alan; Vuchinich, Samuel; Silverthorn, Naida; Snyder, Frank J; Day, Joseph; Ji, Peter; Flay, Brian R

2013-11-01

School-based social-emotional and character development (SECD) programs can influence not only SECD but also academic-related outcomes. This study evaluated the impact of one SECD program, Positive Action (PA), on educational outcomes among low-income, urban youth. The longitudinal study used a matched-pair, cluster-randomized controlled design. Student-reported disaffection with learning and academic grades, and teacher ratings of academic ability and motivation were assessed for a cohort followed from grades 3 to 8. Aggregate school records were used to assess standardized test performance (for entire school, cohort, and demographic subgroups) and absenteeism (entire school). Multilevel growth-curve analyses tested program effects. PA significantly improved growth in academic motivation and mitigated disaffection with learning. There was a positive impact of PA on absenteeism and marginally significant impact on math performance of all students. There were favorable program effects on reading for African American boys and cohort students transitioning between grades 7 and 8, and on math for girls and low-income students. A school-based SECD program was found to influence academic outcomes among students living in low-income, urban communities. Future research should examine mechanisms by which changes in SECD influence changes in academic outcomes. © 2013, American School Health Association.

Large longitudinal spin alignment generated in inelastic nuclear reactions

NASA Astrophysics Data System (ADS)

Hoff, D. E. M.; Potel, G.; Brown, K. W.; Charity, R. J.; Pruitt, C. D.; Sobotka, L. G.; Webb, T. B.; Roeder, B.; Saastamoinen, A.

2018-05-01

Large longitudinal spin alignment of E /A =24 MeV 7Li projectiles inelastically excited by Be, C, and Al targets was observed when the latter remain in their ground state. This alignment is a consequence of an angular-momentum-excitation-energy mismatch, which is well described by a DWBA cluster-model (α +t ). The longitudinal alignment of several other systems is also well described by DWBA calculations, including one where a cluster model is inappropriate, demonstrating that the alignment mechanism is a more general phenomenon. Predictions are made for inelastic excitation of 12C for beam energies above and below the mismatch threshold.

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.

Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife

PubMed Central

Racine, Annie M.; Koscik, Rebecca L.; Berman, Sara E.; Nicholas, Christopher R.; Clark, Lindsay R.; Okonkwo, Ozioma C.; Rowley, Howard A.; Asthana, Sanjay; Bendlin, Barbara B.; Blennow, Kaj; Zetterberg, Henrik; Gleason, Carey E.; Carlsson, Cynthia M.

2016-01-01

The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials. PMID:27324877

Biomarker clusters are differentially associated with longitudinal cognitive decline in late midlife.

PubMed

Racine, Annie M; Koscik, Rebecca L; Berman, Sara E; Nicholas, Christopher R; Clark, Lindsay R; Okonkwo, Ozioma C; Rowley, Howard A; Asthana, Sanjay; Bendlin, Barbara B; Blennow, Kaj; Zetterberg, Henrik; Gleason, Carey E; Carlsson, Cynthia M; Johnson, Sterling C

2016-08-01

The ability to detect preclinical Alzheimer's disease is of great importance, as this stage of the Alzheimer's continuum is believed to provide a key window for intervention and prevention. As Alzheimer's disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer's disease; (ii) mixed Alzheimer's disease and vascular aetiology; (iii) suspected non-Alzheimer's disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Effect of Cognitive Therapy on Structural Social Capital: Results From a Randomized Controlled Trial Among Sexual Violence Survivors in the Democratic Republic of the Congo

PubMed Central

Bolton, Paul A.; Annan, Jeannie; Kaysen, Debra; Robinette, Katie; Cetinoglu, Talita; Wachter, Karin; Bass, Judith K.

2014-01-01

Objectives. We evaluated changes in social capital following group-based cognitive processing therapy (CPT) for female survivors of sexual violence. Methods. We compared CPT with individual support in a cluster-randomized trial in villages in South Kivu province, Democratic Republic of the Congo. Local psychosocial assistants delivered the interventions from April through July 2011. We evaluated differences between CPT and individual support conditions for structural social capital (i.e., time spent with nonkin social network, group membership and participation, and the size of financial and instrumental support networks) and emotional support seeking. We analyzed intervention effects with longitudinal random effects models. Results. We obtained small to medium effect size differences for 2 study outcomes. Women in the CPT villages increased group membership and participation at 6-month follow-up and emotional support seeking after the intervention compared with women in the individual support villages. Conclusions. Results support the efficacy of group CPT to increase dimensions of social capital among survivors of sexual violence in a low-income conflict-affected context. PMID:25033113

Hand washing with soap and WASH educational intervention reduces under-five childhood diarrhoea incidence in Jigjiga District, Eastern Ethiopia: A community-based cluster randomized controlled trial.

PubMed

Hashi, Abdiwahab; Kumie, Abera; Gasana, Janvier

2017-06-01

Despite the tremendous achievement in reducing child mortality and morbidity in the last two decades, diarrhoea is still a major cause of morbidity and mortality among children in many developing countries, including Ethiopia. Hand washing with soap promotion, water quality improvements and improvements in excreta disposal significantly reduces diarrhoeal diseases. The objective of this study was to evaluate the effect of hand washing with soap and water, sanitation and hygiene (WASH) educational Intervention on the incidence of under-five children diarrhoea. A community-based cluster randomized controlled trial was conducted in 24 clusters (sub-Kebelles) in Jigjiga district, Somali region, Eastern Ethiopia from February 1 to July 30, 2015. The trial compared incidence of diarrhoea among under-five children whose primary caretakers receive hand washing with soap and water, sanitation, hygiene educational messages with control households. Generalized estimating equation with a log link function Poisson distribution family was used to compute adjusted incidence rate ratio and the corresponding 95% confidence interval. The results of this study show that the longitudinal adjusted incidence rate ratio (IRR) of diarrhoeal diseases comparing interventional and control households was 0.65 (95% CI 0.57, 0.73) suggesting an overall diarrhoeal diseases reduction of 35%. The results are similar to other trials of WASH educational interventions and hand washing with soap. In conclusion, hand washing with soap practice during critical times and WASH educational messages reduces childhood diarrhoea in the rural pastoralist area.

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.

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.

Does Mass Azithromycin Distribution Impact Child Growth and Nutrition in Niger? A Cluster-Randomized Trial

PubMed Central

Amza, Abdou; Yu, Sun N.; Kadri, Boubacar; Nassirou, Baido; Stoller, Nicole E.; Zhou, Zhaoxia; West, Sheila K.; Bailey, Robin L.; Gaynor, Bruce D.; Keenan, Jeremy D.; Porco, Travis C.; Lietman, Thomas M.

2014-01-01

Background Antibiotic use on animals demonstrates improved growth regardless of whether or not there is clinical evidence of infectious disease. Antibiotics used for trachoma control may play an unintended benefit of improving child growth. Methodology In this sub-study of a larger randomized controlled trial, we assess anthropometry of pre-school children in a community-randomized trial of mass oral azithromycin distributions for trachoma in Niger. We measured height, weight, and mid-upper arm circumference (MUAC) in 12 communities randomized to receive annual mass azithromycin treatment of everyone versus 12 communities randomized to receive biannual mass azithromycin treatments for children, 3 years after the initial mass treatment. We collected measurements in 1,034 children aged 6–60 months of age. Principal Findings We found no difference in the prevalence of wasting among children in the 12 annually treated communities that received three mass azithromycin distributions compared to the 12 biannually treated communities that received six mass azithromycin distributions (odds ratio = 0.88, 95% confidence interval = 0.53 to 1.49). Conclusions/Significance We were unable to demonstrate a statistically significant difference in stunting, underweight, and low MUAC of pre-school children in communities randomized to annual mass azithromycin treatment or biannual mass azithromycin treatment. The role of antibiotics on child growth and nutrition remains unclear, but larger studies and longitudinal trials may help determine any association. PMID:25210836

Childhood antecedents of adolescent personality disorders.

PubMed

Bernstein, D P; Cohen, P; Skodol, A; Bezirganian, S; Brook, J S

1996-07-01

The purpose of this study was to investigate the childhood antecedents of personality disorders that are diagnosed in adolescence. A randomly selected community sample of 641 youths was assessed initially in childhood and followed longitudinally over 10 years. Childhood behavior ratings were based on maternal report; diagnoses of adolescent personality disorders were based on data obtained from both maternal and youth informants. Four composite measures of childhood behavior problems were used: conduct problems, depressive symptoms, anxiety/fear, and immaturity. Adolescent personality disorders were considered present only if the disorders persisted over a 2-year period. For all analyses, personality disorders were grouped into the three clusters (A, B, and C) of DSM-III-R. Logistic regression analyses indicated that all four of the putative childhood antecedents were associated with greater odds of an adolescent personality disorder 10 years later. Childhood conduct problems remained an independent predictor of personality disorders in all three clusters, even when other childhood problems were included in the same regression model. Additionally, depressive symptoms emerged as an independent predictor of cluster A personality disorders in boys, while immaturity was an independent predictor of cluster B personality disorders in girls. No moderating effects of age at time of childhood assessment were found. These results support the view that personality disorders can be traced to childhood emotional and behavioral disturbances and suggest that these problems have both general and specific relationships to adolescent personality functioning.

Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

PubMed

Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

2014-11-01

Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

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…

Evaluation of a health promotion program in children: Study protocol and design of the cluster-randomized Baden-Württemberg primary school study [DRKS-ID: DRKS00000494

PubMed Central

2012-01-01

Background Increasing prevalences of overweight and obesity in children are known problems in industrialized countries. Early prevention is important as overweight and obesity persist over time and are related with health problems later in adulthood. "Komm mit in das gesunde Boot - Grundschule" is a school-based program to promote a healthier lifestyle. Main goals of the intervention are to increase physical activity, decrease the consumption of sugar-sweetened beverages, and to decrease time spent sedentary by promoting active choices for healthy lifestyle. The program to date is distributed by 34 project delivery consultants in the state of Baden-Württemberg and is currently implemented in 427 primary schools. The efficacy of this large scale intervention is examined via the Baden-Württemberg Study. Methods/Design The Baden-Württemberg Study is a prospective, stratified, cluster-randomized, and longitudinal study with two groups (intervention group and control group). Measurements were taken at the beginning of the academic years 2010/2011 and 2011/2012. Efficacy of the intervention is being assessed using three main outcomes: changes in waist circumference, skinfold thickness and 6 minutes run. Stratified cluster-randomization (according to class grade level) was performed for primary schools; pupils, teachers/principals, and parents were investigated. An approximately balanced number of classes in intervention group and control group could be reached by stratified randomization and was maintained at follow-up. Discussion At present, "Komm mit in das Gesunde Boot - Grundschule" is the largest school-based health promotion program in Germany. Comparative objective main outcomes are used for the evaluation of efficacy. Simulations showed sufficient power with the existing sample size. Therefore, the results will show whether the promotion of a healthier lifestyle in primary school children is possible using a relatively low effort within a school-based program involving children, teachers and parents. The research team anticipates that not only efficacy will be proven in this study but also expects many other positive effects of the program. Trial registration German Clinical Trials Register (DRKS), DRKS-ID: DRKS00000494 PMID:22394693

Evaluation of a health promotion program in children: Study protocol and design of the cluster-randomized Baden-Württemberg primary school study [DRKS-ID: DRKS00000494].

PubMed

Dreyhaupt, Jens; Koch, Benjamin; Wirt, Tamara; Schreiber, Anja; Brandstetter, Susanne; Kesztyüs, Dorothea; Wartha, Olivia; Kobel, Susanne; Kettner, Sarah; Prokopchuk, Dmytro; Hundsdörfer, Verena; Klepsch, Melina; Wiedom, Martina; Sufeida, Sabrina; Fischbach, Nanette; Muche, Rainer; Seufert, Tina; Steinacker, Jürgen Michael

2012-03-06

Increasing prevalences of overweight and obesity in children are known problems in industrialized countries. Early prevention is important as overweight and obesity persist over time and are related with health problems later in adulthood. "Komm mit in das gesunde Boot - Grundschule" is a school-based program to promote a healthier lifestyle. Main goals of the intervention are to increase physical activity, decrease the consumption of sugar-sweetened beverages, and to decrease time spent sedentary by promoting active choices for healthy lifestyle. The program to date is distributed by 34 project delivery consultants in the state of Baden-Württemberg and is currently implemented in 427 primary schools. The efficacy of this large scale intervention is examined via the Baden-Württemberg Study. The Baden-Württemberg Study is a prospective, stratified, cluster-randomized, and longitudinal study with two groups (intervention group and control group). Measurements were taken at the beginning of the academic years 2010/2011 and 2011/2012. Efficacy of the intervention is being assessed using three main outcomes: changes in waist circumference, skinfold thickness and 6 minutes run. Stratified cluster-randomization (according to class grade level) was performed for primary schools; pupils, teachers/principals, and parents were investigated. An approximately balanced number of classes in intervention group and control group could be reached by stratified randomization and was maintained at follow-up. At present, "Komm mit in das Gesunde Boot - Grundschule" is the largest school-based health promotion program in Germany. Comparative objective main outcomes are used for the evaluation of efficacy. Simulations showed sufficient power with the existing sample size. Therefore, the results will show whether the promotion of a healthier lifestyle in primary school children is possible using a relatively low effort within a school-based program involving children, teachers and parents. The research team anticipates that not only efficacy will be proven in this study but also expects many other positive effects of the program. German Clinical Trials Register (DRKS), DRKS-ID: DRKS00000494.

Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.

PubMed

Scott, JoAnna M; deCamp, Allan; Juraska, Michal; Fay, Michael P; Gilbert, Peter B

2017-04-01

Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

Typology of alcohol users based on longitudinal patterns of drinking.

PubMed

Harrington, Magdalena; Velicer, Wayne F; Ramsey, Susan

2014-03-01

Worldwide, alcohol is the most commonly used psychoactive substance. However, heterogeneity among alcohol users has been widely recognized. This paper presents a typology of alcohol users based on an implementation of idiographic methodology to examine longitudinal daily and cyclic (weekly) patterns of alcohol use at the individual level. A secondary data analysis was performed on the pre-intervention data from a large randomized control trial. A time series analysis was performed at the individual level, and a dynamic cluster analysis was employed to identify homogenous longitudinal patterns of drinking behavior at the group level. The analysis employed 180 daily observations of alcohol use in a sample of 177 alcohol users. The first order autocorrelations ranged from -.76 to .72, and seventh order autocorrelations ranged from -.27 to .79. Eight distinct profiles of alcohol users were identified, each characterized by a unique configuration of first and seventh autoregressive terms and longitudinal trajectories of alcohol use. External validity of the profiles confirmed the theoretical relevance of different patterns of alcohol use. Significant differences among the eight subtypes were found on gender, marital status, frequency of drug use, lifetime alcohol dependence, family history of alcohol use and the Short Index of Problems. Our findings demonstrate that individuals can have very different temporal patterns of drinking behavior. The daily and cyclic patterns of alcohol use may be important for designing tailored interventions for problem drinkers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Typology of Alcohol Users Based on Longitudinal Patterns of Drinking

PubMed Central

Harrington, Magdalena; Velicer, Wayne F.; Ramsey, Susan

2014-01-01

Objective Worldwide, alcohol is the most commonly used psychoactive substance. However, heterogeneity among alcohol users has been widely recognized. This paper presents a typology of alcohol users based on an implementation of idiographic methodology to examine longitudinal daily and cyclic (weekly) patterns of alcohol use at the individual level. Method A secondary data analysis was performed on the pre-intervention data from a large randomized control trial. A time series analysis was performed at the individual level, and a dynamic cluster analysis was employed to identify homogenous longitudinal patterns of drinking behavior at the group level. The analysis employed 180 daily observations of alcohol use in a sample of 177 alcohol users. Results The first order autocorrelations ranged from −.76 to .72, and seventh order autocorrelations ranged from −.27 to .79. Eight distinct profiles of alcohol users were identified, each characterized by a unique configuration of first and seventh autoregressive terms and longitudinal trajectories of alcohol use. External validity of the profiles confirmed the theoretical relevance of different patterns of alcohol use. Significant differences among the eight subtypes were found on gender, marital status, frequency of drug use, lifetime alcohol dependence, family history of alcohol use and the Short Index of Problems. Conclusions Our findings demonstrate that individuals can have very different temporal patterns of drinking behavior. The daily and cyclic patterns of alcohol use may be important for designing tailored interventions for problem drinkers. PMID:24333036

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

PubMed

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

2017-01-01

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

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.

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

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

PubMed Central

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

2017-01-01

An increasing number of studies are being performed in educational research to evaluate new teaching methods and approaches. These studies could be performed more efficiently and deliver more convincing results if they more strictly applied and complied with recognized standards of scientific studies. Such an approach could substantially increase the quality in particular of prospective, two-arm (intervention) studies that aim to compare two different teaching methods. A key standard in such studies is randomization, which can minimize systematic bias in study findings; such bias may result if the two study arms are not structurally equivalent. If possible, educational research studies should also achieve this standard, although this is not yet generally the case. Some difficulties and concerns exist, particularly regarding organizational and methodological aspects. An important point to consider in educational research studies is that usually individuals cannot be randomized, because of the teaching situation, and instead whole groups have to be randomized (so-called “cluster randomization”). Compared with studies with individual randomization, studies with cluster randomization normally require (significantly) larger sample sizes and more complex methods for calculating sample size. Furthermore, cluster-randomized studies require more complex methods for statistical analysis. The consequence of the above is that a competent expert with respective special knowledge needs to be involved in all phases of cluster-randomized studies. Studies to evaluate new teaching methods need to make greater use of randomization in order to achieve scientifically convincing results. Therefore, in this article we describe the general principles of cluster randomization and how to implement these principles, and we also outline practical aspects of using cluster randomization in prospective, two-arm comparative educational research studies. PMID:28584874

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

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.

Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology

ERIC Educational Resources Information Center

Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…

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.

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.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Analysis of partially observed clustered data using generalized estimating equations and multiple imputation

PubMed Central

Aloisio, Kathryn M.; Swanson, Sonja A.; Micali, Nadia; Field, Alison; Horton, Nicholas J.

2015-01-01

Clustered data arise in many settings, particularly within the social and biomedical sciences. As an example, multiple–source reports are commonly collected in child and adolescent psychiatric epidemiologic studies where researchers use various informants (e.g. parent and adolescent) to provide a holistic view of a subject’s symptomatology. Fitzmaurice et al. (1995) have described estimation of multiple source models using a standard generalized estimating equation (GEE) framework. However, these studies often have missing data due to additional stages of consent and assent required. The usual GEE is unbiased when missingness is Missing Completely at Random (MCAR) in the sense of Little and Rubin (2002). This is a strong assumption that may not be tenable. Other options such as weighted generalized estimating equations (WEEs) are computationally challenging when missingness is non–monotone. Multiple imputation is an attractive method to fit incomplete data models while only requiring the less restrictive Missing at Random (MAR) assumption. Previously estimation of partially observed clustered data was computationally challenging however recent developments in Stata have facilitated their use in practice. We demonstrate how to utilize multiple imputation in conjunction with a GEE to investigate the prevalence of disordered eating symptoms in adolescents reported by parents and adolescents as well as factors associated with concordance and prevalence. The methods are motivated by the Avon Longitudinal Study of Parents and their Children (ALSPAC), a cohort study that enrolled more than 14,000 pregnant mothers in 1991–92 and has followed the health and development of their children at regular intervals. While point estimates were fairly similar to the GEE under MCAR, the MAR model had smaller standard errors, while requiring less stringent assumptions regarding missingness. PMID:25642154

Cluster Adjusted Regression for Displaced Subject Data (CARDS): Marginal Inference under Potentially Informative Temporal Cluster Size Profiles

PubMed Central

Bible, Joe; Beck, James D.; Datta, Somnath

2016-01-01

Summary Ignorance of the mechanisms responsible for the availability of information presents an unusual problem for analysts. It is often the case that the availability of information is dependent on the outcome. In the analysis of cluster data we say that a condition for informative cluster size (ICS) exists when the inference drawn from analysis of hypothetical balanced data varies from that of inference drawn on observed data. Much work has been done in order to address the analysis of clustered data with informative cluster size; examples include Inverse Probability Weighting (IPW), Cluster Weighted Generalized Estimating Equations (CWGEE), and Doubly Weighted Generalized Estimating Equations (DWGEE). When cluster size changes with time, i.e., the data set possess temporally varying cluster sizes (TVCS), these methods may produce biased inference for the underlying marginal distribution of interest. We propose a new marginalization that may be appropriate for addressing clustered longitudinal data with TVCS. The principal motivation for our present work is to analyze the periodontal data collected by Beck et al. (1997, Journal of Periodontal Research 6, 497–505). Longitudinal periodontal data often exhibits both ICS and TVCS as the number of teeth possessed by participants at the onset of study is not constant and teeth as well as individuals may be displaced throughout the study. PMID:26682911

Intimate Partner Violence and Depression Symptom Severity among South African Women during Pregnancy and Postpartum: Population-Based Prospective Cohort Study

PubMed Central

Tsai, Alexander C.; Tomlinson, Mark; Comulada, W. Scott; Rotheram-Borus, Mary Jane

2016-01-01

Background Violence against women by intimate partners remains unacceptably common worldwide. The evidence base for the assumed psychological impacts of intimate partner violence (IPV) is derived primarily from studies conducted in high-income countries. A recently published systematic review identified 13 studies linking IPV to incident depression, none of which were conducted in sub-Saharan Africa. To address this gap in the literature, we analyzed longitudinal data collected during the course of a 3-y cluster-randomized trial with the aim of estimating the association between IPV and depression symptom severity. Methods and Findings We conducted a secondary analysis of population-based, longitudinal data collected from 1,238 pregnant women during a 3-y cluster-randomized trial of a home visiting intervention in Cape Town, South Africa. Surveys were conducted at baseline, 6 mo, 18 mo, and 36 mo (85% retention). The primary explanatory variable of interest was exposure to four types of physical IPV in the past year. Depression symptom severity was measured using the Xhosa version of the ten-item Edinburgh Postnatal Depression Scale. In a pooled cross-sectional multivariable regression model adjusting for potentially confounding time-fixed and time-varying covariates, lagged IPV intensity had a statistically significant association with depression symptom severity (regression coefficient b = 1.04; 95% CI, 0.61–1.47), with estimates from a quantile regression model showing greater adverse impacts at the upper end of the conditional depression distribution. Fitting a fixed effects regression model accounting for all time-invariant confounding (e.g., history of childhood sexual abuse) yielded similar findings (b = 1.54; 95% CI, 1.13–1.96). The magnitudes of the coefficients indicated that a one–standard-deviation increase in IPV intensity was associated with a 12.3% relative increase in depression symptom severity over the same time period. The most important limitations of our study include exposure assessment that lacked measurement of sexual violence, which could have caused us to underestimate the severity of exposure; the extended latency period in the lagged analysis, which could have caused us to underestimate the strength of the association; and outcome assessment that was limited to the use of a screening instrument for depression symptom severity. Conclusions In this secondary analysis of data from a population-based, 3-y cluster-randomized controlled trial, IPV had a statistically significant association with depression symptom severity. The estimated associations were relatively large in magnitude, consistent with findings from high-income countries, and robust to potential confounding by time-invariant factors. Intensive health sector responses to reduce IPV and improve women’s mental health should be explored. PMID:26784110

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…

Model selection for semiparametric marginal mean regression accounting for within-cluster subsampling variability and informative cluster size.

PubMed

Shen, Chung-Wei; Chen, Yi-Hau

2018-03-13

We propose a model selection criterion for semiparametric marginal mean regression based on generalized estimating equations. The work is motivated by a longitudinal study on the physical frailty outcome in the elderly, where the cluster size, that is, the number of the observed outcomes in each subject, is "informative" in the sense that it is related to the frailty outcome itself. The new proposal, called Resampling Cluster Information Criterion (RCIC), is based on the resampling idea utilized in the within-cluster resampling method (Hoffman, Sen, and Weinberg, 2001, Biometrika 88, 1121-1134) and accommodates informative cluster size. The implementation of RCIC, however, is free of performing actual resampling of the data and hence is computationally convenient. Compared with the existing model selection methods for marginal mean regression, the RCIC method incorporates an additional component accounting for variability of the model over within-cluster subsampling, and leads to remarkable improvements in selecting the correct model, regardless of whether the cluster size is informative or not. Applying the RCIC method to the longitudinal frailty study, we identify being female, old age, low income and life satisfaction, and chronic health conditions as significant risk factors for physical frailty in the elderly. © 2018, The International Biometric Society.

Telehealth Coaching: Impact on Dietary and Physical Activity Contributions to Bone Health During a Military Deployment.

PubMed

Frank, Laura L; McCarthy, Mary S

2016-05-01

To examine the difference in bone health and body composition via blood biomarkers, bone mineral density, anthropometrics and dietary intake following deployment to Afghanistan among soldiers randomized to receive telehealth coaching promoting nutrition and exercise. This was a prospective, longitudinal, cluster-randomized, controlled trial with repeated measures in 234 soldiers. Measures included heel bone scan for bone mineral density, blood biomarkers for bone formation, resorption, and turnover, body composition via Futrex, resting metabolic rate via MedGem, physical activity using the Baecke Habitual Physical Activity Questionnaire, and dietary intake obtained from the Block Food Frequency Questionnaire. There were significant increases in body fat (p = 0.00035), osteocalcin (0.0152), and sports index (p = 0.0152) for the telehealth group. No other statistically significant differences were observed between groups. Vitamin D intake among soldiers was ≤ 35% of the suggested Dietary Reference Intakes for age. A 9-month deployment to Afghanistan increased body fat, bone turnover, and physical activity among soldiers randomized to receive telehealth strategies to build bone with nutrition and exercise. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

Impact of an Automatically Generated Cancer Survivorship Care Plan on Patient-Reported Outcomes in Routine Clinical Practice: Longitudinal Outcomes of a Pragmatic, Cluster Randomized Trial.

PubMed

Nicolaije, Kim A H; Ezendam, Nicole P M; Vos, M Caroline; Pijnenborg, Johanna M A; Boll, Dorry; Boss, Erik A; Hermans, Ralph H M; Engelhart, Karin C M; Haartsen, Joke E; Pijlman, Brenda M; van Loon-Baelemans, Ingrid E A M; Mertens, Helena J M M; Nolting, Willem E; van Beek, Johannes J; Roukema, Jan A; Zijlstra, Wobbe P; Kruitwagen, Roy F P M; van de Poll-Franse, Lonneke V

2015-11-01

This study was conducted to longitudinally assess the impact of an automatically generated survivorship care plan (SCP) on patient-reported outcomes in routine clinical practice. Primary outcomes were patient satisfaction with information and care. Secondary outcomes included illness perceptions and health care use. Twelve hospitals were randomly assigned to SCP care or usual care in a pragmatic, cluster randomized trial. Newly diagnosed patients with endometrial cancer completed questionnaires after diagnosis (n = 221; 75% response), 6 months (n = 158), and 12 months (n = 147). An SCP application was built in the Web-based ROGY (Registration System Oncological Gynecology). By clicking the SCP button, a patient-tailored SCP was generated. In the SCP care arm, 74% of patients received an SCP. They reported receiving more information about their treatment (mean [M] = 57, standard deviation [SD] = 20 v M = 47, SD = 24; P = .03), other services (M = 35, SD = 22 v M = 25, SD = 22; P = .03), and different places of care (M = 27, SD = 25 v M = 23, SD = 26; P = .04) than the usual care arm (scales, 0 to 100). However, there were no differences regarding satisfaction with information or care. Patients in the SCP care arm experienced more symptoms (M = 3.3, SD = 2.0 v M = 2.6, SD = 1.6; P = .03), were more concerned about their illness (M = 4.4, SD = 2.3 v M = 3.9, SD = 2.1; P = .03), were more affected emotionally (M = 4.0, SD = 2.2 v M = 3.7, SD = 2.2; P = .046), and reported more cancer-related contact with their primary care physician (M = 1.8, SD = 2.0 v M = 1.1, SD = 0.9; P = .003) than those in the usual care arm (scale, 1 to 10). These effects did not differ over time. The present trial showed no evidence of a benefit of SCPs on satisfaction with information and care. Furthermore, SCPs increased patients' concerns, emotional impact, experienced symptoms, and the amount of cancer-related contact with the primary care physician. Whether this may ultimately lead to more empowered patients should be investigated further. © 2015 by American Society of Clinical Oncology.

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.

Ready-to-use supplementary food increases fat mass and BMI in Haitian school-aged children.

PubMed

Iannotti, Lora L; Henretty, Nicole M; Delnatus, Jacques Raymond; Previl, Windy; Stehl, Tom; Vorkoper, Susan; Bodden, Jaime; Maust, Amanda; Smidt, Rachel; Nash, Marilyn L; Tamimie, Courtney A; Owen, Bridget C; Wolff, Patricia B

2015-04-01

In Haiti and other countries, large-scale investments in school feeding programs have been made with marginal evidence of nutrition outcomes. We aimed to examine the effectiveness of a fortified ready-to-use supplementary food (RUSF), Mamba, on reduced anemia and improved body composition in school-aged children compared to an unfortified cereal bar, Tablet Yo, and control groups. A cluster, randomized trial with children ages 3-13 y (n = 1167) was conducted in the north of Haiti. Six schools were matched and randomized to the control group, Tablet Yo group (42 g, 165 kcal), or Mamba group (50 g, 260 kcal, and >75% of the RDA for critical micronutrients). Children in the supplementation groups received the snack daily for 100 d, and all were followed longitudinally for hemoglobin concentrations, anthropometry, and bioelectrical impedance measures: baseline (December 2012), midline (March 2013), and endline (June 2013). Parent surveys were conducted at baseline and endline to examine secondary outcomes of morbidities and dietary intakes. Longitudinal regression modeling using generalized least squares and logit with random effects tested the main effects. At baseline,14.0% of children were stunted, 14.5% underweight, 9.1% thin, and 73% anemic. Fat mass percentage (mean ± SD) was 8.1% ± 4.3% for boys and 12.5% ± 4.4% for girls. In longitudinal modeling, Mamba supplementation increased body mass index z score (regression coefficient ± SEE) 0.25 ± 0.06, fat mass 0.45 ± 0.14 kg, and percentage fat mass 1.28% ± 0.27% compared with control at each time point (P < 0.001). Among boys, Mamba increased fat mass (regression coefficient ± SEE) 0.73 ± 0.19 kg and fat-free mass 0.62 ± 0.34 kg compared with control (P < 0.001). Mamba reduced the odds of developing anemia by 28% compared to control (adjusted OR: 0.72; 95% CI: 0.57, 0.91; P < 0.001). No treatment effect was found for hemoglobin concentration. To our knowledge, this is the first study to give evidence of body composition effects from an RUSF in school-aged children. © 2015 American Society for Nutrition.

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…

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

ERIC Educational Resources Information Center

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

2006-01-01

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

Estimating correlation between multivariate longitudinal data in the presence of heterogeneity.

PubMed

Gao, Feng; Philip Miller, J; Xiong, Chengjie; Luo, Jingqin; Beiser, Julia A; Chen, Ling; Gordon, Mae O

2017-08-17

Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121-0.420) and random slopes (ρ = 0.579, 95% CI: 0.349-0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125).

Longitudinal patterns of gambling activities and associated risk factors in college students

PubMed Central

Goudriaan, Anna E.; Slutske, Wendy S.; Krull, Jennifer L.; Sher, Kenneth J.

2009-01-01

Aims To investigate which clusters of gambling activities exist within a longitudinal study of college health, how membership in gambling clusters change over time and whether particular clusters of gambling are associated with unhealthy risk behaviour. Design Four-year longitudinal study (2002–2006). Setting Large, public university. Participants Undergraduate college students. Measurements Ten common gambling activities were measured during 4 consecutive college years (years 1–4). Clusters of gambling activities were examined using latent class analyses. Relations between gambling clusters and gender, Greek membership, alcohol use, drug use, personality indicators of behavioural undercontrol and psychological distress were examined. Findings Four latent gambling classes were identified: (1) a low-gambling class, (2) a card gambling class, (3) a casino/slots gambling class and (4) an extensive gambling class. Over the first college years a high probability of transitioning from the low-gambling class and the card gambling class into the casino/slots gambling class was present. Membership in the card, casino/slots and extensive gambling classes were associated with higher scores on alcohol/drug use, novelty seeking and self-identified gambling problems compared to the low-gambling class. The extensive gambling class scored higher than the other gambling classes on risk factors. Conclusions Extensive gamblers and card gamblers are at higher risk for problem gambling and other risky health behaviours. Prospective examinations of class membership suggested that being in the extensive and the low gambling classes was highly stable across the 4 years of college. PMID:19438422

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.

Prevention of illicit drug use through a school-based program: results of a longitudinal, cluster-randomized controlled trial.

PubMed

Guo, Jong-Long; Lee, Tzu-Chi; Liao, Jung-Yu; Huang, Chiu-Mieh

2015-03-01

To evaluate the long-term effects of an illicit drug use prevention program for adolescents that integrates life skills into the theory of planned behavior. We conducted a cluster-randomized trial in which 24 participating schools were randomized to either an intervention group (12 schools, n = 1,176 students) or a control group (12 schools, n = 915 students). Participants were grade 7 students. The intervention comprised a main intervention of 10 sessions and two booster interventions. Booster 1 (four sessions) and booster 2 (two sessions) were performed at 6 months and 12 months, respectively, after completion of the main intervention. Assessments were made at baseline, after the main intervention, and after each booster session using specific questionnaires for measuring participants' attitudes, subjective norms, perceived behavioral control, and life skills. Retention rates were 71.9% (845/1,176) in the intervention group and 90.7% (830/915) in the control group after the 12-month follow-up. A significantly lower proportion of intervention group participants reported illicit drug use after the first and second booster sessions compared with control group participants (.1% vs. 1.7% and .2% vs. 1.7%, respectively; both p < .05). Attitudes, subjective norms, perceived behavioral control, life skills, and behavioral intention scores of the intervention group were significantly higher than those of control group after the first and second booster sessions (all p < .001), suggesting that intervention group students tended to avoid drug use. A drug use prevention program integrating life skills into the theory of planned behavior may be effective for reducing illicit drug use and improving planned behavior-related constructs in adolescents. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

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…

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.

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

Two-year changes in refractive error and related biometric factors in an adult Chinese population.

PubMed

He, Mingguang; Kong, Xiangbin; Chen, Qianyun; Zeng, Yangfa; Huang, Yuanzhou; Zhang, Jian; Morgan, Ian G; Meltzer, Mirjam E; Jin, Ling; Congdon, Nathan

2014-08-01

This article provides, to our knowledge, the first longitudinal population-based data on refractive error (RE) in Chinese persons. To study cohort effects and changes associated with aging in REs among Chinese adults. A 2-year, longitudinal population-based cohort study was conducted in southern China. Participants, identified using cluster random sampling, included residents of Yuexiu District, Guangzhou, China, aged 35 years or older who had undergone no previous eye surgery. Participants underwent noncycloplegic automated refraction and keratometry in December 2008 and December 2010; in a random 50% sample of the participants, anterior segment ocular coherence tomography measurement of lens thickness, as well as measurement of axial length and anterior chamber depth by partial coherence laser interferometry, were performed. Two-year change in spherical equivalent refraction (RE), lens thickness, axial length, and anterior chamber depth in the right eye. A total of 745 individuals underwent biometric testing in both 2008 and 2010 (2008 mean [SD] age, 52.2 [11.5] years; 53.7% women). Mean RE showed a 2-year hyperopic shift from -0.44 (2.21) to -0.31 (2.26) diopters (D) (difference, +0.13; 95% CI, 0.11 to 0.16). A consistent 2-year hyperopic shift of 0.09 to 0.22 D was observed among participants aged 35 to 64 years when stratifying by decade, suggesting that a substantial change in RE with aging may occur during this 30-year period. Cross-sectionally, RE increased only in the cohort younger than 50 years (0.11 D/y; 95% CI, 0.06 to 0.16). In the cross-sectional data, axial length decreased at -0.06 mm/y (95% CI, -0.09 to -0.04), although the 2-year change in axial length was positive and thus could not explain the cross-sectional difference. These latter results suggest a cohort effect, with greater myopia developing among younger persons. This first Chinese population-based longitudinal study of RE provides evidence for both important longitudinal aging changes and cohort effects, most notably greater myopia prevalence among younger persons.

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…

Problem Behaviours, Traditional Bullying and Cyberbullying among Adolescents: Longitudinal Analyses

ERIC Educational Resources Information Center

Lester, Leanne; Cross, Donna; Shaw, Therese

2012-01-01

Problem Behaviour Theory suggests that young people's problem behaviours tend to cluster. This study examined the relationship between traditional bullying, cyberbullying and engagement in problem behaviours using longitudinal data from approximately 1500 students. Levels of traditional victimisation and perpetration at the beginning of secondary…

Methods for sample size determination in cluster randomized trials

PubMed Central

Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

2015-01-01

Background: The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. Methods: We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. Results: We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. Conclusions: There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. PMID:26174515

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.

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.

Identification of five clusters of comorbidities in a longitudinal Japanese chronic obstructive pulmonary disease cohort.

PubMed

Chubachi, Shotaro; Sato, Minako; Kameyama, Naofumi; Tsutsumi, Akihiro; Sasaki, Mamoru; Tateno, Hiroki; Nakamura, Hidetoshi; Asano, Koichiro; Betsuyaku, Tomoko

2016-08-01

Patients with chronic obstructive pulmonary disease (COPD) frequently suffer from various comorbidities. Recently, cluster analysis has been proposed to examine the phenotypic heterogeneity in COPD. In order to comprehensively understand the comorbidities of COPD in Japan, we conducted multicenter, longitudinal cohort study, called the Keio COPD Comorbidity Research (K-CCR). In this cohort, comorbid diagnoses were established by both objective examination and review of clinical records, in addition to self-report. We aimed to investigate the clustering of nineteen clinically relevant comorbidities and the meaningful outcomes of the clusters over a two-year follow-up period. The present study analyzed data from COPD patients whose data of comorbidities were completed (n = 311). Cluster analysis was performed using Ward's minimum-variance method. Five comorbidity clusters were identified: less comorbidity; malignancy; metabolic and cardiovascular; gastroesophageal reflux disease (GERD) and psychological; and underweight and anemic. FEV1 did not differ among the clusters. GERD and psychological cluster had worse COPD assessment test (CAT) and Saint George's respiratory questionnaire (SGRQ) at baseline compared to the other clusters (CAT: p = 0.0003 and SGRQ: p = 0.00046). The rate of change in these scores did not differ within 2 years. The underweight and anemic cluster included subjects with lower baseline ratio of predicted diffusing capacity (DLco/VA) compared to the malignancy cluster (p = 0.036). Five clusters of comorbidities were identified in Japanese COPD patients. The clinical characteristics and health-related quality of life were different among these clusters during a follow-up of two years. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Conducting Three-Level Longitudinal Analyses

ERIC Educational Resources Information Center

Peugh, James L.; Heck, Ronald H.

2017-01-01

Researchers in the field of early adolescence interested in quantifying the environmental influences on a response variable of interest over time would use cluster sampling (i.e., obtaining repeated measures from students nested within classrooms and/or schools) to obtain the needed sample size. The resulting longitudinal data would be nested at…

Profiles of Intrinsic and Extrinsic Motivations in Elementary School: A Longitudinal Analysis

ERIC Educational Resources Information Center

Corpus, Jennifer Henderlong; Wormington, Stephanie V.

2014-01-01

The authors used a person-centered, longitudinal approach to identify and evaluate naturally occurring combinations of intrinsic and extrinsic motivations among 490 third- through fifth-grade students. Cluster analysis revealed 3 groups, characterized by high levels of both motivations ("high quantity"): high intrinsic motivation but low…

Two-Year Longitudinal Analysis of a Cluster Randomized Trial of Physical Activity Promotion by General Practitioners

PubMed Central

Grandes, Gonzalo; Sanchez, Alvaro; Montoya, Imanol; Ortega Sanchez-Pinilla, Ricardo; Torcal, Jesús

2011-01-01

Background We evaluate the effectiveness of a physical activity promotion programme carried out by general practitioners with inactive patients in routine care. Methods and Findings Pragmatic, cluster randomised clinical trial conducted in eleven public primary care centres in Spain. Fifty-six general practitioners (GPs) were randomly assigned to intervention (29) or standard care (27) groups. They assessed the physical activity level of a systematic sample of patients in routine practice and recruited 4317 individuals (2248 intervention and 2069 control) who did not meet minimum physical activity recommendations. Intervention GPs provided advice to all patients and a physical activity prescription to the subgroup attending an additional appointment (30%). A third of these prescriptions were opportunistically repeated. Control GPs provided standard care. Primary outcome measure was the change in self-reported physical activity from baseline to six, 12 and 24 months. Secondary outcomes included cardiorespiratory fitness and health-related quality of life. A total of 3691 patients (85%) were included in the longitudinal analysis and overall trends over the whole 24 month follow-up were significantly better in the intervention group (p<0.01). The greatest differences with the control group were observed at six months (adjusted difference 1.7 MET*hr/wk [95% CI, 0.8 to 2.6], 25 min/wk [95% CI, 11.3 to 38.4], and a 5.3% higher percentage of patients meeting minimum recommendations [95% CI: 2.1% to 8.8%] NNT = 19). These differences were not statistically significant at 12 and 24 months. No differences were found in secondary outcomes. A significant difference was maintained until 24 months in the proportion of patients achieving minimum recommendation in the subgroup that received a repeat prescription (adjusted difference 10.2%, 95% CI 1.5% to 19.4%). Conclusions General practitioners are effective at increasing the level of physical activity among their inactive patients during the initial six-months of an intervention but this effect wears off at 12 and 24 months. Only in the subgroup of patients receiving repeat prescriptions of physical activity is the effect maintained in long-term. Trial Registration clinicaltrials.gov NCT00131079 PMID:21479243

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 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…

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…

Effects of statewide health promotion in primary schools on children's sick days, visits to a physician and parental absence from work: a cluster-randomized trial.

PubMed

Kesztyüs, Dorothea; Lauer, Romy; Traub, Meike; Kesztyüs, Tibor; Steinacker, Jürgen Michael

2016-12-12

Based on the World Health Organization's global school health initiative we investigate intervention effects of statewide health promotion in schools on the numbers of children's sick days and visits to a physician, and parental days off work due to child illness. Cluster-randomized trial with 1-year follow-up in primary schools in the state of Baden-Württemberg, Germany. Anthropometric measurements of first and second grade school children were taken by trained staff. Parents filled in questionnaires for information about socio-demographics, health-related variables, numbers of children's sick days, visits to a physician, and days parents had to stay off work to care for a sick child. Longitudinal differences in the outcome variables were calculated between baseline and follow-up. Intraclass correlation coefficients were determined to quantify a possible clustering of data in schools. Accordingly, linear models and linear mixed models were applied to identify relationships and ascertain significances. Data from 1943 children (1 st grade n = 1024, 6.6 ± 0.4 years old; 2 nd grade n = 919, 7.6 ± 0.4 years old) were available at baseline. Unadjusted differences regarding both grades were found between mean longitudinal changes in intervention and control group in children's sick days (-3.2 ± 7.1 vs. -2.3 ± 5.6, p = 0.013), and maternal days off work (-0.9 ± 2.4 vs. -0.5 ± 2.8, p = 0.019). The intervention effect on sick days was adjusted in a linear regression for baseline values, gender and migration background and confirmed for first grade children (B = -0.83, p = 0.003). The intervention effect on maternal days off work lost its significance after adjusting for baseline values. No significant differences were detected in the numbers of children's visits to a physician and paternal days off work. School-based health promotion slightly reduces sick days in first grade children. Subsequently, parents may not need to stay off work themselves. Small individual effects add up to larger benefits in a statewide implementation of health promotion. Additionally, health promotion may also positively contribute to school success. The study was registered on the German Clinical Trials Register (DRKS), Freiburg University, Germany, under the DRKS-ID: DRKS00000494 . Registered: 25 August 2010.

Comparison of torsional and microburst longitudinal phacoemulsification: a prospective, randomized, masked clinical trial.

PubMed

Vasavada, Abhay R; Raj, Shetal M; Patel, Udayan; Vasavada, Vaishali; Vasavada, Viraj

2010-01-01

To compare intraoperative performance and postoperative outcome of three phacoemulsification technologies in patients undergoing microcoaxial phacoemulsification through 2.2-mm corneal incisions. The prospective, randomized, single-masked study included 360 eyes randomly assigned to torsional (Infiniti Vision System; Alcon Laboratories, Fort Worth, TX), microburst with longitudinal (Infiniti), or microburst with longitudinal (Legacy Everest, Alcon Laboratories) ultrasound. Assessments included surgical clock time, fluid volume, and intraoperative complications, central corneal thickness on day 1 and months 1 and 3 postoperatively, and endothelial cell density at 3 months postoperatively. Comparisons among groups were conducted. Torsional ultrasound required significantly less surgical clock time and fluid volume than the other groups. There were no intraoperative complications. Change in central corneal thickness and endothelial cell loss was significantly lower in the torsional ultrasound group at all postoperative visits (P < .001, Kruskal-Wallis test) compared to microburst longitudinal ultrasound modalities. Torsional ultrasound demonstrated quantitatively superior intraoperative performance and showed less increase in corneal thickness and less endothelial cell loss compared to microburst longitudinal ultrasound. Copyright 2010, SLACK Incorporated.

Parental Influences on Adolescent Adjustment: Parenting Styles Versus Parenting Practices

ERIC Educational Resources Information Center

Lee, Sang Min; Daniels, M. Harry; Kissinger, Daniel B.

2006-01-01

The study identified distinct patterns of parental practices that differentially influence adolescent behavior using the National Educational Longitudinal Survey (NELS:88) database. Following Brenner and Fox's research model (1999), the cluster analysis was used to classify the four types of parental practices. The clusters of parenting practices…

First Selection, Then Influence: Developmental Differences in Friendship Dynamics Regarding Academic Achievement

ERIC Educational Resources Information Center

Gremmen, Mariola Claudia; Dijkstra, Jan Kornelis; Steglich, Christian; Veenstra, René

2017-01-01

This study concerns peer selection and influence dynamics in early adolescents' friendships regarding academic achievement. Using longitudinal social network analysis (RSiena), both selection and influence processes were investigated for students' average grades and their cluster-specific grades (i.e., language, exact, and social cluster). Data…

Individual Differences in Achievement Goals: A Longitudinal Study of Cognitive, Emotional, and Achievement Outcomes

ERIC Educational Resources Information Center

Daniels, Lia M.; Haynes, Tara L.; Stupnisky, Robert H.; Perry, Raymond P.; Newall, Nancy E.; Pekrun, Reinhard

2008-01-01

Within achievement goal theory debate remains regarding the adaptiveness of certain combinations of goals. Assuming a multiple-goals perspective, we used cluster analysis to classify 1002 undergraduate students according to their mastery and performance-approach goals. Four clusters emerged, representing different goal combinations: high…

Predicting declines in perceived relationship continuity using practice deprivation scores: a longitudinal study in primary care.

PubMed

Levene, Louis S; Baker, Richard; Walker, Nicola; Williams, Christopher; Wilson, Andrew; Bankart, John

2018-06-01

Increased relationship continuity in primary care is associated with better health outcomes, greater patient satisfaction, and fewer hospital admissions. Greater socioeconomic deprivation is associated with lower levels of continuity, as well as poorer health outcomes. To investigate whether deprivation scores predicted variations in the decline over time of patient-perceived relationship continuity of care, after adjustment for practice organisational and population factors. An observational study in 6243 primary care practices with more than one GP, in England, using a longitudinal multilevel linear model, 2012-2017 inclusive. Patient-perceived relationship continuity was calculated using two questions from the GP Patient Survey. The effect of deprivation on the linear slope of continuity over time was modelled, adjusting for nine confounding variables (practice population and organisational factors). Clustering of measurements within general practices was adjusted for by using a random intercepts and random slopes model. Descriptive statistics and univariable analyses were also undertaken. Relationship continuity declined by 27.5% between 2012 and 2017, and at all deprivation levels. Deprivation scores from 2012 did not predict variations in the decline of relationship continuity at practice level, after accounting for the effects of organisational and population confounding variables, which themselves did not predict, or weakly predicted with very small effect sizes, the decline of continuity. Cross-sectionally, continuity and deprivation were negatively correlated within each year. The decline in relationship continuity of care has been marked and widespread. Measures to maximise continuity will need to be feasible for individual practices with diverse population and organisational characteristics. © British Journal of General Practice 2018.

Efficient sampling of complex network with modified random walk strategies

NASA Astrophysics Data System (ADS)

Xie, Yunya; Chang, Shuhua; Zhang, Zhipeng; Zhang, Mi; Yang, Lei

2018-02-01

We present two novel random walk strategies, choosing seed node (CSN) random walk and no-retracing (NR) random walk. Different from the classical random walk sampling, the CSN and NR strategies focus on the influences of the seed node choice and path overlap, respectively. Three random walk samplings are applied in the Erdös-Rényi (ER), Barabási-Albert (BA), Watts-Strogatz (WS), and the weighted USAir networks, respectively. Then, the major properties of sampled subnets, such as sampling efficiency, degree distributions, average degree and average clustering coefficient, are studied. The similar conclusions can be reached with these three random walk strategies. Firstly, the networks with small scales and simple structures are conducive to the sampling. Secondly, the average degree and the average clustering coefficient of the sampled subnet tend to the corresponding values of original networks with limited steps. And thirdly, all the degree distributions of the subnets are slightly biased to the high degree side. However, the NR strategy performs better for the average clustering coefficient of the subnet. In the real weighted USAir networks, some obvious characters like the larger clustering coefficient and the fluctuation of degree distribution are reproduced well by these random walk strategies.

Effectiveness of a School- and Community-based Academic Asthma Health Education Program on Use of Effective Asthma Self-care Behaviors in Older School-age Students

PubMed Central

Kintner, Eileen K.; Cook, Gwendolyn; Marti, C. Nathan; Allen, April; Stoddard, Debbie; Harmon, Phyllis; Gomes, Melissa; Meeder, Linda; Van Egeren, Laurie A.

2014-01-01

Purpose The purpose was to evaluate the effectiveness of SHARP, an academic asthma health education and counseling program, on fostering use of effective asthma self-care behaviors. Design and Methods This was a phase III, two-group, cluster randomized, single-blinded, longitudinal design guided the study. Caregivers of 205 fourth- and fifth-grade students completed the asthma health behaviors survey at pre-intervention and 1, 12, and 24 months post-intervention. Analysis involved multilevel modeling. Results All students demonstrated improvement in episode management, risk-reduction/prevention, and health promotion behaviors; SHARP students demonstrated increased improvement in episode management and risk-reduction/prevention behaviors. Practice Implications Working with schoolteachers, nurses can improve use of effective asthma self-care behaviors. PMID:25443867

Fidelity and outcomes in six integrated dual disorders treatment programs.

PubMed

Chandler, Daniel W

2011-02-01

Fidelity scores and outcomes were measured in six outpatient programs in California which implemented Integrated Dual Disorders Treatment (IDDT). Outcomes were measured for 1 year in four sites and 2 years in two sites; fidelity was assessed at 6 month intervals. Three of the six sites achieved high fidelity (at least a 4 on a 5 point fidelity scale) and three moderate fidelity (at least a 3). Retention in treatment, mental health functioning, stage of substance abuse treatment, abstinence, and psychiatric hospitalization were measured. Outcomes for individual programs were generally positive but not consistent within programs or across programs. Using pooled data in a longitudinal regression model with random effects at person level and adjustment of standard errors for clustering by site, change over time was not statistically significant for the primary outcomes. Fidelity scores had limited association with positive outcomes.

Effectiveness of a School-based Academic Asthma Health Education and Counseling Program on Fostering Acceptance of Asthma in Older School-age Students with Asthma

PubMed Central

Kintner, Eileen K.; Cook, Gwendolyn; Marti, C. Nathan; Gomes, Melissa; Meeder, Linda; Van Egeren, Laurie A.

2014-01-01

Purpose The purpose was to evaluate the effectiveness of the academic asthma education and counseling SHARP program on fostering psychosocial acceptance of asthma. Design and Methods This was a phase III, two-group, cluster randomized, single-blinded, longitudinal study. Students from grades 4 and 5 (N = 205) with asthma and their caregivers completed surveys at pre-intervention and at 1, 12, and 24 months post-intervention. Analysis involved multilevel modeling. Results All students demonstrated significant improvement in aspects of acceptance; students in SHARP demonstrated significant improvement in openness to sharing and connectedness with teachers over students in the control condition. Practice Implications The SHARP program offers a well-tested, effective program for psychosocial acceptance of asthma, which is welcomed by schools. PMID:25443593

Spin dynamics of random Ising chain in coexisting transverse and longitudinal magnetic fields

NASA Astrophysics Data System (ADS)

Liu, Zhong-Qiang; Jiang, Su-Rong; Kong, Xiang-Mu; Xu, Yu-Liang

2017-05-01

The dynamics of the random Ising spin chain in coexisting transverse and longitudinal magnetic fields is studied by the recursion method. Both the spin autocorrelation function and its spectral density are investigated by numerical calculations. It is found that system's dynamical behaviors depend on the deviation σJ of the random exchange coupling between nearest-neighbor spins and the ratio rlt of the longitudinal and the transverse fields: (i) For rlt = 0, the system undergoes two crossovers from N independent spins precessing about the transverse magnetic field to a collective-mode behavior, and then to a central-peak behavior as σJ increases. (ii) For rlt ≠ 0, the system may exhibit a coexistence behavior of a collective-mode one and a central-peak one. When σJ is small (or large enough), system undergoes a crossover from a coexistence behavior (or a disordered behavior) to a central-peak behavior as rlt increases. (iii) Increasing σJ depresses effects of both the transverse and the longitudinal magnetic fields. (iv) Quantum random Ising chain in coexisting magnetic fields may exhibit under-damping and critical-damping characteristics simultaneously. These results indicate that changing the external magnetic fields may control and manipulate the dynamics of the random Ising chain.

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.

A Randomized Trial of Longitudinal Effects of Low-Intensity Responsivity Education/Prelinguistic Milieu Teaching

ERIC Educational Resources Information Center

Warren, Steven F.; Fey, Marc E.; Finestack, Lizbeth, H.; Brady, Nancy C.; Bredin-Oja, Shelley L.; Fleming, Kandace K.

2008-01-01

Purpose: To evaluate the longitudinal effects of a 6-month course of responsivity education (RE)/prelinguistic milieu teaching (PMT) for young children with developmental delay. Method: Fifty-one children, age 24-33 months, with fewer than 10 expressive words were randomly assigned to early-treatment/no-treatment groups. All treatment was added as…

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.

X-ray off-specular reflectivity studies of electrochemical pitting of Cu surfaces in sodium bicarbonate solution

NASA Astrophysics Data System (ADS)

Feng, Y. P.; Sinha, S. K.; Melendres, C. A.; Lee, D. D.

1996-02-01

We have studied the electrochemically-induced pitting process on a Cu electrode in NaHCO 3 solution using in-situ X-ray off-specular reflectivity measurements. The morphology and growth dynamics of the localized corrosion sites or pits were studied as the applied potential was varied from the cathodic region where the Cu surface is relatively free of oxide films to the anodic region where surface roughening occurs by general corrosion with concomitant formation of an oxide film. Quantitative analysis of the experimental results indicates that early pitting proceeds in favor of nucleation of pit clusters over individual pit growth. It was found that the lateral distribution of the pits is not random but exhibits a short-range order as evidenced by the appearance of a side peak in the transverse off-specular reflectivity. The position, height, and width of the peak was modeled to yield the average size, nearest-neighbor distance (within any one of the clusters), and over-all density of the pits averaged over the entire illuminated surface. In addition, measurements of the longitudinal off-specular reflectivity indicate a bimodal depth distribution for the pits, suggesting a “film breaking” type of pitting mechanism.

Trial protocol: a clustered, randomised, longitudinal, type 2 translational trial of alcohol consumption and alcohol-related harm among adolescents in Australia.

PubMed

Rowland, B; Abraham, C; Carter, R; Abimanyi-Ochom, J; Kelly, A B; Kremer, P; Williams, J W; Smith, R; Hall, J K; Wagner, D; Renner, H; Hosseini, T; Osborn, A; Mohebbi, M; Toumbourou, J W

2018-04-27

This cluster randomised control trial is designed to evaluate whether the Communities That Care intervention (CTC) is effective in reducing the proportion of secondary school age adolescents who use alcohol before the Australian legal purchasing age of 18 years. Secondary outcomes are other substance use and antisocial behaviours. Long term economic benefits of reduced alcohol use by adolescents for the community will also be assessed. Fourteen communities and 14 other non-contiguous communities will be matched on socioeconomic status (SES), location, and size. One of each pair will be randomly allocated to the intervention in three Australian states (Victoria, Queensland and Western Australia). A longitudinal survey will recruit grade 8 and 10 students (M = 15 years old, N = 3500) in 2017 and conduct follow-up surveys in 2019 and 2021 (M = 19 years old). Municipal youth populations will also be monitored for trends in alcohol-harms using hospital and police administrative data. Community-led interventions that systematically and strategically implement evidence-based programs have been shown to be effective in producing population-level behaviour change, including reduced alcohol and drug use. We expect that the study will be associated with significant effects on alcohol use amongst adolescents because interventions adopted within communities will be based on evidence-based practices and target specific problems identified from surveys conducted within each community. The trial was retrospectively registered in September, 2017 ( ACTRN12616001276448 ), as communities were selected prior to trial registration; however, participants were recruited after registration. Findings will be disseminated in peer-review journals and community fora.

One-year follow-up of a coach-delivered dating violence prevention program: a cluster randomized controlled trial.

PubMed

Miller, Elizabeth; Tancredi, Daniel J; McCauley, Heather L; Decker, Michele R; Virata, Maria Catrina D; Anderson, Heather A; O'Connor, Brian; Silverman, Jay G

2013-07-01

Perpetration of physical, sexual, and psychological abuse is prevalent in adolescent relationships. One strategy for reducing such violence is to increase the likelihood that youth will intervene when they see peers engaging in disrespectful and abusive behaviors. This 12-month follow-up of a cluster RCT examined the longer-term effectiveness of Coaching Boys Into Men, a dating violence prevention program targeting high school male athletes. This cluster RCT was conducted from 2009 to 2011. The unit of randomization was the school, and the unit of analysis was the athlete. Data were analyzed in 2012. Participants were male athletes in Grades 9-11 (N=1513) participating in athletics in 16 high schools. The intervention consisted of training athletic coaches to integrate violence prevention messages into coaching activities through brief, weekly, scripted discussions with athletes. Primary outcomes were intentions to intervene, recognition of abusive behaviors, and gender-equitable attitudes. Secondary outcomes included bystander behaviors and abuse perpetration. Intervention effects were expressed as adjusted mean between-arm differences in changes in outcomes over time, estimated via regression models for clustered, longitudinal data. Perpetration of dating violence in the past 3 months was less prevalent among intervention athletes relative to control athletes, resulting in an estimated intervention effect of -0.15 (95% CI=-0.27, -0.03). Intervention athletes also reported lower levels of negative bystander behaviors (i.e., laughing and going along with peers' abusive behaviors) compared to controls (-0.41, 95% CI=-0.72, -0.10). No differences were observed in intentions to intervene (0.04, 95% CI=-0.07, 0.16); gender-equitable attitudes (-0.04, 95% CI=-0.11, 0.04); recognition of abusive behaviors (-0.03, 95% CI=-0.15, 0.09); or positive bystander behaviors (0.04, 95% CI=-0.11, 0.19). This school athletics-based dating violence prevention program is a promising approach to reduce perpetration and negative bystander behaviors that condone dating violence among male athletes. This study is registered at www.clinicaltrials.gov NCTO1367704. Copyright © 2013 American Journal of Preventive Medicine.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review.

PubMed

Leech, Rebecca M; McNaughton, Sarah A; Timperio, Anna

2014-01-22

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5-18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥ 9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review

PubMed Central

2014-01-01

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5–18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity. PMID:24450617

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.

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…

Motivation for Weight-Loss Diets: A Clustering, Longitudinal Field Study Using Self-Esteem and Self-Determination Theory Perspectives

ERIC Educational Resources Information Center

Georgiadis, Manolis M.; Biddle, Stuart J. H.; Stavrou, Nektarios A.

2006-01-01

Background: Gradual elevation of body weight leads numerous individuals to dieting and weight loss behaviours. Nevertheless, the prevalence of obesity continues to rise in industrialised countries. The examination of the motivational determinants of dietary modification ("dieting") in order to identify clusters of individuals in the…

FUEL ROD CLUSTERS

DOEpatents

Schultz, A.B.

1959-08-01

A cluster of nuclear fuel rods and a tubular casing therefor through which a coolant flows in heat-exchange contact with the fuel rods is described. The fuel rcds are held in the casing by virtue of the compressive force exerted between longitudinal ribs of the fuel rcds and internal ribs of the casing or the internal surfaces thereof.

The Multigroup Multilevel Categorical Latent Growth Curve Models

ERIC Educational Resources Information Center

Hung, Lai-Fa

2010-01-01

Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals. This study embedded the longitudinal model within a multigroup…

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

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.

Do Savings Mediate Changes in Adolescents' Future Orientation and Health-Related Outcomes? Findings From Randomized Experiment in Uganda.

PubMed

Karimli, Leyla; Ssewamala, Fred M

2015-10-01

This present study tests the proposition that an economic strengthening intervention for families caring for AIDS-orphaned adolescents would positively affect adolescent future orientation and psychosocial outcomes through increased asset accumulation (in this case, by increasing family savings). Using longitudinal data from the cluster-randomized experiment, we ran generalized estimating equation models with robust standard errors clustering on individual observations. To examine whether family savings mediate the effect of the intervention on adolescents' future orientation and psychosocial outcomes, analyses were conducted in three steps: (1) testing the effect of intervention on mediator; (2) testing the effect of mediator on outcomes, controlling for the intervention; and (3) testing the significance of mediating effect using Sobel-Goodman method. Asymmetric confidence intervals for mediated effect were obtained through bootstrapping-to address the assumption of normal distribution. Results indicate that participation in a matched Child Savings Account (CSA) program improved adolescents' future orientation and psychosocial outcomes by reducing hopelessness, enhancing self-concept, and improving adolescents' confidence about their educational plans. However, the positive intervention effect on adolescent future orientation and psychosocial outcomes was not transmitted through saving. In other words, participation in the matched CSA program improved adolescent future orientation and psychosocial outcomes regardless of its impact on reported savings. Further research is necessary to understand exactly how participation in economic strengthening interventions, for example, those that employ matched CSAs, shape adolescent future orientation and psychosocial outcomes: what, if not savings, transmits the treatment effect and how? Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Do savings mediate changes in adolescents’ future orientation and health-related outcomes? Findings from randomized experiment in Uganda

PubMed Central

Karimli, Leyla; Ssewamala, Fred M.

2015-01-01

Purpose This present study tests the proposition that an economic strengthening intervention for families caring for AIDS-orphaned adolescents would positively affect adolescent future orientation and psychosocial outcomes through increased asset-accumulation (in this case, by increasing family savings). Methods Using longitudinal data from the cluster-randomized experiment we ran generalized estimating equation (GEE) models with robust standard errors clustering on individual observations. To examine whether family savings mediate the effect of the intervention on adolescents’ future orientation and psychosocial outcomes, analyses were conducted in three steps: (1) testing the effect of intervention on mediator; (2) testing the effect of mediator on outcomes, controlling for the intervention; and (3) testing the significance of mediating effect using Sobel-Goodman method. Asymmetric confidence intervals for mediated effect were obtained through bootstrapping—to address the assumption of normal distribution. Results Results indicate that participation in a matched Child Savings Account program improved adolescents’ future orientation and psychosocial outcomes by reducing hopelessness, enhancing self-concept, and improving adolescents’ confidence about their educational plans. However, the positive intervention effect on adolescent future orientation and psychosocial outcomes was not transmitted through saving. In other words, participation in the matched Child Savings Account program improved adolescent future orientation and psychosocial outcomes regardless of its impact on reported savings. Conclusions Further research is necessary to understand exactly how participation in economic strengthening interventions, for example, those that employ matched Child Savings Accounts, shape adolescent future orientation and psychosocial outcomes: what, if not savings, transmits the treatment effect and how? PMID:26271162

Bayesian analysis of longitudinal dyadic data with informative missing data using a dyadic shared-parameter model.

PubMed

Ahn, Jaeil; Morita, Satoshi; Wang, Wenyi; Yuan, Ying

2017-01-01

Analyzing longitudinal dyadic data is a challenging task due to the complicated correlations from repeated measurements and within-dyad interdependence, as well as potentially informative (or non-ignorable) missing data. We propose a dyadic shared-parameter model to analyze longitudinal dyadic data with ordinal outcomes and informative intermittent missing data and dropouts. We model the longitudinal measurement process using a proportional odds model, which accommodates the within-dyad interdependence using the concept of the actor-partner interdependence effects, as well as dyad-specific random effects. We model informative dropouts and intermittent missing data using a transition model, which shares the same set of random effects as the longitudinal measurement model. We evaluate the performance of the proposed method through extensive simulation studies. As our approach relies on some untestable assumptions on the missing data mechanism, we perform sensitivity analyses to evaluate how the analysis results change when the missing data mechanism is misspecified. We demonstrate our method using a longitudinal dyadic study of metastatic breast cancer.

Objective and Perceived Weight: Associations with Risky Adolescent Sexual Behavior

PubMed Central

Akers, Aletha Y.; Cohen, Elan D.; Marshal, Michael P.; Roebuck, Geoff; Yu, Lan; Hipwell, Alison E.

2016-01-01

CONTEXT Studies have shown that obesity is associated with increased sexual risk-taking, particularly among adolescent females, but the relationships between obesity, perceived weight and sexual risk behaviors are poorly understood. METHODS Integrative data analysis was performed that combined baseline data from the 1994–1995 National Longitudinal Study of Adolescent Health (from 17,606 respondents in grades 7–12) and the 1997 National Longitudinal Survey of Youth (from 7,752 respondents aged 12–16). Using six sexual behaviors measured in both data sets (age at first intercourse, various measures of contraceptive use and number of partners), cluster analysis was conducted that identified five distinct behavior clusters. Multivariate ordinal logistic regression analysis examined associations between adolescents’ weight status (categorized as underweight, normal-weight, overweight or obese) and weight perception and their cluster membership. RESULTS Among males, being underweight, rather than normal-weight, was negatively associated with membership in increasingly risky clusters (odds ratio, 0.5), as was the perception of being overweight, as opposed to about the right weight (0.8). However, being overweight was positively associated with males’ membership in increasingly risky clusters (1.3). Among females, being obese, rather than normal-weight, was negatively correlated with membership in increasingly risky clusters (0.8), while the perception of being overweight was positively correlated with such membership (1.1). CONCLUSIONS Both objective and subjective assessments of weight are associated with the clustering of risky sexual behaviors among adolescents, and these behavioral patterns differ by gender. PMID:27608419

Objective and Perceived Weight: Associations with Risky Adolescent Sexual Behavior.

PubMed

Akers, Aletha Y; Cohen, Elan D; Marshal, Michael P; Roebuck, Geoff; Yu, Lan; Hipwell, Alison E

2016-09-01

Studies have shown that obesity is associated with increased sexual risk-taking, particularly among adolescent females, but the relationships between obesity, perceived weight and sexual risk behaviors are poorly understood. Integrative data analysis was performed that combined baseline data from the 1994-1995 National Longitudinal Study of Adolescent Health (from 17,606 respondents in grades 7-12) and the 1997 National Longitudinal Survey of Youth (from 7,752 respondents aged 12-16). Using six sexual behaviors measured in both data sets (age at first intercourse, various measures of contraceptive use and number of partners), cluster analysis was conducted that identified five distinct behavior clusters. Multivariate ordinal logistic regression analysis examined associations between adolescents' weight status (categorized as underweight, normal-weight, overweight or obese) and weight perception and their cluster membership. Among males, being underweight, rather than normal-weight, was negatively associated with membership in increasingly risky clusters (odds ratio, 0.5), as was the perception of being overweight, as opposed to about the right weight (0.8). However, being overweight was positively associated with males' membership in increasingly risky clusters (1.3). Among females, being obese, rather than normal-weight, was negatively correlated with membership in increasingly risky clusters (0.8), while the perception of being overweight was positively correlated with such membership (1.1). Both objective and subjective assessments of weight are associated with the clustering of risky sexual behaviors among adolescents, and these behavioral patterns differ by gender. Copyright © 2016 by the Guttmacher Institute.

Clustering of unhealthy behaviors in the aerobics center longitudinal study.

PubMed

Héroux, Mariane; Janssen, Ian; Lee, Duck-chul; Sui, Xuemei; Hebert, James R; Blair, Steven N

2012-04-01

Clustering of unhealthy behaviors has been reported in previous studies; however the link with all-cause mortality and differences between those with and without chronic disease requires further investigation. To observe the clustering effects of unhealthy diet, fitness, smoking, and excessive alcohol consumption in adults with and without chronic disease and to assess all-cause mortality risk according to the clustering of unhealthy behaviors. Participants were 13,621 adults (aged 20-84) from the Aerobics Center Longitudinal Study. Four health behaviors were observed (diet, fitness, smoking, and drinking). Baseline characteristics of the study population and bivariate relations between pairs of the health behaviors were evaluated separately for those with and without chronic disease using cross-tabulation and a chi-square test. The odds of partaking in unhealthy behaviors were also calculated. Latent class analysis (LCA) was used to assess clustering. Cox regression was used to assess the relationship between the behaviors and mortality. The four health behaviors were related to each other. LCA results suggested that two classes existed. Participants in class 1 had a higher probability of partaking in each of the four unhealthy behaviors than participants in class 2. No differences in health behavior clustering were found between participants with and without chronic disease. Mortality risk increased relative to the number of unhealthy behaviors participants engaged in. Unhealthy behaviors cluster together irrespective of chronic disease status. Such findings suggest that multi-behavioral intervention strategies can be similar in those with and without chronic disease.

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.

Empirically Derived Learning Disability Subtypes: A Replication Attempt and Longitudinal Patterns over 15 Years.

ERIC Educational Resources Information Center

Spreen, Otfried; Haaf, Robert G.

1986-01-01

Test scores of two groups of learning disabled children (N=63 and N=96) were submitted to cluster analysis in an attempt to replicate previously described subtypes. All three subtypes (visuo-perceptual, linguistic, and articulo-graphomotor types) were identified along with minimally and severely impaired subtypes. Similar clusters in the same…

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.

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

Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data

PubMed Central

Hu, Jianhua; Wang, Peng; Qu, Annie

2014-01-01

Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433

Explicating the Conditions Under Which Multilevel Multiple Imputation Mitigates Bias Resulting from Random Coefficient-Dependent Missing Longitudinal Data.

PubMed

Gottfredson, Nisha C; Sterba, Sonya K; Jackson, Kristina M

2017-01-01

Random coefficient-dependent (RCD) missingness is a non-ignorable mechanism through which missing data can arise in longitudinal designs. RCD, for which we cannot test, is a problematic form of missingness that occurs if subject-specific random effects correlate with propensity for missingness or dropout. Particularly when covariate missingness is a problem, investigators typically handle missing longitudinal data by using single-level multiple imputation procedures implemented with long-format data, which ignores within-person dependency entirely, or implemented with wide-format (i.e., multivariate) data, which ignores some aspects of within-person dependency. When either of these standard approaches to handling missing longitudinal data is used, RCD missingness leads to parameter bias and incorrect inference. We explain why multilevel multiple imputation (MMI) should alleviate bias induced by a RCD missing data mechanism under conditions that contribute to stronger determinacy of random coefficients. We evaluate our hypothesis with a simulation study. Three design factors are considered: intraclass correlation (ICC; ranging from .25 to .75), number of waves (ranging from 4 to 8), and percent of missing data (ranging from 20 to 50%). We find that MMI greatly outperforms the single-level wide-format (multivariate) method for imputation under a RCD mechanism. For the MMI analyses, bias was most alleviated when the ICC is high, there were more waves of data, and when there was less missing data. Practical recommendations for handling longitudinal missing data are suggested.

Matched Child Savings Accounts in Low-Resource Communities: Who Saves?

PubMed Central

Karimli, Leyla; Ssewamala, Fred M.; Neilands, Torsten B.; McKay, Mary McKernan

2015-01-01

This study examines variations in saving behavior among poor families enrolled in a Child Savings Account program for orphaned and vulnerable school-going children in Uganda. We employ multilevel analyses using longitudinal data from a cluster-randomized experimental design. Our analyses reveal the following significant results: (1) given the average number of months during which the account was open (18 months), families saved on average, USD 54.72, which, after being matched by the program (2:1 match rate) comes to USD 164.16—enough to cover approximately five academic terms of post-primary education; (2) children's saving behavior was not associated with quality of family relations; it was, however, significantly associated with family financial socialization; (3) family demographics were significantly associated with children's saving behavior in the matched Child Savings Account program; and (4) children enrolled in some schools saved better compared to children enrolled in other schools within the same treatment group. PMID:26636025

Network Ecology and Adolescent Social Structure

PubMed Central

McFarland, Daniel A.; Moody, James; Diehl, David; Smith, Jeffrey A.; Thomas, Reuben J.

2014-01-01

Adolescent societies—whether arising from weak, short-term classroom friendships or from close, long-term friendships—exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study), and by extending exponential random graph models to the study of multiple societies over time. PMID:25535409

Relationship between body image and breast self-examination intentions and behavior among female university students in Malaysia.

PubMed

Samah, Asnarulkhadi Abu; Ahmadian, Maryam

2014-01-01

This study aimed to examine the relationship between body image satisfaction and breast self-screening behavior and intentions. The sample for this cross-sectional study consisted of 842 female university students who were recruited from a number of public and private universities. Data were obtained between the months of November and December, 2013, using multistage random cluster sampling. Main research variables were breast cancer screening behavior and intentions, demographic factors, and the total scores on each of the Multidimensional Body-Self Relations Questionnaire (MBSRQ-Appearance Scales) subscales. Results of multivariate analysis showed that having higher satisfaction and more positive evaluation of appearance were related to having performed breast self-examination more frequently in the last year and intending to perform breast self-examination more frequently in the next year. Longitudinal research can potentially provide detailed information about overall body image satisfaction and breast cancer screening behavior among various communities.

Network Ecology and Adolescent Social Structure.

PubMed

McFarland, Daniel A; Moody, James; Diehl, David; Smith, Jeffrey A; Thomas, Reuben J

2014-12-01

Adolescent societies-whether arising from weak, short-term classroom friendships or from close, long-term friendships-exhibit various levels of network clustering, segregation, and hierarchy. Some are rank-ordered caste systems and others are flat, cliquish worlds. Explaining the source of such structural variation remains a challenge, however, because global network features are generally treated as the agglomeration of micro-level tie-formation mechanisms, namely balance, homophily, and dominance. How do the same micro-mechanisms generate significant variation in global network structures? To answer this question we propose and test a network ecological theory that specifies the ways features of organizational environments moderate the expression of tie-formation processes, thereby generating variability in global network structures across settings. We develop this argument using longitudinal friendship data on schools (Add Health study) and classrooms (Classroom Engagement study), and by extending exponential random graph models to the study of multiple societies over time.

Elevated incidence rates of diabetes in Peru: report from PERUDIAB, a national urban population-based longitudinal study

PubMed Central

Seclen, Segundo Nicolas; Rosas, Moises Ernesto; Arias, Arturo Jaime; Medina, Cecilia Alexandra

2017-01-01

Objective A recent report from a non-nationally representative, geographically diverse sample in four separate communities in Peru suggests an unusually high diabetes incidence. We aimed to estimate the national diabetes incidence rate using PERUDIAB, a probabilistic, national urban population-based longitudinal study. Research design and methods 662 subjects without diabetes, selected by multistage, cluster, random sampling of households, representing the 24 administrative and the 3 (coast, highlands and jungle) natural regions across the country, from both sexes, aged 25+ years at baseline, enrolled in 2010–2012, were followed for 3.8 years. New diabetes cases were defined as fasting blood glucose ≥126 mg/dL or on medical diabetes treatment. Results There were 49 cases of diabetes in 2408 person-years follow-up. The weighted cumulative incidence of diabetes was 7.2% while the weighted incidence rate was estimated at 19.5 (95% CI 13.9 to 28.3) new cases per 1000 person-years. Older age, obesity and technical or higher education were statistically associated with the incidence of diabetes. Conclusion Our results confirm that the incidence of diabetes in Peru is among the highest reported globally. The fast economic growth in the last 20 years, high overweight and obesity rates may have triggered this phenomenon. PMID:28878935

Elevated incidence rates of diabetes in Peru: report from PERUDIAB, a national urban population-based longitudinal study.

PubMed

Seclen, Segundo Nicolas; Rosas, Moises Ernesto; Arias, Arturo Jaime; Medina, Cecilia Alexandra

2017-01-01

A recent report from a non-nationally representative, geographically diverse sample in four separate communities in Peru suggests an unusually high diabetes incidence. We aimed to estimate the national diabetes incidence rate using PERUDIAB, a probabilistic, national urban population-based longitudinal study. 662 subjects without diabetes, selected by multistage, cluster, random sampling of households, representing the 24 administrative and the 3 (coast, highlands and jungle) natural regions across the country, from both sexes, aged 25+ years at baseline, enrolled in 2010-2012, were followed for 3.8 years. New diabetes cases were defined as fasting blood glucose ≥126 mg/dL or on medical diabetes treatment. There were 49 cases of diabetes in 2408 person-years follow-up. The weighted cumulative incidence of diabetes was 7.2% while the weighted incidence rate was estimated at 19.5 (95% CI 13.9 to 28.3) new cases per 1000 person-years. Older age, obesity and technical or higher education were statistically associated with the incidence of diabetes. Our results confirm that the incidence of diabetes in Peru is among the highest reported globally. The fast economic growth in the last 20 years, high overweight and obesity rates may have triggered this phenomenon.

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

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

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.…

The economics of dementia-care mapping in nursing homes: a cluster-randomised controlled trial.

PubMed

van de Ven, Geertje; Draskovic, Irena; van Herpen, Elke; Koopmans, Raymond T C M; Donders, Rogier; Zuidema, Sytse U; Adang, Eddy M M; Vernooij-Dassen, Myrra J F J

2014-01-01

Dementia-care mapping (DCM) is a cyclic intervention aiming at reducing neuropsychiatric symptoms in people with dementia in nursing homes. Alongside an 18-month cluster-randomized controlled trial in which we studied the effectiveness of DCM on residents and staff outcomes, we investigated differences in costs of care between DCM and usual care in nursing homes. Dementia special care units were randomly assigned to DCM or usual care. Nurses from the intervention care homes received DCM training, a DCM organizational briefing day and conducted the 4-months DCM-intervention twice during the study. A single DCM cycle consists of observation, feedback to the staff, and action plans for the residents. We measured costs related to health care consumption, falls and psychotropic drug use at the resident level and absenteeism at the staff level. Data were extracted from resident files and the nursing home records. Prizes were determined using the Dutch manual of health care cost and the cost prices delivered by a pharmacy and a nursing home. Total costs were evaluated by means of linear mixed-effect models for longitudinal data, with the unit as a random effect to correct for dependencies within units. 34 units from 11 nursing homes, including 318 residents and 376 nursing staff members participated in the cost analyses. Analyses showed no difference in total costs. However certain changes within costs could be noticed. The intervention group showed lower costs associated with outpatient hospital appointments over time (p = 0.05) than the control group. In both groups, the number of falls, costs associated with the elderly-care physician and nurse practitioner increased equally during the study (p<0.02). DCM is a cost-neutral intervention. It effectively reduces outpatient hospital appointments compared to usual care. Other considerations than costs, such as nursing homes' preferences, may determine whether they adopt the DCM method. Dutch Trials Registry NTR2314.

Randomized Trial of Two Dissemination Strategies for a Skin Cancer Prevention Program in Aquatic Settings

PubMed Central

Escoffery, Cam; Elliott, Tom; Nehl, Eric J.

2015-01-01

Objectives. We compared 2 strategies for disseminating an evidence-based skin cancer prevention program. Methods. We evaluated the effects of 2 strategies (basic vs enhanced) for dissemination of the Pool Cool skin cancer prevention program in outdoor swimming pools on (1) program implementation, maintenance, and sustainability and (2) improvements in organizational and environmental supports for sun protection. The trial used a cluster-randomized design with pools as the unit of intervention and outcome. The enhanced group received extra incentives, reinforcement, feedback, and skill-building guidance. Surveys were collected in successive years (2003–2006) from managers of 435 pools in 33 metropolitan areas across the United States participating in the Pool Cool Diffusion Trial. Results. Both treatment groups improved their implementation of the program, but pools in the enhanced condition had significantly greater overall maintenance of the program over 3 summers of participation. Furthermore, pools in the enhanced condition established and maintained significantly greater sun-safety policies and supportive environments over time. Conclusions. This study found that more intensive, theory-driven dissemination strategies can significantly enhance program implementation and maintenance of health-promoting environmental and policy changes. Future research is warranted through longitudinal follow-up to examine sustainability. PMID:25521872

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.

Study design of a cluster-randomized controlled trial to evaluate a large-scale distribution of cook stoves and water filters in Western Province, Rwanda.

PubMed

Nagel, Corey L; Kirby, Miles A; Zambrano, Laura D; Rosa, Ghislane; Barstow, Christina K; Thomas, Evan A; Clasen, Thomas F

2016-12-15

In Rwanda, pneumonia and diarrhea are the first and second leading causes of death, respectively, among children under five. Household air pollution (HAP) resultant from cooking indoors with biomass fuels on traditional stoves is a significant risk factor for pneumonia, while consumption of contaminated drinking water is a primary cause of diarrheal disease. To date, there have been no large-scale effectiveness trials of programmatic efforts to provide either improved cookstoves or household water filters at scale in a low-income country. In this paper we describe the design of a cluster-randomized trial to evaluate the impact of a national-level program to distribute and promote the use of improved cookstoves and advanced water filters to the poorest quarter of households in Rwanda. We randomly allocated 72 sectors (administratively defined units) in Western Province to the intervention, with the remaining 24 sectors in the province serving as controls. In the intervention sectors, roughly 100,000 households received improved cookstoves and household water filters through a government-sponsored program targeting the poorest quarter of households nationally. The primary outcome measures are the incidence of acute respiratory infection (ARI) and diarrhea among children under five years of age. Over a one-year surveillance period, all cases of acute respiratory infection (ARI) and diarrhea identified by health workers in the study area will be extracted from records maintained at health facilities and by community health workers (CHW). In addition, we are conducting intensive, longitudinal data collection among a random sample of households in the study area for in-depth assessment of coverage, use, environmental exposures, and additional health measures. Although previous research has examined the impact of providing household water treatment and improved cookstoves on child health, there have been no studies of national-level programs to deliver these interventions at scale in a developing country. The results of this study, the first RCT of a large-scale programmatic cookstove or household water filter intervention, will inform global efforts to reduce childhood morbidity and mortality from diarrheal disease and pneumonia. This trial is registered at Clinicaltrials.gov (NCT02239250).

Critical behavior of a quantum chain with four-spin interactions in the presence of longitudinal and transverse magnetic fields.

PubMed

Boechat, B; Florencio, J; Saguia, A; de Alcantara Bonfim, O F

2014-03-01

We study the ground-state properties of a spin-1/2 model on a chain containing four-spin Ising-like interactions in the presence of both transverse and longitudinal magnetic fields. We use entanglement entropy and finite-size scaling methods to obtain the phase diagrams of the model. Our numerical calculations reveal a rich variety of phases and the existence of multicritical points in the system. We identify phases with both ferromagnetic and antiferromagnetic orderings. We also find periodically modulated orderings formed by a cluster of like spins followed by another cluster of opposite like spins. The quantum phases in the model are found to be separated by either first- or second-order transition lines.

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.

Human comfort response to dominant random motions in longitudinal modes of aircraft motion

NASA Technical Reports Server (NTRS)

Stone, R. W., Jr.

1980-01-01

The effects of random vertical and longitudinal accelerations and pitching velocity passenger ride comfort responses were examined on the NASA Langley Visual Motion Simulator. Effects of power spectral density shape were studied for motions where the peak was between 0 and 2 Hz. The subjective rating data and the physical motion data obtained are presented without interpretation or detailed analysis. There existed motions in all other degrees of freedom as well as the particular pair of longitudinal airplane motions studied. These unwanted motions, caused by the characteristics of the simulator may have introduced some interactive effects on passenger responses.

Consonant Cluster Production in Children with Cochlear Implants: A Comparison with Normally Hearing Peers

ERIC Educational Resources Information Center

Faes, Jolien; Gillis, Steven

2017-01-01

In early word productions, the same types of errors are manifest in children with cochlear implants (CI) as in their normally hearing (NH) peers with respect to consonant clusters. However, the incidence of those types and their longitudinal development have not been examined or quantified in the literature thus far. Furthermore, studies on the…

Mixed models approaches for joint modeling of different types of responses.

PubMed

Ivanova, Anna; Molenberghs, Geert; Verbeke, Geert

2016-01-01

In many biomedical studies, one jointly collects longitudinal continuous, binary, and survival outcomes, possibly with some observations missing. Random-effects models, sometimes called shared-parameter models or frailty models, received a lot of attention. In such models, the corresponding variance components can be employed to capture the association between the various sequences. In some cases, random effects are considered common to various sequences, perhaps up to a scaling factor; in others, there are different but correlated random effects. Even though a variety of data types has been considered in the literature, less attention has been devoted to ordinal data. For univariate longitudinal or hierarchical data, the proportional odds mixed model (POMM) is an instance of the generalized linear mixed model (GLMM; Breslow and Clayton, 1993). Ordinal data are conveniently replaced by a parsimonious set of dummies, which in the longitudinal setting leads to a repeated set of dummies. When ordinal longitudinal data are part of a joint model, the complexity increases further. This is the setting considered in this paper. We formulate a random-effects based model that, in addition, allows for overdispersion. Using two case studies, it is shown that the combination of random effects to capture association with further correction for overdispersion can improve the model's fit considerably and that the resulting models allow to answer research questions that could not be addressed otherwise. Parameters can be estimated in a fairly straightforward way, using the SAS procedure NLMIXED.

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.

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.

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.

Longitudinal changes in physical activity, sedentary behavior and body mass index in adolescence: Migrations towards different weight cluster.

PubMed

Devís-Devís, José; Lizandra, Jorge; Valencia-Peris, Alexandra; Pérez-Gimeno, Esther; García-Massò, Xavier; Peiró-Velert, Carmen

2017-01-01

This study examined longitudinal changes in physical activity, sedentary behavior and body mass index in adolescents, specifically their migrations towards a different weight cluster. A cohort of 755 adolescents participated in a three-year study. A clustering Self-Organized Maps Analysis was performed to visualize changes in subjects' characteristics between the first and second assessment, and how adolescents were grouped. Also a classification tree was used to identify the behavioral characteristics of the groups that changed their weight cluster. Results indicated that boys were more active and less sedentary than girls. Boys were especially keen to technological-based activities while girls preferred social-based activities. A moderate competing effect between sedentary behaviors and physical activities was observed, especially in girls. Overweight and obesity were negatively associated with physical activity, although a small group of overweight/obese adolescents showed a positive relationship with vigorous physical activity. Cluster migrations indicated that 22.66% of adolescents changed their weight cluster to a lower category and none of them moved in the opposite direction. The behavioral characteristics of these adolescents did not support the hypothesis that the change to a lower weight cluster was a consequence of an increase in time devoted to physical activity or a decrease in time spent on sedentary behavior. Physical activity and sedentary behavior does not exert a substantial effect on overweight and obesity. Therefore, there are other ways of changing to a lower-weight status in adolescents apart from those in which physical activity and sedentary behavior are involved.

Longitudinal changes in physical activity, sedentary behavior and body mass index in adolescence: Migrations towards different weight cluster

PubMed Central

Lizandra, Jorge; Valencia-Peris, Alexandra; Pérez-Gimeno, Esther; García-Massò, Xavier; Peiró-Velert, Carmen

2017-01-01

This study examined longitudinal changes in physical activity, sedentary behavior and body mass index in adolescents, specifically their migrations towards a different weight cluster. A cohort of 755 adolescents participated in a three-year study. A clustering Self-Organized Maps Analysis was performed to visualize changes in subjects’ characteristics between the first and second assessment, and how adolescents were grouped. Also a classification tree was used to identify the behavioral characteristics of the groups that changed their weight cluster. Results indicated that boys were more active and less sedentary than girls. Boys were especially keen to technological-based activities while girls preferred social-based activities. A moderate competing effect between sedentary behaviors and physical activities was observed, especially in girls. Overweight and obesity were negatively associated with physical activity, although a small group of overweight/obese adolescents showed a positive relationship with vigorous physical activity. Cluster migrations indicated that 22.66% of adolescents changed their weight cluster to a lower category and none of them moved in the opposite direction. The behavioral characteristics of these adolescents did not support the hypothesis that the change to a lower weight cluster was a consequence of an increase in time devoted to physical activity or a decrease in time spent on sedentary behavior. Physical activity and sedentary behavior does not exert a substantial effect on overweight and obesity. Therefore, there are other ways of changing to a lower-weight status in adolescents apart from those in which physical activity and sedentary behavior are involved. PMID:28636644

An in-depth look into PTSD-depression comorbidity: A longitudinal study of chronically-exposed Detroit residents.

PubMed

Horesh, Danny; Lowe, Sarah R; Galea, Sandro; Aiello, Allison E; Uddin, Monica; Koenen, Karestan C

2017-01-15

Although PTSD-major depressive disorder (MDD) co-morbidity is well-established, the vast majority of studies have examined comorbidity at the level of PTSD total severity, rather than at the level of specific PTSD symptom clusters. This study aimed to examine the long-term associations between MDD and PTSD symptom clusters (intrusion, avoidance, hyperarousal), and the moderating role of gender in these associations. 942 residents of urban Detroit neighborhoods were interviewed at 3 waves, 1 year apart. At each wave, they were assessed for PTSD, depression, trauma exposure, and stressful life events. At all waves, hyperarousal was the PTSD cluster most strongly correlated with MDD. For the full sample, a reciprocal relationship was found between MDD and all three PTSD clusters across time. Interestingly, the relative strength of associations between MDD and specific PTSD clusters changed over time. Women showed the same bidirectional MDD-PTSD pattern as in the entire sample, while men sometimes showed non-significant associations between early MDD and subsequent PTSD clusters. First, our analyses are based on DSM-IV criteria, as this was the existing edition at the time of this study. Second, although this is a longitudinal study, inferences regarding temporal precedence of one disorder over another must be made with caution. Early identification of either PTSD or MDD following trauma may be crucial in order to prevent the development of the other disorder over time. The PTSD cluster of hyper-arousal may require special therapeutic attention. Also, professionals are encouraged to develop more gender-specific interventions post-trauma. Copyright © 2016 Elsevier B.V. All rights reserved.

Marginal and Random Intercepts Models for Longitudinal Binary Data With Examples From Criminology.

PubMed

Long, Jeffrey D; Loeber, Rolf; Farrington, David P

2009-01-01

Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides individual-level information including information about heterogeneity of growth. It is shown how a type of numerical averaging can be used with the random intercepts model to obtain group-level information, thus approximating individual and marginal aspects of the LMM. The types of inferences associated with each model are illustrated with longitudinal criminal offending data based on N = 506 males followed over a 22-year period. Violent offending indexed by official records and self-report were analyzed, with the marginal model estimated using generalized estimating equations and the random intercepts model estimated using maximum likelihood. The results show that the numerical averaging based on the random intercepts can produce prediction curves almost identical to those obtained directly from the marginal model parameter estimates. The results provide a basis for contrasting the models and the estimation procedures and key features are discussed to aid in selecting a method for empirical analysis.

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 estimation of branching curves in the presence of subject-specific random effects.

PubMed

Elmi, Angelo; Ratcliffe, Sarah J; Guo, Wensheng

2014-12-20

Branching curves are a technique for modeling curves that change trajectory at a change (branching) point. Currently, the estimation framework is limited to independent data, and smoothing splines are used for estimation. This article aims to extend the branching curve framework to the longitudinal data setting where the branching point varies by subject. If the branching point is modeled as a random effect, then the longitudinal branching curve framework is a semiparametric nonlinear mixed effects model. Given existing issues with using random effects within a smoothing spline, we express the model as a B-spline based semiparametric nonlinear mixed effects model. Simple, clever smoothness constraints are enforced on the B-splines at the change point. The method is applied to Women's Health data where we model the shape of the labor curve (cervical dilation measured longitudinally) before and after treatment with oxytocin (a labor stimulant). Copyright © 2014 John Wiley & Sons, Ltd.

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.

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.

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

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 Longitudinal Investigation of the Relationship between Posttraumatic Stress Symptoms and Posttraumatic Growth in a Cohort of Israeli Jews and Palestinians during Ongoing Violence

PubMed Central

Hall, Brian J.; Saltzman, Leia Y.; Canetti, Daphna; Hobfoll, Stevan E.

2015-01-01

Objectives Meta-analytic evidence based on cross-sectional investigations between posttraumatic growth (PTG) and posttraumatic stress disorder (PTSD) demonstrates that the two concepts are positively related and that ethnic minorities report greater PTG. Few longitudinal studies have quantified this relationship so the evidence is limited regarding the potential benefit PTG may have on post-traumatic adjustment and whether differences between ethnic groups exist. Methods The current study attempts to fill a substantial gap in the literature by exploring the relationship between PTG and PTSD symptom clusters longitudinally using a nationally representative cohort of 1613 Israelis and Palestinian Citizens of Israel (PCI) interviewed via telephone on three measurement occasions during one year. Latent cross-lagged structural models estimated the relationship between PTG and each PTSD symptom cluster, derived from confirmatory factor analysis, representing latent and statistically invariant PTSD symptom factors, best representing PTSD for both ethnic groups. Results PTG was not associated with less PTSD symptom severity in any of the four PTSD clusters, for Jews and PCI. In contrast, PTSD symptom severity assessed earlier was related to later reported PTG in both groups. Conclusions This study demonstrates that PTSD symptoms contribute to greater reported PTG, but that PTG does not provide a salutatory benefit by reducing symptoms of PTSD. PMID:25910043

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.

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…

An Ecological Analysis of the Effects of Deviant Peer Clustering on Sexual Promiscuity, Problem Behavior, and Childbearing from Early Adolescence to Adulthood: An Enhancement of the Life History Framework

PubMed Central

Dishion, Thomas J.; Ha, Thao; Véronneau, Marie-Hélène

2012-01-01

This study proposes the inclusion of peer relationships in a life history perspective on adolescent problem behavior. Longitudinal analyses were used to examine deviant peer clustering as the mediating link between attenuated family ties, peer marginalization, and social disadvantage in early adolescence and sexual promiscuity in middle adolescence and childbearing by early adulthood. Specifically, 998 youth and their families were assessed at age 11 years and periodically through age 24 years. Structural equation modeling revealed that the peer-enhanced life history model provided a good fit to the longitudinal data, with deviant peer clustering strongly predicting adolescent sexual promiscuity and other correlated problem behaviors. Sexual promiscuity, as expected, also strongly predicted the number of children by age 22–24 years. Consistent with a life history perspective, family social disadvantage directly predicted deviant peer clustering and number of children in early adulthood, controlling for all other variables in the model. These data suggest that deviant peer clustering is a core dimension of a fast life history strategy, with strong links to sexual activity and childbearing. The implications of these findings are discussed with respect to the need to integrate an evolutionary-based model of self-organized peer groups in developmental and intervention science. PMID:22409765

An ecological analysis of the effects of deviant peer clustering on sexual promiscuity, problem behavior, and childbearing from early adolescence to adulthood: an enhancement of the life history framework.

PubMed

Dishion, Thomas J; Ha, Thao; Véronneau, Marie-Hélène

2012-05-01

The authors propose that peer relationships should be included in a life history perspective on adolescent problem behavior. Longitudinal analyses were used to examine deviant peer clustering as the mediating link between attenuated family ties, peer marginalization, and social disadvantage in early adolescence and sexual promiscuity in middle adolescence and childbearing by early adulthood. Specifically, 998 youths, along with their families, were assessed at age 11 years and periodically through age 24 years. Structural equation modeling revealed that the peer-enhanced life history model provided a good fit to the longitudinal data, with deviant peer clustering strongly predicting adolescent sexual promiscuity and other correlated problem behaviors. Sexual promiscuity, as expected, also strongly predicted the number of children by ages 22-24 years. Consistent with a life history perspective, family social disadvantage directly predicted deviant peer clustering and number of children in early adulthood, controlling for all other variables in the model. These data suggest that deviant peer clustering is a core dimension of a fast life history strategy, with strong links to sexual activity and childbearing. The implications of these findings are discussed with respect to the need to integrate an evolutionary-based model of self-organized peer groups in developmental and intervention science.

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.

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.

Clustering of Magnetic Swimmers in a Poiseuille Flow

NASA Astrophysics Data System (ADS)

Meng, Fanlong; Matsunaga, Daiki; Golestanian, Ramin

2018-05-01

We investigate the collective behavior of magnetic swimmers, which are suspended in a Poiseuille flow and placed under an external magnetic field, using analytical techniques and Brownian dynamics simulations. We find that the interplay between intrinsic activity, external alignment, and magnetic dipole-dipole interactions leads to longitudinal structure formation. Our work sheds light on a recent experimental observation of a clustering instability in this system.

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.

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…

Left hemisphere fractional anisotropy increase in noise-induced tinnitus: a diffusion tensor imaging (DTI) study of white matter tracts in the brain.

PubMed

Benson, Randall R; Gattu, Ramtilak; Cacace, Anthony T

2014-03-01

Diffusion tensor imaging (DTI) is a contemporary neuroimaging modality used to study connectivity patterns and microstructure of white matter tracts in the brain. The use of DTI in the study of tinnitus is a relatively unexplored methodology with no studies focusing specifically on tinnitus induced by noise exposure. In this investigation, participants were two groups of adults matched for etiology, age, and degree of peripheral hearing loss, but differed by the presence or absence (+/-) of tinnitus. It is assumed that matching individuals on the basis of peripheral hearing loss, allows for differentiating changes in white matter microstructure due to hearing loss from changes due to the effects of chronic tinnitus. Alterations in white matter tracts, using the fractional anisotropy (FA) metric, which measures directional diffusion of water, were quantified using tract-based spatial statistics (TBSS) with additional details provided by in vivo probabilistic tractography. Our results indicate that 10 voxel clusters differentiated the two groups, including 9 with higher FA in the group with tinnitus. A decrease in FA was found for a single cluster in the group with tinnitus. However, seven of the 9 clusters with higher FA were in left hemisphere thalamic, frontal, and parietal white matter. These foci were localized to the anterior thalamic radiations and the inferior and superior longitudinal fasciculi. The two right-sided clusters with increased FA were located in the inferior fronto-occipital fasciculus and superior longitudinal fasciculus. The only decrease in FA for the tinnitus-positive group was found in the superior longitudinal fasciculus of the left parietal lobe. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatial cluster detection for repeatedly measured outcomes while accounting for residential history.

PubMed

Cook, Andrea J; Gold, Diane R; Li, Yi

2009-10-01

Spatial cluster detection has become an important methodology in quantifying the effect of hazardous exposures. Previous methods have focused on cross-sectional outcomes that are binary or continuous. There are virtually no spatial cluster detection methods proposed for longitudinal outcomes. This paper proposes a new spatial cluster detection method for repeated outcomes using cumulative geographic residuals. A major advantage of this method is its ability to readily incorporate information on study participants relocation, which most cluster detection statistics cannot. Application of these methods will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between environmental exposures and repeated measured outcome, occurrence of wheeze in the last 6 months, while taking into account mobile locations.

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.

Analysis of baseline, average, and longitudinally measured blood pressure data using linear mixed models.

PubMed

Hossain, Ahmed; Beyene, Joseph

2014-01-01

This article compares baseline, average, and longitudinal data analysis methods for identifying genetic variants in genome-wide association study using the Genetic Analysis Workshop 18 data. We apply methods that include (a) linear mixed models with baseline measures, (b) random intercept linear mixed models with mean measures outcome, and (c) random intercept linear mixed models with longitudinal measurements. In the linear mixed models, covariates are included as fixed effects, whereas relatedness among individuals is incorporated as the variance-covariance structure of the random effect for the individuals. The overall strategy of applying linear mixed models decorrelate the data is based on Aulchenko et al.'s GRAMMAR. By analyzing systolic and diastolic blood pressure, which are used separately as outcomes, we compare the 3 methods in identifying a known genetic variant that is associated with blood pressure from chromosome 3 and simulated phenotype data. We also analyze the real phenotype data to illustrate the methods. We conclude that the linear mixed model with longitudinal measurements of diastolic blood pressure is the most accurate at identifying the known single-nucleotide polymorphism among the methods, but linear mixed models with baseline measures perform best with systolic blood pressure as the outcome.

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.

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.

Reporting and methodological quality of sample size calculations in cluster randomized trials could be improved: a review.

PubMed

Rutterford, Clare; Taljaard, Monica; Dixon, Stephanie; Copas, Andrew; Eldridge, Sandra

2015-06-01

To assess the quality of reporting and accuracy of a priori estimates used in sample size calculations for cluster randomized trials (CRTs). We reviewed 300 CRTs published between 2000 and 2008. The prevalence of reporting sample size elements from the 2004 CONSORT recommendations was evaluated and a priori estimates compared with those observed in the trial. Of the 300 trials, 166 (55%) reported a sample size calculation. Only 36 of 166 (22%) reported all recommended descriptive elements. Elements specific to CRTs were the worst reported: a measure of within-cluster correlation was specified in only 58 of 166 (35%). Only 18 of 166 articles (11%) reported both a priori and observed within-cluster correlation values. Except in two cases, observed within-cluster correlation values were either close to or less than a priori values. Even with the CONSORT extension for cluster randomization, the reporting of sample size elements specific to these trials remains below that necessary for transparent reporting. Journal editors and peer reviewers should implement stricter requirements for authors to follow CONSORT recommendations. Authors should report observed and a priori within-cluster correlation values to enable comparisons between these over a wider range of trials. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

[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.

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

10B+α states with chain-like structures in 14N

NASA Astrophysics Data System (ADS)

Kanada-En'yo, Yoshiko

2015-12-01

I investigate 10B+α -cluster states of 14N with a 10B+α -cluster model. Near the α -decay threshold energy, I obtain Kπ=3+ and Kπ=1+ rotational bands having 10B(3+) +α and 10B(1+) +α components, respectively. I assign the bandhead state of the Kπ=3+ band to the experimental 3+ at Ex=13.19 MeV of 14N observed in α scattering reactions by 10B and show that the calculated α -decay width is consistent with the experimental data. I discuss an α -cluster motion around the 10B cluster and show that the Kπ=3+ and Kπ=1+ rotational bands contain an enhanced component of a linear-chain 3 α configuration, in which an α cluster is localized in the longitudinal direction around the deformed 10B cluster.

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…

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.…

An Ecological Analysis of the Effects of Deviant Peer Clustering on Sexual Promiscuity, Problem Behavior, and Childbearing from Early Adolescence to Adulthood: An Enhancement of the Life History Framework

ERIC Educational Resources Information Center

Dishion, Thomas J.; Ha, Thao; Veronneau, Marie-Helene

2012-01-01

The authors propose that peer relationships should be included in a life history perspective on adolescent problem behavior. Longitudinal analyses were used to examine deviant peer clustering as the mediating link between attenuated family ties, peer marginalization, and social disadvantage in early adolescence and sexual promiscuity in middle…

Cluster shell model: I. Structure of 9Be, 9B

NASA Astrophysics Data System (ADS)

Della Rocca, V.; Iachello, F.

2018-05-01

We calculate energy spectra, electromagnetic transition rates, longitudinal and transverse electron scattering form factors and log ft values for beta decay in 9Be, 9B, within the framework of a cluster shell model. By comparing with experimental data, we find strong evidence for the structure of these nuclei to be two α-particles in a dumbbell configuration with Z2 symmetry, plus an additional nucleon.

A New MI-Based Visualization Aided Validation Index for Mining Big Longitudinal Web Trial Data

PubMed Central

Zhang, Zhaoyang; Fang, Hua; Wang, Honggang

2016-01-01

Web-delivered clinical trials generate big complex data. To help untangle the heterogeneity of treatment effects, unsupervised learning methods have been widely applied. However, identifying valid patterns is a priority but challenging issue for these methods. This paper, built upon our previous research on multiple imputation (MI)-based fuzzy clustering and validation, proposes a new MI-based Visualization-aided validation index (MIVOOS) to determine the optimal number of clusters for big incomplete longitudinal Web-trial data with inflated zeros. Different from a recently developed fuzzy clustering validation index, MIVOOS uses a more suitable overlap and separation measures for Web-trial data but does not depend on the choice of fuzzifiers as the widely used Xie and Beni (XB) index. Through optimizing the view angles of 3-D projections using Sammon mapping, the optimal 2-D projection-guided MIVOOS is obtained to better visualize and verify the patterns in conjunction with trajectory patterns. Compared with XB and VOS, our newly proposed MIVOOS shows its robustness in validating big Web-trial data under different missing data mechanisms using real and simulated Web-trial data. PMID:27482473

Conditional Monte Carlo randomization tests for regression models.

PubMed

Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

2014-08-15

We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

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

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.

A longitudinal study of feed contamination by European starling excreta in Ohio dairy farms (2007-2008).

PubMed

Medhanie, G A; Pearl, D L; McEwen, S A; Guerin, M T; Jardine, C M; Schrock, J; LeJeune, J T

2014-01-01

The objectives of this study were to understand the temporal pattern of contamination of cattle feed by starling excrement on dairy farms and to evaluate the temporal pattern in recovering Escherichia coli O157:H7 or Salmonella in relation to the absolute mass of excrement recovered. A longitudinal study was conducted on 15 dairy farms in Ohio from July 2007 to October 2008. One open-topped tray filled with bird feed was placed near a cattle feeding site; bird excrement from the tray was weighed monthly for 12 consecutive months. Linear regression models with a random intercept for farm were computed to examine the association between the absolute weight of excrement recovered each month or the farm-specific standard score for weight of excrement, and month or season. Exact logistic regression was used to determine whether an association between recovering E. coli O157:H7 or Salmonella was present and the amount of excrement recovered and season. A spatial scan statistic was used to test for evidence of space-time clustering of excrement, based on the standard score for the weight of the excrement, among our study farms. A total of 5 of 179 excrement samples (2.79%) were positive for E. coli O157:H7 and 2 (1.12%) were positive for Salmonella. A significantly higher level of contamination with excrement was observed during the winter. The odds of recovering a pathogen increased with the amount of excrement recovered and decreased if the excrement was collected in the winter. A spatio-temporal cluster of contamination with excrement was detected. These findings provide basic information for future quantitative microbial risk assessments concerning the role of starlings in spreading enteric pathogens on dairy farms. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

What do you do with success? The science of scaling up a health systems strengthening intervention in Ghana.

PubMed

Phillips, James F; Awoonor-Williams, John Koku; Bawah, Ayaga A; Nimako, Belinda Afriyie; Kanlisi, Nicholas S; Sheff, Mallory C; Asuming, Patrick O; Kyei, Pearl E; Biney, Adriana; Jackson, Elizabeth F

2018-06-22

The completion of an implementation research project typically signals the end of research. In contrast, the Ghana Health Service has embraced a continuous process of evidence-based programming, wherein each research episode is followed by action and a new program of research that monitors and guides the utilization of lessons learned. This paper reviews the objectives and design of the most recent phase in this process, known as a National Program for Strengthening the Implementation of the Community-based Health Planning and Services (CHPS) Initiative in Ghana (CHPS+). A mixed method evaluation strategy has been launched involving: i) baseline and endline randomized sample surveys with 247 clusters dispersed in 14 districts of the Northern and Volta Regions to assess the difference in difference effect of stepped wedge differential cluster exposure to CHPS+ activities on childhood survival, ii) a monitoring system to assess the association of changes in service system readiness with CHPS+ interventions, and iii) a program of qualitative systems appraisal to gauge stakeholder perceptions of systems problems, reactions to interventions, and perceptions of change. Integrated survey and monitoring data will permit multi-level longitudinal models of impact; longitudinal QSA data will provide data on the implementation process. A process of exchanges, team interaction, and catalytic financing has accelerated the expansion of community-based primary health care in Ghana's Upper East Region (UER). Using two Northern and two Volta Region districts, the UER systems learning concept will be transferred to counterpart districts where a program of team-based peer training will be instituted. A mixed method research system will be used to assess the impact of this transfer of innovation in collaboration with national and regional program management. This arrangement will generate embedded science that optimizes prospects that results will contribute to national CHPS reform policies and action.

The Role of Vitamin D in the Transcriptional Program of Human Pregnancy

PubMed Central

Al-Garawi, Amal; Carey, Vincent J.; Chhabra, Divya; Morrow, Jarrett; Lasky-Su, Jessica; Qiu, Weiliang; Laranjo, Nancy; Litonjua, Augusto A.; Weiss, Scott T.

2016-01-01

Background Patterns of gene expression of human pregnancy are poorly understood. In a trial of vitamin D supplementation in pregnant women, peripheral blood transcriptomes were measured longitudinally on 30 women and used to characterize gene co-expression networks. Objective Studies suggest that increased maternal Vitamin D levels may reduce the risk of asthma in early life, yet the underlying mechanisms have not been examined. In this study, we used a network-based approach to examine changes in gene expression profiles during the course of normal pregnancy and evaluated their association with maternal Vitamin D levels. Design The VDAART study is a randomized clinical trial of vitamin D supplementation in pregnancy for reduction of pediatric asthma risk. The trial enrolled 881 women at 10–18 weeks of gestation. Longitudinal gene expression measures were obtained on thirty pregnant women, using RNA isolated from peripheral blood samples obtained in the first and third trimesters. Differentially expressed genes were identified using significance of analysis of microarrays (SAM), and clustered using a weighted gene co-expression network analysis (WGCNA). Gene-set enrichment was performed to identify major biological pathways. Results Comparison of transcriptional profiles between first and third trimesters of pregnancy identified 5839 significantly differentially expressed genes (FDR<0.05). Weighted gene co-expression network analysis clustered these transcripts into 14 co-expression modules of which two showed significant correlation with maternal vitamin D levels. Pathway analysis of these two modules revealed genes enriched in immune defense pathways and extracellular matrix reorganization as well as genes enriched in notch signaling and transcription factor networks. Conclusion Our data show that gene expression profiles of healthy pregnant women change during the course of pregnancy and suggest that maternal Vitamin D levels influence transcriptional profiles. These alterations of the maternal transcriptome may contribute to fetal immune imprinting and reduce allergic sensitization in early life. Trial Registration clinicaltrials.gov NCT00920621 PMID:27711190

Transversely polarized source cladding for an optical fiber

NASA Technical Reports Server (NTRS)

Egalon, Claudio Oliveira (Inventor); Rogowski, Robert S. (Inventor)

1994-01-01

An optical fiber comprising a fiber core having a longitudinal symmetry axis is provided. An active cladding surrounds a portion of the fiber core and comprises light-producing sources which emit light in response to chemical or light excitation. The cladding sources are oriented transversely with respect to the longitudinal axis of the fiber core. This polarization results in a superior power efficiency compared to active cladding sources that are randomly polarized or longitudinally polarized parallel with the longitudinal symmetry axis.

Associations between the physical activity levels of fathers and their children at 20 months, 3.5 and five years of age.

PubMed

Walsh, Adam D; Crawford, David; Cameron, Adrian J; Campbell, Karen J; Hesketh, Kylie D

2017-07-05

Early childhood (under five years of age) is a critical developmental period when children's physical activity behaviours are shaped and when physical activity patterns begin to emerge. Physical activity levels track from early childhood through to adolescence with low levels of physical activity associated with poorer health. The aims of this study were to examine cross-sectional and longitudinal associations between the physical activity levels of fathers and their children at the ages of 20 months, 3.5 and 5 years, and to investigate whether these associations differed based on paternal body mass index (BMI) and education. The Melbourne Infant Feeding Activity and Nutrition Trial (InFANT) Program was a cluster randomized-controlled trial delivered to pre-existing first-time parent groups. Physical activity levels of fathers and their first-born children were assessed using the Active Australia Survey and ActiGraph accelerometers respectively. Cross-sectional associations between father and child physical activity behaviours were assessed at each time point. Longitudinal associations between father and child physical activity were also investigated from child age 20 months to both 3.5 and 5 years. Additional stratified analyses were conducted based on paternal BMI and paternal education as a proxy for socioeconomic position (SEP). Data from the control and interventions groups were pooled and all analyses adjusted for intervention status, clustering by first-time parent group and accelerometer wear time. Physical activity levels of fathers and their children at child age 20 months were not associated cross-sectionally or longitudinally at child age 3.5 and 5 years. Positive associations were observed between light physical activity of healthy weight fathers and children at age 3.5 years. Inverse associations were observed for moderate/vigorous physical activity between fathers and children at age 5 years, including between overweight/obese fathers and their children at this age in stratified analyses. There were no clear associations between the physical activity of fathers and children. Future research should include the use of more robust measures of physical activity among fathers to allow in-depth assessment of their physical activity behaviours. Investigation of well-defined correlates of physical activity in young children is warranted to confirm these findings and further progress research in this field.

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

PubMed

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

2016-01-01

Natural populations of plants and animals spatially cluster because (1) suitable habitat is patchy, and (2) within suitable habitat, individuals aggregate further into clusters of higher density. We compare the precision of random and systematic field sampling survey designs under these two processes of species clustering. Second, we evaluate the performance of 13 estimators for the variance of the sample mean from a systematic survey. Replicated simulated surveys, as counts from 100 transects, allocated either randomly or systematically within the study region, were used to estimate population density in six spatial point populations including habitat patches and Matérn circular clustered aggregations of organisms, together and in combination. The standard one-start aligned systematic survey design, a uniform 10 x 10 grid of transects, was much more precise. Variances of the 10 000 replicated systematic survey mean densities were one-third to one-fifth of those from randomly allocated transects, implying transect sample sizes giving equivalent precision by random survey would need to be three to five times larger. Organisms being restricted to patches of habitat was alone sufficient to yield this precision advantage for the systematic design. But this improved precision for systematic sampling in clustered populations is underestimated by standard variance estimators used to compute confidence intervals. True variance for the survey sample mean was computed from the variance of 10 000 simulated survey mean estimates. Testing 10 published and three newly proposed variance estimators, the two variance estimators (v) that corrected for inter-transect correlation (ν₈ and ν(W)) were the most accurate and also the most precise in clustered populations. These greatly outperformed the two "post-stratification" variance estimators (ν₂ and ν₃) that are now more commonly applied in systematic surveys. Similar variance estimator performance rankings were found with a second differently generated set of spatial point populations, ν₈ and ν(W) again being the best performers in the longer-range autocorrelated populations. However, no systematic variance estimators tested were free from bias. On balance, systematic designs bring more narrow confidence intervals in clustered populations, while random designs permit unbiased estimates of (often wider) confidence interval. The search continues for better estimators of sampling variance for the systematic survey mean.

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 ).

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

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

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.

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.

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.

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.

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.

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.

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.

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

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1976-01-01

The author has identified the following significant results. There is strong indication that spatially rare feature classes may be missed in clustering classifications based on 2% random sampling. Therefore, it seems advisable to augment random sampling for cluster analysis with directed sampling of any spatially rare features which are relevant to the analysis.

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…

Sampling designs for HIV molecular epidemiology with application to Honduras.

PubMed

Shepherd, Bryan E; Rossini, Anthony J; Soto, Ramon Jeremias; De Rivera, Ivette Lorenzana; Mullins, James I

2005-11-01

Proper sampling is essential to characterize the molecular epidemiology of human immunodeficiency virus (HIV). HIV sampling frames are difficult to identify, so most studies use convenience samples. We discuss statistically valid and feasible sampling techniques that overcome some of the potential for bias due to convenience sampling and ensure better representation of the study population. We employ a sampling design called stratified cluster sampling. This first divides the population into geographical and/or social strata. Within each stratum, a population of clusters is chosen from groups, locations, or facilities where HIV-positive individuals might be found. Some clusters are randomly selected within strata and individuals are randomly selected within clusters. Variation and cost help determine the number of clusters and the number of individuals within clusters that are to be sampled. We illustrate the approach through a study designed to survey the heterogeneity of subtype B strains in Honduras.

Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the 'Mean Duration of Recent Infection'.

PubMed

Kassanjee, Reshma; De Angelis, Daniela; Farah, Marian; Hanson, Debra; Labuschagne, Jan Phillipus Lourens; Laeyendecker, Oliver; Le Vu, Stéphane; Tom, Brian; Wang, Rui; Welte, Alex

2017-03-01

The application of biomarkers for 'recent' infection in cross-sectional HIV incidence surveillance requires the estimation of critical biomarker characteristics. Various approaches have been employed for using longitudinal data to estimate the Mean Duration of Recent Infection (MDRI) - the average time in the 'recent' state. In this systematic benchmarking of MDRI estimation approaches, a simulation platform was used to measure accuracy and precision of over twenty approaches, in thirty scenarios capturing various study designs, subject behaviors and test dynamics that may be encountered in practice. Results highlight that assuming a single continuous sojourn in the 'recent' state can produce substantial bias. Simple interpolation provides useful MDRI estimates provided subjects are tested at regular intervals. Regression performs the best - while 'random effects' describe the subject-clustering in the data, regression models without random effects proved easy to implement, stable, and of similar accuracy in scenarios considered; robustness to parametric assumptions was improved by regressing 'recent'/'non-recent' classifications rather than continuous biomarker readings. All approaches were vulnerable to incorrect assumptions about subjects' (unobserved) infection times. Results provided show the relationships between MDRI estimation performance and the number of subjects, inter-visit intervals, missed visits, loss to follow-up, and aspects of biomarker signal and noise.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the Northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

NASA Astrophysics Data System (ADS)

Savage, J. C.; Simpson, R. W.

2013-09-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Clustering of velocities in a GPS network spanning the Sierra Nevada Block, the northern Walker Lane Belt, and the Central Nevada Seismic Belt, California-Nevada

USGS Publications Warehouse

Savage, James C.; Simpson, Robert W.

2013-01-01

The deformation across the Sierra Nevada Block, the Walker Lane Belt, and the Central Nevada Seismic Belt (CNSB) between 38.5°N and 40.5°N has been analyzed by clustering GPS velocities to identify coherent blocks. Cluster analysis determines the number of clusters required and assigns the GPS stations to the proper clusters. The clusters are shown on a fault map by symbols located at the positions of the GPS stations, each symbol representing the cluster to which the velocity of that GPS station belongs. Fault systems that separate the clusters are readily identified on such a map. Four significant clusters are identified. Those clusters are strips separated by (from west to east) the Mohawk Valley-Genoa fault system, the Pyramid Lake-Wassuk fault system, and the Central Nevada Seismic Belt. The strain rates within the westernmost three clusters approximate simple right-lateral shear (~13 nstrain/a) across vertical planes roughly parallel to the cluster boundaries. Clustering does not recognize the longitudinal segmentation of the Walker Lane Belt into domains dominated by either northwesterly trending, right-lateral faults or northeasterly trending, left-lateral faults.

Beverage consumption patterns at age 13–17 are associated with weight, height, and BMI at age 17

PubMed Central

Marshall, Teresa A.; Van Buren, John M.; Warren, John J.; Cavanaugh, Joseph E.; Levy, Steven M.

2017-01-01

Background Sugar-sweetened beverages (SSBs) have been associated with obesity in children and adults; however, associations between beverage patterns and obesity are not understood. Objective To describe beverage patterns during adolescence, and the associations between adolescent beverage patterns and age 17 anthropometric measures. Design Cross-sectional analyses of longitudinally-collected data. Participants/setting Participants in the longitudinal Iowa Fluoride Study having at least one beverage questionnaire completed between ages 13.0 and 14.0 years, having a second questionnaire completed between 16.0 and 17.0 years and attending an age 17 clinic exam for weight and height measurements (n=369). Exposure Beverages were collapsed into 4 categories {i.e., 100% juice, milk, water and other sugar-free beverages (water/SFB), and SSBs} for the purpose of clustering. Five beverage clusters were identified from standardized age 13–17 mean daily beverage intakes and named by the authors for the dominant beverage: juice, milk, water/SFB, neutral and SSB. Outcome Age 17 weight, height and BMI. Statistical analyses Ward’s method for clustering of beverage variables. One-way ANOVA and chi-square tests for bivariable associations. Gamma regression for associations of weight or BMI (outcomes) with beverage clusters and demographic variables. Linear regression for associations of height (outcome) with beverage clusters and demographic variables. Results Participants with family incomes < $60,000 trended shorter (1.5±0.8 cm; P=0.070) and were heavier (2.0±0.7 BMI units; P=0.002) than participants with family incomes ≥ 60,000/year. Adjusted mean weight, height and BMI estimates differed by beverage cluster membership. For example, on average, male and female members of the neutral cluster were 4.5 cm (P=0.010) and 4.2 (P=0.034) cm shorter, respectively, than members of the milk cluster. For members of the juice cluster, the mean BMI was lower than for members of the milk cluster (by 2.4 units), water/SFB cluster (3.5 units), neutral cluster (2.2 units) and SSB cluster (3.2 units) (all Ps<0.05). Conclusions Age 13–17 year beverage patterns were associated with age 17 anthropometric measures and BMI in this sample. Beverage patterns might be characteristic of overall food choices and dietary behaviors that influence growth. PMID:28259744

Examining solutions to missing data in longitudinal nursing research.

PubMed

Roberts, Mary B; Sullivan, Mary C; Winchester, Suzy B

2017-04-01

Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study's purpose was to (1) introduce a three-step approach to assess and address missing data and (2) illustrate this approach using categorical and continuous-level variables from a longitudinal study of premature infants. A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification (FCS). Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and FCS. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. The rate of missingness was 16-23% for continuous variables and 1-28% for categorical variables. FCS imputation provided the least difference in mean and standard deviation estimates for continuous measures. FCS imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. © 2017 Wiley Periodicals, Inc.

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.

Accelerated longitudinal designs: An overview of modelling, power, costs and handling missing data.

PubMed

Galbraith, Sally; Bowden, Jack; Mander, Adrian

2017-02-01

Longitudinal studies are often used to investigate age-related developmental change. Whereas a single cohort design takes a group of individuals at the same initial age and follows them over time, an accelerated longitudinal design takes multiple single cohorts, each one starting at a different age. The main advantage of an accelerated longitudinal design is its ability to span the age range of interest in a shorter period of time than would be possible with a single cohort longitudinal design. This paper considers design issues for accelerated longitudinal studies. A linear mixed effect model is considered to describe the responses over age with random effects for intercept and slope parameters. Random and fixed cohort effects are used to cope with the potential bias accelerated longitudinal designs have due to multiple cohorts. The impact of other factors such as costs and the impact of dropouts on the power of testing or the precision of estimating parameters are examined. As duration-related costs increase relative to recruitment costs the best designs shift towards shorter duration and eventually cross-sectional design being best. For designs with the same duration but differing interval between measurements, we found there was a cutoff point for measurement costs relative to recruitment costs relating to frequency of measurements. Under our model of 30% dropout there was a maximum power loss of 7%.

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.

Zero-inflated count models for longitudinal measurements with heterogeneous random effects.

PubMed

Zhu, Huirong; Luo, Sheng; DeSantis, Stacia M

2017-08-01

Longitudinal zero-inflated count data arise frequently in substance use research when assessing the effects of behavioral and pharmacological interventions. Zero-inflated count models (e.g. zero-inflated Poisson or zero-inflated negative binomial) with random effects have been developed to analyze this type of data. In random effects zero-inflated count models, the random effects covariance matrix is typically assumed to be homogeneous (constant across subjects). However, in many situations this matrix may be heterogeneous (differ by measured covariates). In this paper, we extend zero-inflated count models to account for random effects heterogeneity by modeling their variance as a function of covariates. We show via simulation that ignoring intervention and covariate-specific heterogeneity can produce biased estimates of covariate and random effect estimates. Moreover, those biased estimates can be rectified by correctly modeling the random effects covariance structure. The methodological development is motivated by and applied to the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study, the largest clinical trial of alcohol dependence performed in United States with 1383 individuals.

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.

Evaluation of the procedure 1A component of the 1980 US/Canada wheat and barley exploratory experiment

NASA Technical Reports Server (NTRS)

Chapman, G. M. (Principal Investigator); Carnes, J. G.

1981-01-01

Several techniques which use clusters generated by a new clustering algorithm, CLASSY, are proposed as alternatives to random sampling to obtain greater precision in crop proportion estimation: (1) Proportional Allocation/relative count estimator (PA/RCE) uses proportional allocation of dots to clusters on the basis of cluster size and a relative count cluster level estimate; (2) Proportional Allocation/Bayes Estimator (PA/BE) uses proportional allocation of dots to clusters and a Bayesian cluster-level estimate; and (3) Bayes Sequential Allocation/Bayesian Estimator (BSA/BE) uses sequential allocation of dots to clusters and a Bayesian cluster level estimate. Clustering in an effective method in making proportion estimates. It is estimated that, to obtain the same precision with random sampling as obtained by the proportional sampling of 50 dots with an unbiased estimator, samples of 85 or 166 would need to be taken if dot sets with AI labels (integrated procedure) or ground truth labels, respectively were input. Dot reallocation provides dot sets that are unbiased. It is recommended that these proportion estimation techniques are maintained, particularly the PA/BE because it provides the greatest precision.

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.

Factors associated with nutritional status and dietary practices of Bangladeshi adolescents in early pregnancy.

PubMed

Mridha, Malay K; Matias, Susana L; Arnold, Charles D; Dewey, Kathryn G

2018-02-18

Bangladesh has a high prevalence of adolescent pregnancy, but little is known about the nutritional status and dietary practices of Bangladeshi adolescents in early pregnancy or associated factors. We used the baseline data of 1552 pregnant adolescents from a longitudinal, cluster-randomized effectiveness trial conducted in northwest Bangladesh. Forty-four percent of the adolescents were short for their age, 36% had low body mass index, 28% were anemic, 10% had iron deficiency, and 32% had vitamin A deficiency. The mean consumption of animal-source foods was 10.3 times/week. In multivariate analysis, socioeconomic status, education, and food security were generally positively associated with anthropometric indicators and dietary practices but not with iron or vitamin A status. Our findings confirm that there is a high burden of undernutrition among these Bangladeshi adolescents in early pregnancy. Understanding factors related to undernutrition can help to identify adolescent pregnant women at higher risk and provide appropriate counseling and care. © 2018 New York Academy of Sciences.

Social and Emotional Learning Services and Child Outcomes in Third Grade: Evidence from a Cohort of Head Start Participants.

PubMed

Zhai, Fuhua; Raver, C Cybele; Jones, Stephanie M

2015-09-01

A variety of universal school-based social and emotional learning (SEL) programs have been designed in the past decades to help children improve social-emotional and academic skills. Evidence on the effectiveness of SEL programs has been mixed in the literature. Using data from a longitudinal follow-up study of children (n = 414) originally enrolled in a clustered randomized controlled trial (RCT) when they were in Head Start, we examined whether universal SEL services in third grade were associated with the development of children from disadvantaged families. We took advantage of pairwise matching in the RCT design to compare children who had similar family background and preschool experiences but received different doses of SEL services in third grade. The results showed that the frequent (i.e., weekly to daily) exposure to SEL opportunities was associated with favorable social-emotional and academic development in third grade, including increased social skills, student-teacher relationship, and academic skills, as well as reduced impulsiveness.

Predictors for Physical Activity in Adolescent Girls Using Statistical Shrinkage Techniques for Hierarchical Longitudinal Mixed Effects Models

PubMed Central

Grant, Edward M.; Young, Deborah Rohm; Wu, Tong Tong

2015-01-01

We examined associations among longitudinal, multilevel variables and girls’ physical activity to determine the important predictors for physical activity change at different adolescent ages. The Trial of Activity for Adolescent Girls 2 study (Maryland) contributed participants from 8th (2009) to 11th grade (2011) (n=561). Questionnaires were used to obtain demographic, and psychosocial information (individual- and social-level variables); height, weight, and triceps skinfold to assess body composition; interviews and surveys for school-level data; and self-report for neighborhood-level variables. Moderate to vigorous physical activity minutes were assessed from accelerometers. A doubly regularized linear mixed effects model was used for the longitudinal multilevel data to identify the most important covariates for physical activity. Three fixed effects at the individual level and one random effect at the school level were chosen from an initial total of 66 variables, consisting of 47 fixed effects and 19 random effects variables, in additional to the time effect. Self-management strategies, perceived barriers, and social support from friends were the three selected fixed effects, and whether intramural or interscholastic programs were offered in middle school was the selected random effect. Psychosocial factors and friend support, plus a school’s physical activity environment, affect adolescent girl’s moderate to vigorous physical activity longitudinally. PMID:25928064

Observed intra-cluster correlation coefficients in a cluster survey sample of patient encounters in general practice in Australia

PubMed Central

Knox, Stephanie A; Chondros, Patty

2004-01-01

Background Cluster sample study designs are cost effective, however cluster samples violate the simple random sample assumption of independence of observations. Failure to account for the intra-cluster correlation of observations when sampling through clusters may lead to an under-powered study. Researchers therefore need estimates of intra-cluster correlation for a range of outcomes to calculate sample size. We report intra-cluster correlation coefficients observed within a large-scale cross-sectional study of general practice in Australia, where the general practitioner (GP) was the primary sampling unit and the patient encounter was the unit of inference. Methods Each year the Bettering the Evaluation and Care of Health (BEACH) study recruits a random sample of approximately 1,000 GPs across Australia. Each GP completes details of 100 consecutive patient encounters. Intra-cluster correlation coefficients were estimated for patient demographics, morbidity managed and treatments received. Intra-cluster correlation coefficients were estimated for descriptive outcomes and for associations between outcomes and predictors and were compared across two independent samples of GPs drawn three years apart. Results Between April 1999 and March 2000, a random sample of 1,047 Australian general practitioners recorded details of 104,700 patient encounters. Intra-cluster correlation coefficients for patient demographics ranged from 0.055 for patient sex to 0.451 for language spoken at home. Intra-cluster correlations for morbidity variables ranged from 0.005 for the management of eye problems to 0.059 for management of psychological problems. Intra-cluster correlation for the association between two variables was smaller than the descriptive intra-cluster correlation of each variable. When compared with the April 2002 to March 2003 sample (1,008 GPs) the estimated intra-cluster correlation coefficients were found to be consistent across samples. Conclusions The demonstrated precision and reliability of the estimated intra-cluster correlations indicate that these coefficients will be useful for calculating sample sizes in future general practice surveys that use the GP as the primary sampling unit. PMID:15613248

Modeling Achievement Trajectories when Attrition Is Informative

ERIC Educational Resources Information Center

Feldman, Betsy J.; Rabe-Hesketh, Sophia

2012-01-01

In longitudinal education studies, assuming that dropout and missing data occur completely at random is often unrealistic. When the probability of dropout depends on covariates and observed responses (called "missing at random" [MAR]), or on values of responses that are missing (called "informative" or "not missing at random" [NMAR]),…

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

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…

Capacity-building and clinical competence in infectious disease in Uganda: a mixed-design study with pre/post and cluster-randomized trial components.

PubMed

Weaver, Marcia R; Crozier, Ian; Eleku, Simon; Makanga, Gyaviira; Mpanga Sebuyira, Lydia; Nyakake, Janepher; Thompson, MaryLou; Willis, Kelly

2012-01-01

Best practices for training mid-level practitioners (MLPs) to improve global health-services are not well-characterized. Two hypotheses were: 1) Integrated Management of Infectious Disease (IMID) training would improve clinical competence as tested with a single arm, pre-post design, and 2) on-site support (OSS) would yield additional improvements as tested with a cluster-randomized trial. Thirty-six Ugandan health facilities (randomized 1∶1 to parallel OSS and control arms) enrolled two MLPs each. All MLPs participated in IMID (3-week core course, two 1-week boost sessions, distance learning). After the 3-week course, OSS-arm trainees participated in monthly OSS. Twelve written case scenarios tested clinical competencies in HIV/AIDS, tuberculosis, malaria, and other infectious diseases. Each participant completed different randomly-assigned blocks of four scenarios before IMID (t0), after 3-week course (t1), and after second boost course (t2, 24 weeks after t1). Scoring guides were harmonized with IMID content and Ugandan national policy. Score analyses used a linear mixed-effects model. The primary outcome measure was longitudinal change in scenario scores. Scores were available for 856 scenarios. Mean correct scores at t0, t1, and t2 were 39.3%, 49.1%, and 49.6%, respectively. Mean score increases (95% CI, p-value) for t0-t1 (pre-post period) and t1-t2 (parallel-arm period) were 12.1 ((9.6, 14.6), p<0.001) and -0.6 ((-3.1, +1.9), p = 0.647) percent for OSS arm and 7.5 ((5.0, 10.0), p<0.001) and 1.6 ((-1.0, +4.1), p = 0.225) for control arm. The estimated mean difference in t1 to t2 score change, comparing arm A (participated in OSS) vs. arm B was -2.2 ((-5.8, +1.4), p = 0.237). From t0-t2, mean scores increased for all 12 scenarios. Clinical competence increased significantly after a 3-week core course; improvement persisted for 24 weeks. No additional impact of OSS was observed. Data on clinical practice, facility-level performance and health outcomes will complete assessment of overall impact of IMID and OSS. ClinicalTrials.gov NCT01190540.

Systems analysis and improvement to optimize pMTCT (SAIA): a cluster randomized trial

PubMed Central

2014-01-01

Background Despite significant increases in global health investment and the availability of low-cost, efficacious interventions to prevent mother-to-child HIV transmission (pMTCT) in low- and middle-income countries with high HIV burden, the translation of scientific advances into effective delivery strategies has been slow, uneven and incomplete. As a result, pediatric HIV infection remains largely uncontrolled. A five-step, facility-level systems analysis and improvement intervention (SAIA) was designed to maximize effectiveness of pMTCT service provision by improving understanding of inefficiencies (step one: cascade analysis), guiding identification and prioritization of low-cost workflow modifications (step two: value stream mapping), and iteratively testing and redesigning these modifications (steps three through five). This protocol describes the SAIA intervention and methods to evaluate the intervention’s impact on reducing drop-offs along the pMTCT cascade. Methods This study employs a two-arm, longitudinal cluster randomized trial design. The unit of randomization is the health facility. A total of 90 facilities were identified in Côte d’Ivoire, Kenya and Mozambique (30 per country). A subset was randomly selected and assigned to intervention and comparison arms, stratified by country and service volume, resulting in 18 intervention and 18 comparison facilities across all three countries, with six intervention and six comparison facilities per country. The SAIA intervention will be implemented for six months in the 18 intervention facilities. Primary trial outcomes are designed to assess improvements in the pMTCT service cascade, and include the percentage of pregnant women being tested for HIV at the first antenatal care visit, the percentage of HIV-infected pregnant women receiving adequate prophylaxis or combination antiretroviral therapy in pregnancy, and the percentage of newborns exposed to HIV in pregnancy receiving an HIV diagnosis eight weeks postpartum. The Consolidated Framework for Implementation Research (CFIR) will guide collection and analysis of qualitative data on implementation process. Discussion This study is a pragmatic trial that has the potential benefit of improving maternal and infant outcomes by reducing drop-offs along the pMTCT cascade. The SAIA intervention is designed to provide simple tools to guide decision-making for pMTCT program staff at the facility level, and to identify low cost, contextually appropriate pMTCT improvement strategies. Trial registration ClinicalTrials.gov NCT02023658 PMID:24885976

Systems analysis and improvement to optimize pMTCT (SAIA): a cluster randomized trial.

PubMed

Sherr, Kenneth; Gimbel, Sarah; Rustagi, Alison; Nduati, Ruth; Cuembelo, Fatima; Farquhar, Carey; Wasserheit, Judith; Gloyd, Stephen

2014-05-08

Despite significant increases in global health investment and the availability of low-cost, efficacious interventions to prevent mother-to-child HIV transmission (pMTCT) in low- and middle-income countries with high HIV burden, the translation of scientific advances into effective delivery strategies has been slow, uneven and incomplete. As a result, pediatric HIV infection remains largely uncontrolled. A five-step, facility-level systems analysis and improvement intervention (SAIA) was designed to maximize effectiveness of pMTCT service provision by improving understanding of inefficiencies (step one: cascade analysis), guiding identification and prioritization of low-cost workflow modifications (step two: value stream mapping), and iteratively testing and redesigning these modifications (steps three through five). This protocol describes the SAIA intervention and methods to evaluate the intervention's impact on reducing drop-offs along the pMTCT cascade. This study employs a two-arm, longitudinal cluster randomized trial design. The unit of randomization is the health facility. A total of 90 facilities were identified in Côte d'Ivoire, Kenya and Mozambique (30 per country). A subset was randomly selected and assigned to intervention and comparison arms, stratified by country and service volume, resulting in 18 intervention and 18 comparison facilities across all three countries, with six intervention and six comparison facilities per country. The SAIA intervention will be implemented for six months in the 18 intervention facilities. Primary trial outcomes are designed to assess improvements in the pMTCT service cascade, and include the percentage of pregnant women being tested for HIV at the first antenatal care visit, the percentage of HIV-infected pregnant women receiving adequate prophylaxis or combination antiretroviral therapy in pregnancy, and the percentage of newborns exposed to HIV in pregnancy receiving an HIV diagnosis eight weeks postpartum. The Consolidated Framework for Implementation Research (CFIR) will guide collection and analysis of qualitative data on implementation process. This study is a pragmatic trial that has the potential benefit of improving maternal and infant outcomes by reducing drop-offs along the pMTCT cascade. The SAIA intervention is designed to provide simple tools to guide decision-making for pMTCT program staff at the facility level, and to identify low cost, contextually appropriate pMTCT improvement strategies. ClinicalTrials.gov NCT02023658.

Dietary patterns in the Avon Longitudinal Study of Parents and Children

PubMed Central

Jones, Louise R.; Northstone, Kate

2015-01-01

Publications from the Avon Longitudinal Study of Parents and Children that used empirically derived dietary patterns were reviewed. The relationships of dietary patterns with socioeconomic background and childhood development were examined. Diet was assessed using food frequency questionnaires and food records. Three statistical methods were used: principal components analysis, cluster analysis, and reduced rank regression. Throughout childhood, children and parents have similar dietary patterns. The “health-conscious” and “traditional” patterns were associated with high intakes of fruits and/or vegetables and better nutrient profiles than the “processed” patterns. There was evidence of tracking in childhood diet, with the “health-conscious” patterns tracking most strongly, followed by the “processed” pattern. An “energy-dense, low-fiber, high-fat” dietary pattern was extracted using reduced rank regression; high scores on this pattern were associated with increasing adiposity. Maternal education was a strong determinant of pattern score or cluster membership; low educational attainment was associated with higher scores on processed, energy-dense patterns in both parents and children. The Avon Longitudinal Study of Parents and Children has provided unique insights into the value of empirically derived dietary patterns and has demonstrated that they are a useful tool in nutritional epidemiology. PMID:26395343

Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes.

PubMed

King, Paula; Pham, Long K; Waltz, Shannon; Sphar, Dan; Yamamoto, Robert T; Conrad, Douglas; Taplitz, Randy; Torriani, Francesca; Forsyth, R Allyn

2016-01-01

We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.

Fruit and vegetable consumption and sports participation among UK Youth.

PubMed

McAloney, Kareena; Graham, Hilary; Law, Catherine; Platt, Lucinda; Wardle, Heather; Hall, Julia

2014-02-01

UK guidelines for youth recommend daily physical activity and five portions of fruit and vegetables per day. This study examined the prevalence and clustering of meeting recommendations among 10- to 15-year old. Data for 3,914 youth, from the first wave of Understanding Society: the UK Household Longitudinal Study, were analysed. Clustering was assessed using the observed/expected ratio method. A minority of youth met both recommendations, and these behaviours were clustered. The odds of meeting both recommendations were lower for older youth and for Pakistani and Bangladeshi youth; boys in lower income households were less likely to meet both recommendations. Most youth met neither recommendation and the behaviours clustered with variations by ethnicity and socioeconomic conditions.

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.

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.

An integrated intervention to reduce intimate partner violence and psychological distress with refugees in low-resource settings: study protocol for the Nguvu cluster randomized trial.

PubMed

Tol, Wietse A; Greene, M Claire; Likindikoki, Samuel; Misinzo, Lusia; Ventevogel, Peter; Bonz, Ann G; Bass, Judith K; Mbwambo, Jessie K K

2017-05-18

Intimate partner violence (IPV) is a critical public health and human rights concern globally, including for refugee women in low-resource settings. Little is known about effective interventions for this population. IPV and psychological distress have a bi-directional relationship, indicating the potential benefit of a structured psychological component as part of efforts to reduce IPV for women currently in violent relationships. This protocol describes a cluster randomized controlled trial aimed at evaluating an 8-session integrated psychological and advocacy intervention (Nguvu) with female adult survivors of past-year IPV displaying moderate to severe psychological distress. Outcomes are reductions in: recurrence of IPV; symptoms of anxiety, depression and post-traumatic stress (primary); and functional impairment (secondary). Hypothesized mediators of the intervention are improvements in social support, coping skills and support seeking. We will recruit 400 participants from existing women's support groups operating within villages in Nyarugusu refugee camp, Tanzania. Women's groups will be randomized to receive the intervention (Nguvu and usual care) or usual care alone. All eligible women will complete a baseline assessment (week 0) followed by a post-treatment (week 9) and a 3-month post-treatment assessment (week 20). The efficacy of the intervention will be determined by between-group differences in the longitudinal trajectories of primary outcomes evaluated using mixed-effects models. Study procedures have been approved by Institutional Review Boards in the United States and Tanzania. This trial will provide evidence on the efficacy of a novel integrated group intervention aimed at secondary prevention of IPV that includes a structured psychological component to address psychological distress. The psychological and advocacy components of the proposed intervention have been shown to be efficacious for their respective outcomes when delivered in isolation; however, administering these approaches through a single, integrated intervention may result in synergistic effects given the interrelated, bidirectional relationship between IPV and mental health. Furthermore, this trial will provide information regarding the feasibility of implementing a structured intervention for IPV and mental health in a protracted humanitarian setting. ISRCTN65771265 , June 27, 2016.

A more randomly organized grey matter network is associated with deteriorating language and global cognition in individuals with subjective cognitive decline.

PubMed

Verfaillie, Sander C J; Slot, Rosalinde E R; Dicks, Ellen; Prins, Niels D; Overbeek, Jozefien M; Teunissen, Charlotte E; Scheltens, Philip; Barkhof, Frederik; van der Flier, Wiesje M; Tijms, Betty M

2018-03-30

Grey matter network disruptions in Alzheimer's disease (AD) are associated with worse cognitive impairment cross-sectionally. Our aim was to investigate whether indications of a more random network organization are associated with longitudinal decline in specific cognitive functions in individuals with subjective cognitive decline (SCD). We included 231 individuals with SCD who had annually repeated neuropsychological assessment (3 ± 1 years; n = 646 neuropsychological investigations) available from the Amsterdam Dementia Cohort (54% male, age: 63 ± 9, MMSE: 28 ± 2). Single-subject grey matter networks were extracted from baseline 3D-T1 MRI scans and we computed basic network (size, degree, connectivity density) and higher-order (path length, clustering, betweenness centrality, normalized path length [lambda] and normalized clustering [gamma]) parameters at whole brain and/or regional levels. We tested associations of network parameters with baseline and annual cognition (memory, attention, executive functioning, language composite scores, and global cognition [all domains with MMSE]) using linear mixed models, adjusted for age, sex, education, scanner and total gray matter volume. Lower network size was associated with steeper decline in language (β ± SE = 0.12 ± 0.05, p < 0.05FDR). Higher-order network parameters showed no cross-sectional associations. Lower gamma and lambda values were associated with steeper decline in global cognition (gamma: β ± SE = 0.06 ± 0.02); lambda: β ± SE = 0.06 ± 0.02), language (gamma: β ± SE = 0.11 ± 0.04; lambda: β ± SE = 0.12 ± 0.05; all p < 0.05FDR). Lower path length values in precuneus and fronto-temporo-occipital cortices were associated with a steeper decline in global cognition. A more randomly organized grey matter network was associated with a steeper decline of cognitive functioning, possibly indicating the start of cognitive impairment. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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

Longitudinal Study of Career Cluster Persistence from 8th Grade to 12th Grade with a Focus on the Science, Technology, Engineering, & Math Career Cluster

NASA Astrophysics Data System (ADS)

Wagner, Judson

Today's technology driven global economy has put pressure on the American education system to produce more students who are prepared for careers in Science, Technology, Engineering, and Math (STEM). Adding to this pressure is the demand for a more diverse workforce that can stimulate the development of new ideas and innovation. This in turn requires more female and under represented minority groups to pursue future careers in STEM. Though STEM careers include many of the highest paid professionals, school systems are dealing with exceptionally high numbers of students, especially female and under represented minorities, who begin but do not persist to STEM degree completion. Using the Expectancy-Value Theory (EVT) framework that attributes student motivation to a combination of intrinsic, utility, and attainment values, this study analyzed readily available survey data to gauge students' career related values. These values were indirectly investigated through a longitudinal approach, spanning five years, on the predictive nature of 8 th grade survey-derived recommendations for students to pursue a future in a particular career cluster. Using logistic regression analysis, it was determined that this 8 th grade data, particularly in STEM, provides significantly high probabilities of a 12th grader's average grade, SAT-Math score, the math and science elective courses they take, and most importantly, interest in the same career cluster.

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.

Longitudinal influence of alcohol and marijuana use on academic performance in college students.

PubMed

Meda, Shashwath A; Gueorguieva, Ralitza V; Pittman, Brian; Rosen, Rivkah R; Aslanzadeh, Farah; Tennen, Howard; Leen, Samantha; Hawkins, Keith; Raskin, Sarah; Wood, Rebecca M; Austad, Carol S; Dager, Alecia; Fallahi, Carolyn; Pearlson, Godfrey D

2017-01-01

Alcohol and marijuana are the two most abused substances in US colleges. However, research on the combined influence (cross sectional or longitudinal) of these substances on academic performance is currently scant. Data were derived from the longitudinal 2-year Brain and Alcohol Research in College Students (BARCS) study including 1142 freshman students who completed monthly marijuana use and alcohol consumption surveys. Subjects were classified into data-driven groups based on their alcohol and marijuana consumption. A linear mixed-model (LMM) was employed using this grouping factor to predict grade point average (GPA), adjusted for a variety of socio-demographic and clinical factors. Three data-driven clusters emerged: 1) No/low users of both, 2) medium-high alcohol/no-low marijuana, and 3) medium-high users of both substances. Individual cluster derivations between consecutive semesters remained stable. No significant interaction between clusters and semester (time) was noted. Post-hoc analysis suggest that at the outset, compared to sober peers, students using moderate to high levels of alcohol and low marijuana demonstrate lower GPAs, but this difference becomes non-significant over time. In contrast, students consuming both substances at moderate-to-high levels score significantly lower at both the outset and across the 2-year investigation period. Our follow-up analysis also indicate that when students curtailed their substance use over time they had significantly higher academic GPA compared to those who remained stable in their substance use patterns over the two year period. Overall, our study validates and extends the current literature by providing important implications of concurrent alcohol and marijuana use on academic achievement in college.

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.

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.

Longitudinal Examination of the Influence of Individual Posttraumatic Stress Disorder Symptoms and Clusters of Symptoms on the Initiation of Cigarette Smoking.

PubMed

Seelig, Amber D; Bensley, Kara M; Williams, Emily C; Armenta, Richard F; Rivera, Anna C; Peterson, Arthur V; Jacobson, Isabel G; Littman, Alyson J; Maynard, Charles; Bricker, Jonathan B; Rull, Rudolph P; Boyko, Edward J

2018-06-06

The aim of this study was to determine whether specific individual posttraumatic stress disorder (PTSD) symptoms or symptom clusters predict cigarette smoking initiation. Longitudinal data from the Millennium Cohort Study were used to estimate the relative risk for smoking initiation associated with PTSD symptoms among 2 groups: (1) all individuals who initially indicated they were nonsmokers (n = 44,968, main sample) and (2) a subset of the main sample who screened positive for PTSD (n = 1622). Participants were military service members who completed triennial comprehensive surveys that included assessments of smoking and PTSD symptoms. Complementary log-log models were fit to estimate the relative risk for subsequent smoking initiation associated with each of the 17 symptoms that comprise the PTSD Checklist and 5 symptom clusters. Models were adjusted for demographics, military factors, comorbid conditions, and other PTSD symptoms or clusters. In the main sample, no individual symptoms or clusters predicted smoking initiation. However, in the subset with PTSD, the symptoms "feeling irritable or having angry outbursts" (relative risk [RR] 1.41, 95% confidence interval [CI] 1.13-1.76) and "feeling as though your future will somehow be cut short" (RR 1.19, 95% CI 1.02-1.40) were associated with increased risk for subsequent smoking initiation. Certain PTSD symptoms were associated with higher risk for smoking initiation among current and former service members with PTSD. These results may help identify individuals who might benefit from more intensive smoking prevention efforts included with PTSD treatment.

Longitudinal data analysis with non-ignorable missing data.

PubMed

Tseng, Chi-hong; Elashoff, Robert; Li, Ning; Li, Gang

2016-02-01

A common problem in the longitudinal data analysis is the missing data problem. Two types of missing patterns are generally considered in statistical literature: monotone and non-monotone missing data. Nonmonotone missing data occur when study participants intermittently miss scheduled visits, while monotone missing data can be from discontinued participation, loss to follow-up, and mortality. Although many novel statistical approaches have been developed to handle missing data in recent years, few methods are available to provide inferences to handle both types of missing data simultaneously. In this article, a latent random effects model is proposed to analyze longitudinal outcomes with both monotone and non-monotone missingness in the context of missing not at random. Another significant contribution of this article is to propose a new computational algorithm for latent random effects models. To reduce the computational burden of high-dimensional integration problem in latent random effects models, we develop a new computational algorithm that uses a new adaptive quadrature approach in conjunction with the Taylor series approximation for the likelihood function to simplify the E-step computation in the expectation-maximization algorithm. Simulation study is performed and the data from the scleroderma lung study are used to demonstrate the effectiveness of this method. © The Author(s) 2012.

Examining Solutions to Missing Data in Longitudinal Nursing Research

PubMed Central

Roberts, Mary B.; Sullivan, Mary C.; Winchester, Suzy B.

2017-01-01

Purpose Longitudinal studies are highly valuable in pediatrics because they provide useful data about developmental patterns of child health and behavior over time. When data are missing, the value of the research is impacted. The study’s purpose was to: (1) introduce a 3-step approach to assess and address missing data; (2) illustrate this approach using categorical and continuous level variables from a longitudinal study of premature infants. Methods A three-step approach with simulations was followed to assess the amount and pattern of missing data and to determine the most appropriate imputation method for the missing data. Patterns of missingness were Missing Completely at Random, Missing at Random, and Not Missing at Random. Missing continuous-level data were imputed using mean replacement, stochastic regression, multiple imputation, and fully conditional specification. Missing categorical-level data were imputed using last value carried forward, hot-decking, stochastic regression, and fully conditional specification. Simulations were used to evaluate these imputation methods under different patterns of missingness at different levels of missing data. Results The rate of missingness was 16–23% for continuous variables and 1–28% for categorical variables. Fully conditional specification imputation provided the least difference in mean and standard deviation estimates for continuous measures. Fully conditional specification imputation was acceptable for categorical measures. Results obtained through simulation reinforced and confirmed these findings. Practice Implications Significant investments are made in the collection of longitudinal data. The prudent handling of missing data can protect these investments and potentially improve the scientific information contained in pediatric longitudinal studies. PMID:28425202

Advanced Issues in Propensity Scores: Longitudinal and Missing Data

ERIC Educational Resources Information Center

Kupzyk, Kevin A.; Beal, Sarah J.

2017-01-01

In order to investigate causality in situations where random assignment is not possible, propensity scores can be used in regression adjustment, stratification, inverse-probability treatment weighting, or matching. The basic concepts behind propensity scores have been extensively described. When data are longitudinal or missing, the estimation and…

A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

ERIC Educational Resources Information Center

Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

2012-01-01

The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

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...

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

PubMed

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

2009-04-01

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

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.

Water cluster fragmentation probed by pickup experiments

NASA Astrophysics Data System (ADS)

Huang, Chuanfu; Kresin, Vitaly V.; Pysanenko, Andriy; Fárník, Michal

2016-09-01

Electron ionization is a common tool for the mass spectrometry of atomic and molecular clusters. Any cluster can be ionized efficiently by sufficiently energetic electrons, but concomitant fragmentation can seriously obstruct the goal of size-resolved detection. We present a new general method to assess the original neutral population of the cluster beam. Clusters undergo a sticking collision with a molecule from a crossed beam, and the velocities of neat and doped cluster ion peaks are measured and compared. By making use of longitudinal momentum conservation, one can reconstruct the sizes of the neutral precursors. Here this method is applied to H2O and D2O clusters in the detected ion size range of 3-10. It is found that water clusters do fragment significantly upon electron impact: the deduced neutral precursor size is ˜3-5 times larger than the observed cluster ions. This conclusion agrees with beam size characterization by another experimental technique: photoionization after Na-doping. Abundant post-ionization fragmentation of water clusters must therefore be an important factor in the interpretation of experimental data; interestingly, there is at present no detailed microscopic understanding of the underlying fragmentation dynamics.

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.

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

Gupta, Shashaank; Belianinov, Alex; Okatan, Mahmut B

(001)pc textured K0.5Na0.5NbO3 (KNN) ceramic was found to exhibit a 65% improvement in the longitudinal piezoelectric response as compared to its random counterpart. Piezoresponse force microscopy study revealed the existence of larger 180 and non-180 domains for textured ceramic as compared to that of the random ceramic. Improvement in piezoresponse by the development of (001)pc texture is discussed in terms of the crystallographic nature of KNN and domain morphology. A comparative analysis performed with a rhombohedral composition suggested that the improvement in longitudinal piezoresponse of polycrystalline ceramics by the development of (001)pc texture is limited by the crystal structure.

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.

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

PubMed

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

2010-06-30

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

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.

Temperature dependences of characteristics of 2,5-hexanediol and 1,2,6-hexanetriol cluster structures according to dielectric radiospectroscopy

NASA Astrophysics Data System (ADS)

Usacheva, T. M.; Zhuravlev, V. I.

2013-03-01

Dielectric radiospectra (DRS) of 2,5-hexanediol and 1,2,6-hexanetriol at frequencies of 1 MHz, 9.375, 36.885, and 74.569 GHz in a temperature range of 303-423 K (above the glass transition temperatures) are studied. Experimental DRS are analyzed using the Dissado-Hill (DH) cluster model. The dependence of the equilibrium and relaxation characteristics of DRS on the number of OH groups is studied. The dipole moments of the clusters are calculated. The change in the orientation of the dipole moments of the molecules in the cluster during the rearranging of its structure is characterized through the unit vector of the longitudinal component of dipole moment M e of the cluster. The relation between a change in the Onsager-Kirkwood-Fröhlich correlation factor and the behavior of M e is shown.

Beverage Consumption Patterns at Age 13 to 17 Years Are Associated with Weight, Height, and Body Mass Index at Age 17 Years.

PubMed

Marshall, Teresa A; Van Buren, John M; Warren, John J; Cavanaugh, Joseph E; Levy, Steven M

2017-05-01

Sugar-sweetened beverages (SSBs) have been associated with obesity in children and adults; however, associations between beverage patterns and obesity are not understood. Our aim was to describe beverage patterns during adolescence and associations between adolescent beverage patterns and anthropometric measures at age 17 years. We conducted a cross-sectional analyses of longitudinally collected data. Data from participants in the longitudinal Iowa Fluoride Study having at least one beverage questionnaire completed between ages 13.0 and 14.0 years, having a second questionnaire completed between 16.0 and 17.0 years, and attending clinic examination for weight and height measurements at age 17 years (n=369) were included. Beverages were collapsed into four categories (ie, 100% juice, milk, water and other sugar-free beverages, and SSBs) for the purpose of clustering. Five beverage clusters were identified from standardized age 13 to 17 years mean daily beverage intakes and named by the authors for the dominant beverage: juice, milk, water/sugar-free beverages, neutral, and SSB. Weight, height, and body mass index (BMI; calculated as kg/m 2 ) at age 17 years were analyzed. We used Ward's method for clustering of beverage variables, one-way analysis of variance and χ 2 tests for bivariable associations, and γ-regression for associations of weight or BMI (outcomes) with beverage clusters and demographic variables. Linear regression was used for associations of height (outcome) with beverage clusters and demographic variables. Participants with family incomes <$60,000 trended shorter (1.5±0.8 cm; P=0.070) and were heavier (2.0±0.7 BMI units; P=0.002) than participants with family incomes ≥$60,000/year. Adjusted mean weight, height, and BMI estimates differed by beverage cluster membership. For example, on average, male and female members of the neutral cluster were 4.5 cm (P=0.010) and 4.2 cm (P=0.034) shorter, respectively, than members of the milk cluster. For members of the juice cluster, mean BMI was lower than for members of the milk cluster (by 2.4 units), water/sugar-free beverage cluster (3.5 units), neutral cluster (2.2 units), and SSB cluster (3.2 units) (all P<0.05). Beverage patterns at ages 13 to 17 years were associated with anthropometric measures and BMI at age 17 years in this sample. Beverage patterns might be characteristic of overall food choices and dietary behaviors that influence growth. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Stable dissipative optical vortex clusters by inhomogeneous effective diffusion.

PubMed

Li, Huishan; Lai, Shiquan; Qui, Yunli; Zhu, Xing; Xie, Jianing; Mihalache, Dumitru; He, Yingji

2017-10-30

We numerically show the generation of robust vortex clusters embedded in a two-dimensional beam propagating in a dissipative medium described by the generic cubic-quintic complex Ginzburg-Landau equation with an inhomogeneous effective diffusion term, which is asymmetrical in the two transverse directions and periodically modulated in the longitudinal direction. We show the generation of stable optical vortex clusters for different values of the winding number (topological charge) of the input optical beam. We have found that the number of individual vortex solitons that form the robust vortex cluster is equal to the winding number of the input beam. We have obtained the relationships between the amplitudes and oscillation periods of the inhomogeneous effective diffusion and the cubic gain and diffusion (viscosity) parameters, which depict the regions of existence and stability of vortex clusters. The obtained results offer a method to form robust vortex clusters embedded in two-dimensional optical beams, and we envisage potential applications in the area of structured light.

Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

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

Whitehead, Alfred J.; McMillan, Stephen L. W.; Vesperini, Enrico

2013-12-01

We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noisemore » introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.« less

A polymer, random walk model for the size-distribution of large DNA fragments after high linear energy transfer radiation

NASA Technical Reports Server (NTRS)

Ponomarev, A. L.; Brenner, D.; Hlatky, L. R.; Sachs, R. K.

2000-01-01

DNA double-strand breaks (DSBs) produced by densely ionizing radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. Stochastic DSB clustering at large scales, from > 100 Mbp down to < 0.01 Mbp, is modeled using computer simulations and analytic equations. A random-walk, coarse-grained polymer model for chromatin is combined with a simple track structure model in Monte Carlo software called DNAbreak and is applied to data on alpha-particle irradiation of V-79 cells. The chromatin model neglects molecular details but systematically incorporates an increase in average spatial separation between two DNA loci as the number of base-pairs between the loci increases. Fragment-size distributions obtained using DNAbreak match data on large fragments about as well as distributions previously obtained with a less mechanistic approach. Dose-response relations, linear at small doses of high linear energy transfer (LET) radiation, are obtained. They are found to be non-linear when the dose becomes so large that there is a significant probability of overlapping or close juxtaposition, along one chromosome, for different DSB clusters from different tracks. The non-linearity is more evident for large fragments than for small. The DNAbreak results furnish an example of the RLC (randomly located clusters) analytic formalism, which generalizes the broken-stick fragment-size distribution of the random-breakage model that is often applied to low-LET data.

Mechanisms contributing to cluster formation in the inferior olivary nucleus in brainstem slices from postnatal mice

PubMed Central

Kølvraa, Mathias; Müller, Felix C; Jahnsen, Henrik; Rekling, Jens C

2014-01-01

Abstract The inferior olivary nucleus (IO) in in vitro slices from postnatal mice (P5.5–P15.5) spontaneously generates clusters of neurons with synchronous calcium transients, and intracellular recordings from IO neurons suggest that electrical coupling between neighbouring IO neurons may serve as a synchronizing mechanism. Here, we studied the cluster-forming mechanism and find that clusters overlap extensively with an overlap distribution that resembles the distribution for a random overlap model. The average somatodendritic field size of single curly IO neurons was ∼6400 μm2, which is slightly smaller than the average IO cluster size. Eighty-seven neurons with overlapping dendrites were estimated to be contained in the principal olive mean cluster size, and about six non-overlapping curly IO neurons could be contained within the largest clusters. Clusters could also be induced by iontophoresis with glutamate. Induced clusters were inhibited by tetrodotoxin, carbenoxelone and 18β-glycyrrhetinic acid, suggesting that sodium action potentials and electrical coupling are involved in glutamate-induced cluster formation, which could also be induced by activation of N-methyl-d-aspartate and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors. Spikelets and a small transient depolarizing response were observed during glutamate-induced cluster formation. Calcium transients spread with decreasing velocity during cluster formation, and somatic action potentials and cluster formation are accompanied by large dendritic calcium transients. In conclusion, cluster formation depends on gap junctions, sodium action potentials and spontaneous clusters occur randomly throughout the IO. The relative slow signal spread during cluster formation, combined with a strong dendritic influx of calcium, may signify that active dendritic properties contribute to cluster formation. PMID:24042500

Parenthood and the Quality of Experience in Daily Life: A Longitudinal Study

ERIC Educational Resources Information Center

Fave, Antonella Delle; Massimini, Fausto

2004-01-01

This longitudinal study analyzes the time budget and the quality of experience reported by new parents. Five primiparous couples were repeatedly administered Experience Sampling Method. They carried pagers sending random signals 6-8 times a day; at the signal reception, they filled out forms sampling current thoughts, activities, and the quality…

Human comfort response to random motions with a dominant longitudinal motion

NASA Technical Reports Server (NTRS)

Stone, R. W., Jr.

1975-01-01

Subjective ride comfort response ratings were measured on the Langley Visual Motion Simulator with longitudinal acceleration inputs with various power spectra shapes and magnitudes. The results show only little influence of spectra shape on comfort response. The effects of magnitude on comfort response indicate the applicability of psychophysical precepts for comfort modeling.

Using Fit Indexes to Select a Covariance Model for Longitudinal Data

ERIC Educational Resources Information Center

Liu, Siwei; Rovine, Michael J.; Molenaar, Peter C. M.

2012-01-01

This study investigated the performance of fit indexes in selecting a covariance structure for longitudinal data. Data were simulated to follow a compound symmetry, first-order autoregressive, first-order moving average, or random-coefficients covariance structure. We examined the ability of the likelihood ratio test (LRT), root mean square error…

An INAR(1) Negative Multinomial Regression Model for Longitudinal Count Data.

ERIC Educational Resources Information Center

Bockenholt, Ulf

1999-01-01

Discusses a regression model for the analysis of longitudinal count data in a panel study by adapting an integer-valued first-order autoregressive (INAR(1)) Poisson process to represent time-dependent correlation between counts. Derives a new negative multinomial distribution by combining INAR(1) representation with a random effects approach.…

Predicting Posttraumatic Stress Symptoms Longitudinally in a Representative Sample of Hospitalized Injured Adolescents

ERIC Educational Resources Information Center

Zatzick, Douglas F.; Grossman, David C.; Russo, Joan; Pynoos, Robert; Berliner, Lucy; Jurkovich, Gregory; Sabin, Janice A.; Katon, Wayne; Ghesquiere, Angela; McCauley, Elizabeth; Rivara, Frederick P.

2006-01-01

Objective: Adolescents constitute a high-risk population for traumatic physical injury, yet few longitudinal investigations have assessed the development of posttraumatic stress disorder (PTSD) symptoms over time in representative samples. Method: Between July 2002 and August 2003,108 randomly selected injured adolescent patients ages 12 to 18 and…

Classroom Connectivity and Algebra 1 Achievement: A Three-Year Longitudinal Study

ERIC Educational Resources Information Center

Irving, Karen E.; Pape, Stephen J.; Owens, Douglas T.; Abrahamson, Louis; Silver, David; Sanalan, Vehbi A.

2016-01-01

Findings from three years of a longitudinal randomized control trial involving a national U.S. sample of Algebra 1 teachers and students are reported. The study examines the effects of a connected classroom technology (CCT) professional development and classroom intervention on student achievement when compared to classroom instruction with…

Increasing Young Children's Contact with Print during Shared Reading: Longitudinal Effects on Literacy Achievement

ERIC Educational Resources Information Center

Piasta, Shayne B.; Justice, Laura M.; McGinty, Anita S.; Kaderavek, Joan N.

2012-01-01

Longitudinal results for a randomized-controlled trial (RCT) assessing the impact of increasing preschoolers' attention to print during reading are reported. Four-year-old children (N = 550) in 85 classrooms experienced a 30-week shared reading program implemented by their teachers. Children in experimental classrooms experienced shared-book…

Weight loss is associated with improvements in cognitive function among overweight and obese people: A systematic review and meta-analysis.

PubMed

Veronese, Nicola; Facchini, Silvia; Stubbs, Brendon; Luchini, Claudio; Solmi, Marco; Manzato, Enzo; Sergi, Giuseppe; Maggi, Stefania; Cosco, Theodore; Fontana, Luigi

2017-01-01

Whilst obesity is associated with a higher risk of cognitive impairment, the influence of weight loss on cognitive function in obese/overweight people is equivocal. We conducted a meta-analysis of randomized controlled trials (RCTs) and longitudinal studies evaluating the influence of voluntary weight loss on cognitive function in obese/overweight individuals. Articles were acquired from a systematic search of major databases from inception till 01/2016. A random effect meta-analysis of weight loss interventions (diet, physical activity, bariatric surgery) on different cognitive domains (memory, attention, executive functions, language and motor speed) was conducted. Twenty studies (13 longitudinal studies=551 participants; 7 RCTs=328 treated vs. 140 controls) were included. Weight loss was associated with a significant improvement in attention and memory in both longitudinal studies and RCTs, whereas executive function and language improved in longitudinal and RCT studies, respectively. In conclusion, intentional weight loss in obese/overweight people is associated with improvements in performance across various cognitive domains. Future adequately powered RCTs are required to confirm/refute these findings. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

On the Coupling Time of the Heat-Bath Process for the Fortuin-Kasteleyn Random-Cluster Model

NASA Astrophysics Data System (ADS)

Collevecchio, Andrea; Elçi, Eren Metin; Garoni, Timothy M.; Weigel, Martin

2018-01-01

We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process.

Psychoanalytic-Interactional Therapy versus Psychodynamic Therapy by Experts for Personality Disorders: A Randomized Controlled Efficacy-Effectiveness Study in Cluster B Personality Disorders.

PubMed

Leichsenring, Falk; Masuhr, Oliver; Jaeger, Ulrich; Rabung, Sven; Dally, Andreas; Dümpelmann, Michael; Fricke-Neef, Christian; Steinert, Christiane; Streeck, Ulrich

2016-01-01

With regard to cluster B personality disorders, most psychotherapeutic treatments focus on borderline personality disorder. Evidence-based treatments for patients with other cluster B personality disorders are not yet available. Psychoanalytic-interactional therapy (PIT) represents a transdiagnostic treatment for severe personality disorders. PIT has been applied in clinical practice for many years and has proven effective in open studies. In a randomized controlled trial, we compared manual-guided PIT to nonmanualized pychodynamic therapy by experts in personality disorders (E-PDT) in patients with cluster B personality disorders. In an inpatient setting, patients with cluster B personality disorders were randomly assigned to manual-guided PIT (n = 64) or nonmanualized E-PDT (n = 58). In addition, a quasi-experimental control condition was used (n = 46) including both patients receiving treatment as usual and patients waiting for treatment. Primary outcomes were level of personality organization and overall psychological distress. As secondary outcomes, depression, anxiety and interpersonal problems were examined. No significant improvements were found in the control patients. Both PIT and E-PDT achieved significant improvements in all outcome measures and were superior to the control condition. No differences were found between PIT and E-PDT in any outcome measure at the end of treatment. The type of cluster B personality disorder had no impact on the results. In an inpatient setting, both PIT and E-PDT proved to be superior to a control condition in cluster B personality disorders. In a head-to-head comparison, both treatments appeared to be equally effective. Further research on the treatment of cluster B personality disorders is required. © 2016 S. Karger AG, Basel.

Cascades on a class of clustered random networks

NASA Astrophysics Data System (ADS)

Hackett, Adam; Melnik, Sergey; Gleeson, James P.

2011-05-01

We present an analytical approach to determining the expected cascade size in a broad range of dynamical models on the class of random networks with arbitrary degree distribution and nonzero clustering introduced previously in [M. E. J. Newman, Phys. Rev. Lett. PRLTAO0031-900710.1103/PhysRevLett.103.058701103, 058701 (2009)]. A condition for the existence of global cascades is derived as well as a general criterion that determines whether increasing the level of clustering will increase, or decrease, the expected cascade size. Applications, examples of which are provided, include site percolation, bond percolation, and Watts’ threshold model; in all cases analytical results give excellent agreement with numerical simulations.

Seizure clustering.

PubMed

Haut, Sheryl R

2006-02-01

Seizure clusters, also known as repetitive or serial seizures, occur commonly in epilepsy. Clustering implies that the occurrence of one seizure may influence the probability of a subsequent seizure; thus, the investigation of the clustering phenomenon yields insights into both specific mechanisms of seizure clustering and more general concepts of seizure occurrence. Seizure clustering has been defined clinically as a number of seizures per unit time and, statistically, as a deviation from a random distribution, or interseizure interval dependence. This review explores the pathophysiology, epidemiology, and clinical implications of clustering, as well as other periodic patterns of seizure occurrence. Risk factors for experiencing clusters and potential precipitants of clustering are also addressed.

A mixed-effects regression model for longitudinal multivariate ordinal data.

PubMed

Liu, Li C; Hedeker, Donald

2006-03-01

A mixed-effects item response theory model that allows for three-level multivariate ordinal outcomes and accommodates multiple random subject effects is proposed for analysis of multivariate ordinal outcomes in longitudinal studies. This model allows for the estimation of different item factor loadings (item discrimination parameters) for the multiple outcomes. The covariates in the model do not have to follow the proportional odds assumption and can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is proposed utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher scoring solution, which provides standard errors for all model parameters, is used. An analysis of a longitudinal substance use data set, where four items of substance use behavior (cigarette use, alcohol use, marijuana use, and getting drunk or high) are repeatedly measured over time, is used to illustrate application of the proposed model.

School-based mental health intervention for children in war-affected Burundi: a cluster randomized trial.

PubMed

Tol, Wietse A; Komproe, Ivan H; Jordans, Mark J D; Ndayisaba, Aline; Ntamutumba, Prudence; Sipsma, Heather; Smallegange, Eva S; Macy, Robert D; de Jong, Joop T V M

2014-04-01

Armed conflicts are associated with a wide range of impacts on the mental health of children and adolescents. We evaluated the effectiveness of a school-based intervention aimed at reducing symptoms of posttraumatic stress disorder, depression, and anxiety (treatment aim); and improving a sense of hope and functioning (preventive aim). We conducted a cluster randomized trial with 329 children in war-affected Burundi (aged 8 to 17 (mean 12.29 years, standard deviation 1.61); 48% girls). One group of children (n = 153) participated in a 15-session school-based intervention implemented by para-professionals, and the remaining 176 children formed a waitlist control condition. Outcomes were measured before, one week after, and three months after the intervention. No main effects of the intervention were identified. However, longitudinal growth curve analyses showed six favorable and two unfavorable differences in trajectories between study conditions in interaction with several moderators. Children in the intervention condition living in larger households showed decreases on depressive symptoms and function impairment, and those living with both parents showed decreases on posttraumatic stress disorder and depressive symptoms. The groups of children in the waitlist condition showed increases in depressive symptoms. In addition, younger children and those with low levels of exposure to traumatic events in the intervention condition showed improvements on hope. Children in the waitlist condition who lived on their original or newly bought land showed improvements in hope and function impairment, whereas children in the intervention condition showed deterioration on these outcomes. Given inconsistent effects across studies, findings do not support this school-based intervention as a treatment for posttraumatic stress disorder and depressive symptoms in conflict-affected children. The intervention appears to have more consistent preventive benefits, but these effects are contingent upon individual (for example, age, gender) and contextual (for example, family functioning, state of conflict, displacement) variables. Results suggest the potential benefit of school-based preventive interventions particularly in post-conflict settings. The study was registered as ISRCTN42284825.

Role of maternal health and infant inflammation in nutritional and neurodevelopmental outcomes of two-year-old Bangladeshi children.

PubMed

Donowitz, Jeffrey R; Cook, Heather; Alam, Masud; Tofail, Fahmida; Kabir, Mamun; Colgate, E Ross; Carmolli, Marya P; Kirkpatrick, Beth D; Nelson, Charles A; Ma, Jennie Z; Haque, Rashidul; Petri, William A

2018-05-01

Previous studies have shown maternal, inflammatory, and socioeconomic variables to be associated with growth and neurodevelopment in children from low-income countries. However, these outcomes are multifactorial and work describing which predictors most strongly influence them is lacking. We conducted a longitudinal study of Bangladeshi children from birth to two years to assess oral vaccine efficacy. Variables pertaining to maternal and perinatal health, socioeconomic status, early childhood enteric and systemic inflammation, and anthropometry were collected. Bayley-III neurodevelopmental assessment was conducted at two years. As a secondary analysis, we employed hierarchical cluster and random forests techniques to identify and rank which variables predicted growth and neurodevelopment. Cluster analysis demonstrated three distinct groups of predictors. Mother's weight and length-for-age Z score (LAZ) at enrollment were the strongest predictors of LAZ at two years. Cognitive score on Bayley-III was strongly predicted by weight-for-age (WAZ) at enrollment, income, and LAZ at enrollment. Top predictors of language included Rotavirus vaccination, plasma IL 5, sCD14, TNFα, mother's weight, and male gender. Motor function was best predicted by fecal calprotectin, WAZ at enrollment, fecal neopterin, and plasma CRP index. The strongest predictors for social-emotional score included plasma sCD14, income, WAZ at enrollment, and LAZ at enrollment. Based on the random forests' predictions, the estimated percentage of variation explained was 35.4% for LAZ at two years, 34.3% for ΔLAZ, 42.7% for cognitive score, 28.1% for language, 40.8% for motor, and 37.9% for social-emotional score. Birth anthropometry and maternal weight were strong predictors of growth while enteric and systemic inflammation had stronger associations with neurodevelopment. Birth anthropometry was a powerful predictor for all outcomes. These data suggest that further study of stunting in low-income settings should include variables relating to maternal and prenatal health, while investigations focusing on neurodevelopmental outcomes should additionally target causes of systemic and enteric inflammation.

Effect of village-wide use of long-lasting insecticidal nets on visceral Leishmaniasis vectors in India and Nepal: a cluster randomized trial.

PubMed

Picado, Albert; Das, Murari L; Kumar, Vijay; Kesari, Shreekant; Dinesh, Diwakar S; Roy, Lalita; Rijal, Suman; Das, Pradeep; Rowland, Mark; Sundar, Shyam; Coosemans, Marc; Boelaert, Marleen; Davies, Clive R

2010-01-26

Visceral leishmaniasis (VL) control in the Indian subcontinent is currently based on case detection and treatment, and on vector control using indoor residual spraying (IRS). The use of long-lasting insecticidal nets (LN) has been postulated as an alternative or complement to IRS. Here we tested the impact of comprehensive distribution of LN on the density of Phlebotomus argentipes in VL-endemic villages. A cluster-randomized controlled trial with household P. argentipes density as outcome was designed. Twelve clusters from an ongoing LN clinical trial--three intervention and three control clusters in both India and Nepal--were selected on the basis of accessibility and VL incidence. Ten houses per cluster selected on the basis of high pre-intervention P. argentipes density were monitored monthly for 12 months after distribution of LN using CDC light traps (LT) and mouth aspiration methods. Ten cattle sheds per cluster were also monitored by aspiration. A random effect linear regression model showed that the cluster-wide distribution of LNs significantly reduced the P. argentipes density/house by 24.9% (95% CI 1.80%-42.5%) as measured by means of LTs. The ongoing clinical trial, designed to measure the impact of LNs on VL incidence, will confirm whether LNs should be adopted as a control strategy in the regional VL elimination programs. The entomological evidence described here provides some evidence that LNs could be usefully deployed as part of the VL control program. ClinicalTrials.gov CT-2005-015374.

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.

UNSTEADY DISPERSION IN RANDOM INTERMITTENT FLOW

EPA Science Inventory

The longitudinal dispersion coefficient of a conservative tracer was calculated from flow tests in a dead-end pipe loop system. Flow conditions for these tests ranged from laminar to transitional flow, and from steady to intermittent and random. Two static mixers linked in series...

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.

Phytomonas: analysis of polymorphism and genetic relatedness between isolates from plants and phytophagous insects from different geographic regions by RAPD fingerprints and synapomorphic markers.

PubMed

Serrano, M G; Camargo, E P; Teixeira, M M

1999-01-01

The random amplification of polymorphic DNA was used for easy, quick and sensitive assessment of genetic polymorphism within Phytomonas to discriminate isolates and determine genetic relationships within the genus. We examined 48 Phytomonas spp., 31 isolates from plants and 17 from insects, from different geographic regions. Topology of the dendrogram based on randomly amplified polymorphic DNA fingerprints segregated the Phytomonas spp. into 5 main clusters, despite the high genetic variability within this genus. Similar clustering could also be obtained by both visual and cross-hybridization analysis of randomly amplified synapomorphic DNA fragments. There was some concordance between the genetic relationship of isolates and their plant tissue tropism. Moreover, Phytomonas spp. from plants and insects were grouped according to geographic origin, thus revealing a complex structure of this taxon comprising several clusters of very closely related organisms.

Outcomes of a pilot hand hygiene randomized cluster trial to reduce communicable infections among US office-based employees.

PubMed

Stedman-Smith, Maggie; DuBois, Cathy L Z; Grey, Scott F; Kingsbury, Diana M; Shakya, Sunita; Scofield, Jennifer; Slenkovich, Ken

2015-04-01

To determine the effectiveness of an office-based multimodal hand hygiene improvement intervention in reducing self-reported communicable infections and work-related absence. A randomized cluster trial including an electronic training video, hand sanitizer, and educational posters (n = 131, intervention; n = 193, control). Primary outcomes include (1) self-reported acute respiratory infections (ARIs)/influenza-like illness (ILI) and/or gastrointestinal (GI) infections during the prior 30 days; and (2) related lost work days. Incidence rate ratios calculated using generalized linear mixed models with a Poisson distribution, adjusted for confounders and random cluster effects. A 31% relative reduction in self-reported combined ARI-ILI/GI infections (incidence rate ratio: 0.69; 95% confidence interval, 0.49 to 0.98). A 21% nonsignificant relative reduction in lost work days. An office-based multimodal hand hygiene improvement intervention demonstrated a substantive reduction in self-reported combined ARI-ILI/GI infections.

Comparison of endothelial changes and power settings between torsional and longitudinal phacoemulsification.

PubMed

Reuschel, Anna; Bogatsch, Holger; Barth, Thomas; Wiedemann, Renate

2010-11-01

To compare the intraoperative and postoperative outcomes of conventional longitudinal phacoemulsification and torsional phacoemulsification. Department of Ophthalmology, University of Leipzig, Germany. Randomized single-center clinical trial. Eyes with senile cataract were randomized to have phacoemulsification using the Infiniti Vision System and the torsional mode (OZil) or conventional longitudinal mode. Primary outcomes were corrected distance visual acuity (CDVA) and central endothelial cell density (ECD), calculated according to the Conference on Harmonisation-E9 Guidelines in which missing values were substituted by the median in each group (primary analysis) and the loss was then calculated using actual data (secondary analysis). Secondary outcomes were ultrasound (US) time, cumulative dissipated energy (CDE), and percentage total equivalent power in position 3. Postoperative follow-up was at 3 months. The mean preoperative CDVA was 0.41 logMAR in the torsional group and 0.38 logMAR in the longitudinal group, improving to 0.07 logMAR postoperatively in both groups. The mean ECD loss was 7.2% ± 4.6% in the torsional group (72 patients) and 7.1% ± 4.4% in the longitudinal group (76 patients), with no statistically significant differences in the primary analysis (P = .342) or secondary analysis (P = .906). The mean US time, CDE, and percentage total equivalent power in position 3 were statistically significantly lower in the torsional group (98 patients) than in the longitudinal group (94 patients) (P<.001). The torsional mode was as safe as the longitudinal mode in phacoemulsification for age-related cataract. Copyright © 2010 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Effect of poverty reduction program on nutritional status of the extreme poor in Bangladesh.

PubMed

Jalal, Chowdhury S B; Frongillo, Edward A

2013-12-01

Poverty alleviation programs for the extreme poor improve participants' economic status and may impact other important outcomes that are seldom evaluated. A program targeted to the extreme poor by BRAG, a development organization in Bangladesh, has been successful in significantly alleviating extreme poverty. We hypothesized that the program also improved the nutritional status of women and preschool children. A nonequivalent control, pre- and posttest quasi-experimental design that was longitudinal at the village level was used to test the hypotheses. Data were collected from a random sample of 4,131 children and 3,551 women from 3,409 households in 159 villages of 3 northern districts of Bangladesh in 2002 and 2006. Linear mixed random-intercept models accounted for clustering effects and potential confounders. The weight-for-height of children between 24 and 35 months of age from program households was significantly higher (p < .05) than that of children from control households. We found no significant differences between control and program households in three other growth and body-composition indicators in three other age categories of preschool children or in women. These results are important, as this is a large-scale program that has already been extended to more than half the country. The findings will contribute to judging the cost-benefit and cost-effectiveness of the program and in garnering support for the expansion of such programs.

Evaluation of a demand-creation intervention for couples' HIV testing services among married or cohabiting individuals in Rakai, Uganda: a cluster-randomized intervention trial.

PubMed

Matovu, Joseph K B; Todd, Jim; Wanyenze, Rhoda K; Kairania, Robert; Serwadda, David; Wabwire-Mangen, Fred

2016-08-08

Uptake of couples' HIV counseling and testing (couples' HCT) services remains largely low in most settings. We report the effect of a demand-creation intervention trial on couples' HCT uptake among married or cohabiting individuals who had never received couples' HCT. This was a cluster-randomized intervention trial implemented in three study regions with differing HIV prevalence levels (range: 9-43 %) in Rakai district, southwestern Uganda, between February and September 2014. We randomly assigned six clusters (1:1) to receive the intervention or serve as the comparison arm using computer-generated random numbers. In the intervention clusters, individuals attended small group, couple and male-focused interactive sessions, reinforced with testimonies from 'expert couples', and received invitation coupons to test together with their partners at designated health facilities. In the comparison clusters, participants attended general adult health education sessions but received no invitation coupons. The primary outcome was couples' HCT uptake, measured 12 months post-baseline. Baseline data were collected between November 2013 and February 2014 while follow-up data were collected between March and April 2015. We conducted intention-to-treat analysis using a mixed effects Poisson regression model to assess for differences in couples' HCT uptake between the intervention and comparison clusters. Data analysis was conducted using STATA statistical software, version 14.1. Of 2135 married or cohabiting individuals interviewed at baseline, 42 % (n = 846) had ever received couples' HCT. Of those who had never received couples' HCT (n = 1,174), 697 were interviewed in the intervention clusters while 477 were interviewed in the comparison clusters. 73.6 % (n = 513) of those interviewed in the intervention and 82.6 % (n = 394) of those interviewed in the comparison cluster were interviewed at follow-up. Of those interviewed, 72.3 % (n = 371) in the intervention and 65.2 % (n = 257) in the comparison clusters received HCT. Couples' HCT uptake was higher in the intervention than in the comparison clusters (20.3 % versus 13.7 %; adjusted prevalence ratio (aPR) = 1.43, 95 % CI: 1.02, 2.01, P = 0.04). Our findings show that a small group, couple and male-focused, demand-creation intervention reinforced with testimonies from 'expert couples', improved uptake of couples' HCT in this rural setting. ClinicalTrials.gov, NCT02492061 . Date of registration: June 14, 2015.

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.

Longitudinal influence of alcohol and marijuana use on academic performance in college students

PubMed Central

Meda, Shashwath A.; Gueorguieva, Ralitza V.; Pittman, Brian; Rosen, Rivkah R.; Aslanzadeh, Farah; Tennen, Howard; Leen, Samantha; Hawkins, Keith; Raskin, Sarah; Wood, Rebecca M.; Austad, Carol S.; Dager, Alecia; Fallahi, Carolyn; Pearlson, Godfrey D.

2017-01-01

Background Alcohol and marijuana are the two most abused substances in US colleges. However, research on the combined influence (cross sectional or longitudinal) of these substances on academic performance is currently scant. Methods Data were derived from the longitudinal 2-year Brain and Alcohol Research in College Students (BARCS) study including 1142 freshman students who completed monthly marijuana use and alcohol consumption surveys. Subjects were classified into data-driven groups based on their alcohol and marijuana consumption. A linear mixed-model (LMM) was employed using this grouping factor to predict grade point average (GPA), adjusted for a variety of socio-demographic and clinical factors. Results Three data-driven clusters emerged: 1) No/low users of both, 2) medium-high alcohol/no-low marijuana, and 3) medium-high users of both substances. Individual cluster derivations between consecutive semesters remained stable. No significant interaction between clusters and semester (time) was noted. Post-hoc analysis suggest that at the outset, compared to sober peers, students using moderate to high levels of alcohol and low marijuana demonstrate lower GPAs, but this difference becomes non-significant over time. In contrast, students consuming both substances at moderate-to-high levels score significantly lower at both the outset and across the 2-year investigation period. Our follow-up analysis also indicate that when students curtailed their substance use over time they had significantly higher academic GPA compared to those who remained stable in their substance use patterns over the two year period. Conclusions Overall, our study validates and extends the current literature by providing important implications of concurrent alcohol and marijuana use on academic achievement in college. PMID:28273162

On the Clustering of Europa's Small Craters

NASA Technical Reports Server (NTRS)

Bierhaus, E. B.; Chapman, C. R.; Merline, W. J.

2001-01-01

We analyze the spatial distribution of Europa's small craters and find that many are too tightly clustered to result from random, primary impacts. Additional information is contained in the original extended abstract.

Individualizing drug dosage with longitudinal data.

PubMed

Zhu, Xiaolu; Qu, Annie

2016-10-30

We propose a two-step procedure to personalize drug dosage over time under the framework of a log-linear mixed-effect model. We model patients' heterogeneity using subject-specific random effects, which are treated as the realizations of an unspecified stochastic process. We extend the conditional quadratic inference function to estimate both fixed-effect coefficients and individual random effects on a longitudinal training data sample in the first step and propose an adaptive procedure to estimate new patients' random effects and provide dosage recommendations for new patients in the second step. An advantage of our approach is that we do not impose any distribution assumption on estimating random effects. Moreover, the new approach can accommodate more general time-varying covariates corresponding to random effects. We show in theory and numerical studies that the proposed method is more efficient compared with existing approaches, especially when covariates are time varying. In addition, a real data example of a clozapine study confirms that our two-step procedure leads to more accurate drug dosage recommendations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Methods to Limit Attrition in Longitudinal Comparative Effectiveness Trials: Lessons from the Lithium Use for Bipolar Disorder (LiTMUS) Study

PubMed Central

Sylvia, Louisa G.; Reilly-Harrington, Noreen A.; Leon, Andrew C.; Kansky, Christine I.; Ketter, Terence A.; Calabrese, Joseph R.; Thase, Michael E.; Bowden, Charles L.; Friedman, Edward S.; Ostacher, Michael J.; Iosifescu, Dan V.; Severe, Joanne; Nierenberg, Andrew A.

2013-01-01

Background High attrition rates which occur frequently in longitudinal clinical trials of interventions for bipolar disorder limit the interpretation of results. Purpose The aim of this article is to present design approaches that limited attrition in the Lithium Use for Bipolar Disorder (LiTMUS) Study. Methods LiTMUS was a 6-month randomized, longitudinal multi-site comparative effectiveness trial that examined bipolar participants who were at least mildly ill. Participants were randomized to either low to moderate doses of lithium or no lithium, in addition to other treatments needed for mood stabilization administered in a guideline-informed, empirically supported, and personalized fashion (N=283). Results Components of the study design that may have contributed to the low attrition rate of the study included use of: (1) an intent-to-treat design; (2) a randomized adjunctive single-blind design; (3) participant reimbursement; (4) intent-to-attend the next study visit (includes a discussion of attendance obstacles when intention is low); (5) quality care with limited participant burden; and (6) target windows for study visits. Limitations Site differences and the effectiveness and tolerability data have not been analyzed yet. Conclusions These components of the LiTMUS study design may have reduced the probability of attrition which would inform the design of future randomized clinical effectiveness trials. PMID:22076437

Implementation of client versus care-provider strategies to improve external cephalic version rates: a cluster randomized controlled trial.

PubMed

Vlemmix, Floortje; Rosman, Ageeth N; Rijnders, Marlies E; Beuckens, Antje; Opmeer, Brent C; Mol, Ben W J; Kok, Marjolein; Fleuren, Margot A H

2015-05-01

To determine the effectiveness of a client or care-provider strategy to improve the implementation of external cephalic version. Cluster randomized controlled trial. Twenty-five clusters; hospitals and their referring midwifery practices randomly selected in the Netherlands. Singleton breech presentation from 32 weeks of gestation onwards. We randomized clusters to a client strategy (written information leaflets and decision aid), a care-provider strategy (1-day counseling course focused on knowledge and counseling skills), a combined client and care-provider strategy and care-as-usual strategy. We performed an intention-to-treat analysis. Rate of external cephalic version in various strategies. Secondary outcomes were the percentage of women counseled and opting for a version attempt. The overall implementation rate of external cephalic version was 72% (1169 of 1613 eligible clients) with a range between clusters of 8-95%. Neither the client strategy (OR 0.8, 95% CI 0.4-1.5) nor the care-provider strategy (OR 1.2, 95% CI 0.6-2.3) showed significant improvements. Results were comparable when we limited the analysis to those women who were actually offered intervention (OR 0.6, 95% CI 0.3-1.4 and OR 2.0, 95% CI 0.7-4.5). Neither a client nor a care-provider strategy improved the external cephalic version implementation rate for breech presentation, neither with regard to the number of version attempts offered nor the number of women accepting the procedure. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

Power Analysis for Cross Level Mediation in CRTs

ERIC Educational Resources Information Center

Kelcey, Ben

2014-01-01

A common design in education research for interventions operating at a group or cluster level is a cluster randomized trial (CRT) (Bloom, 2005). In CRTs, intact clusters (e.g., schools) are assigned to treatment conditions rather than individuals (e.g., students) and are frequently an effective way to study interventions because they permit…

Dispersivity of Bidisperse Packings of Spheres and Evidence for Distinct Random Structures

NASA Astrophysics Data System (ADS)

Scheven, U. M.

2018-05-01

The intrinsic longitudinal and transverse dispersivity of bidisperse random packings of spheres with size ratio 5 ∶1 was determined by pulsed field gradient nuclear magnetic resonance, in the dilute regime where small spheres occupy between 0% and 5% of the packings' volume. Small spheres plugging pores systematically raise the mechanical transverse and longitudinal dispersivity above that of reference packings of monodisperse spheres. NMR-derived porosities, widths of velocity distributions, and dispersivities reveal distinct states of structural disorder above and below a relative sphere concentration n /N =1 , where n and N are the number densities of small and large spheres.

Permeability of model porous medium formed by random discs

NASA Astrophysics Data System (ADS)

Gubaidullin, A. A.; Gubkin, A. S.; Igoshin, D. E.; Ignatev, P. A.

2018-03-01

Two-dimension model of the porous medium with skeleton of randomly located overlapping discs is proposed. The geometry and computational grid are built in open package Salome. Flow of Newtonian liquid in longitudinal and transverse directions is calculated and its flow rate is defined. The numerical solution of the Navier-Stokes equations for a given pressure drop at the boundaries of the area is realized in the open package OpenFOAM. Calculated value of flow rate is used for defining of permeability coefficient on the base of Darcy law. For evaluating of representativeness of computational domain the permeability coefficients in longitudinal and transverse directions are compered.

Mathematical modelling of complex contagion on clustered networks

NASA Astrophysics Data System (ADS)

O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James

2015-09-01

The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.

Longitudinal Associations between Adolescent Alcohol Use and Parents' Sources of Knowledge

ERIC Educational Resources Information Center

Stavrinides, Panayiotis; Georgiou, Stelios; Demetriou, Andreas

2010-01-01

The aim of this study was to test the direction of effect in the relationship between parents' sources of knowledge (parental monitoring and child disclosure) and adolescent alcohol use. The participants were 215 adolescents and their mothers, randomly selected from urban and rural areas in Cyprus. A 3-month, two-timepoint longitudinal design was…

Sensitivity Analysis of Mixed Models for Incomplete Longitudinal Data

ERIC Educational Resources Information Center

Xu, Shu; Blozis, Shelley A.

2011-01-01

Mixed models are used for the analysis of data measured over time to study population-level change and individual differences in change characteristics. Linear and nonlinear functions may be used to describe a longitudinal response, individuals need not be observed at the same time points, and missing data, assumed to be missing at random (MAR),…

Family and Psychosocial Risk Factors in a Longitudinal Epidemiological Study of Adolescents.

ERIC Educational Resources Information Center

Cuffe, Steven P.; McKeown, Robert E.; Addy, Cheryl L.; Garrison, Carol Z.

2005-01-01

Objective: To study the association of family and social risk factors with psychopathology in a longitudinal study of adolescents. Method: From 1986 to 1988, 3,419 seventh through ninth graders were screened with the Center for Epidemiologic Studies Depression Scale. The top decile scorers and a random sample of the remainder were interviewed…

A comparison of three random effects approaches to analyze repeated bounded outcome scores with an application in a stroke revalidation study.

PubMed

Molas, Marek; Lesaffre, Emmanuel

2008-12-30

Discrete bounded outcome scores (BOS), i.e. discrete measurements that are restricted on a finite interval, often occur in practice. Examples are compliance measures, quality of life measures, etc. In this paper we examine three related random effects approaches to analyze longitudinal studies with a BOS as response: (1) a linear mixed effects (LM) model applied to a logistic transformed modified BOS; (2) a model assuming that the discrete BOS is a coarsened version of a latent random variable, which after a logistic-normal transformation, satisfies an LM model; and (3) a random effects probit model. We consider also the extension whereby the variability of the BOS is allowed to depend on covariates. The methods are contrasted using a simulation study and on a longitudinal project, which documents stroke rehabilitation in four European countries using measures of motor and functional recovery. Copyright 2008 John Wiley & Sons, Ltd.

Mapping concentrations of posttraumatic stress and depression trajectories following Hurricane Ike

PubMed Central

Gruebner, Oliver; Lowe, Sarah R.; Tracy, Melissa; Joshi, Spruha; Cerdá, Magdalena; Norris, Fran H.; Subramanian, S. V.; Galea, Sandro

2016-01-01

We investigated geographic concentration in elevated risk for a range of postdisaster trajectories of chronic posttraumatic stress symptom (PTSS) and depression symptoms in a longitudinal study (N = 561) of a Hurricane Ike affected population in Galveston and Chambers counties, TX. Using an unadjusted spatial scan statistic, we detected clusters of elevated risk of PTSS trajectories, but not depression trajectories, on Galveston Island. We then tested for predictors of membership in each trajectory of PTSS and depression (e.g., demographic variables, trauma exposure, social support), not taking the geographic nature of the data into account. After adjusting for significant predictors in the spatial scan statistic, we noted that spatial clusters of PTSS persisted and additional clusters of depression trajectories emerged. This is the first study to show that longitudinal trajectories of postdisaster mental health problems may vary depending on the geographic location and the individual- and community-level factors present at these locations. Such knowledge is crucial to identifying vulnerable regions and populations within them, to provide guidance for early responders, and to mitigate mental health consequences through early detection of mental health needs in the population. As human-made disasters increase, our approach may be useful also in other regions in comparable settings worldwide. PMID:27558011

Mapping concentrations of posttraumatic stress and depression trajectories following Hurricane Ike.

PubMed

Gruebner, Oliver; Lowe, Sarah R; Tracy, Melissa; Joshi, Spruha; Cerdá, Magdalena; Norris, Fran H; Subramanian, S V; Galea, Sandro

2016-08-25

We investigated geographic concentration in elevated risk for a range of postdisaster trajectories of chronic posttraumatic stress symptom (PTSS) and depression symptoms in a longitudinal study (N = 561) of a Hurricane Ike affected population in Galveston and Chambers counties, TX. Using an unadjusted spatial scan statistic, we detected clusters of elevated risk of PTSS trajectories, but not depression trajectories, on Galveston Island. We then tested for predictors of membership in each trajectory of PTSS and depression (e.g., demographic variables, trauma exposure, social support), not taking the geographic nature of the data into account. After adjusting for significant predictors in the spatial scan statistic, we noted that spatial clusters of PTSS persisted and additional clusters of depression trajectories emerged. This is the first study to show that longitudinal trajectories of postdisaster mental health problems may vary depending on the geographic location and the individual- and community-level factors present at these locations. Such knowledge is crucial to identifying vulnerable regions and populations within them, to provide guidance for early responders, and to mitigate mental health consequences through early detection of mental health needs in the population. As human-made disasters increase, our approach may be useful also in other regions in comparable settings worldwide.

Influence of fiber packing structure on permeability

NASA Technical Reports Server (NTRS)

Cai, Zhong; Berdichevsky, Alexander L.

1993-01-01

The study on the permeability of an aligned fiber bundle is the key building block in modeling the permeability of advanced woven and braided preforms. Available results on the permeability of fiber bundles in the literature show that a substantial difference exists between numerical and analytical calculations on idealized fiber packing structures, such as square and hexagonal packing, and experimental measurements on practical fiber bundles. The present study focuses on the variation of the permeability of a fiber bundle under practical process conditions. Fiber bundles are considered as containing openings and fiber clusters within the bundle. Numerical simulations on the influence of various openings on the permeability were conducted. Idealized packing structures are used, but with introduced openings distributed in different patterns. Both longitudinal and transverse flow are considered. The results show that openings within the fiber bundle have substantial effect on the permeability. In the longitudinal flow case, the openings become the dominant flow path. In the transverse flow case, the fiber clusters reduce the gap sizes among fibers. Therefore the permeability is greatly influenced by these openings and clusters, respectively. In addition to the porosity or fiber volume fraction, which is commonly used in the permeability expression, another fiber bundle status parameter, the ultimate fiber volume fraction, is introduced to capture the disturbance within a fiber bundle.

Effects of quality improvement in health facilities and community mobilization through women's groups on maternal, neonatal and perinatal mortality in three districts of Malawi: MaiKhanda, a cluster randomized controlled effectiveness trial.

PubMed

Colbourn, Tim; Nambiar, Bejoy; Bondo, Austin; Makwenda, Charles; Tsetekani, Eric; Makonda-Ridley, Agnes; Msukwa, Martin; Barker, Pierre; Kotagal, Uma; Williams, Cassie; Davies, Ros; Webb, Dale; Flatman, Dorothy; Lewycka, Sonia; Rosato, Mikey; Kachale, Fannie; Mwansambo, Charles; Costello, Anthony

2013-09-01

Maternal, perinatal and neonatal mortality remains high in low-income countries. We evaluated community and facility-based interventions to reduce deaths in three districts of Malawi. We evaluated a rural participatory women's group community intervention (CI) and a quality improvement intervention at health centres (FI) via a two-by-two factorial cluster randomized controlled trial. Consenting pregnant women were followed-up to 2 months after birth using key informants. Primary outcomes were maternal, perinatal and neonatal mortality. Clusters were health centre catchment areas assigned using stratified computer-generated randomization. Following exclusions, including non-birthing facilities, 61 clusters were analysed: control (17 clusters, 4912 births), FI (15, 5335), CI (15, 5080) and FI + CI (14, 5249). This trial was registered as International Standard Randomised Controlled Trial [ISRCTN18073903]. Outcomes for 14,576 and 20,576 births were recorded during baseline (June 2007-September 2008) and intervention (October 2008-December 2010) periods. For control, FI, CI and FI + CI clusters neonatal mortality rates were 34.0, 28.3, 29.9 and 27.0 neonatal deaths per 1000 live births and perinatal mortality rates were 56.2, 55.1, 48.0 and 48.4 per 1000 births, during the intervention period. Adjusting for clustering and stratification, the neonatal mortality rate was 22% lower in FI + CI than control clusters (OR = 0.78, 95% CI 0.60-1.01), and the perinatal mortality rate was 16% lower in CI clusters (OR = 0.84, 95% CI 0.72-0.97). We did not observe any intervention effects on maternal mortality. Despite implementation problems, a combined community and facility approach using participatory women's groups and quality improvement at health centres reduced newborn mortality in rural Malawi.

Effects of quality improvement in health facilities and community mobilization through women’s groups on maternal, neonatal and perinatal mortality in three districts of Malawi: MaiKhanda, a cluster randomized controlled effectiveness trial

PubMed Central

Colbourn, Tim; Nambiar, Bejoy; Bondo, Austin; Makwenda, Charles; Tsetekani, Eric; Makonda-Ridley, Agnes; Msukwa, Martin; Barker, Pierre; Kotagal, Uma; Williams, Cassie; Davies, Ros; Webb, Dale; Flatman, Dorothy; Lewycka, Sonia; Rosato, Mikey; Kachale, Fannie; Mwansambo, Charles; Costello, Anthony

2016-01-01

Background Maternal, perinatal and neonatal mortality remains high in low-income countries. We evaluated community and facility-based interventions to reduce deaths in three districts of Malawi. Methods We evaluated a rural participatory women’s group community intervention (CI) and a quality improvement intervention at health centres (FI) via a two-by-two factorial cluster randomized controlled trial. Consenting pregnant women were followed-up to 2 months after birth using key informants. Primary outcomes were maternal, perinatal and neonatal mortality. Clusters were health centre catchment areas assigned using stratified computer-generated randomization. Following exclusions, including non-birthing facilities, 61 clusters were analysed: control (17 clusters, 4912 births), FI (15, 5335), CI (15, 5080) and FI + CI (14, 5249). This trial was registered as International Standard Randomised Controlled Trial [ISRCTN18073903]. Outcomes for 14 576 and 20 576 births were recorded during baseline (June 2007–September 2008) and intervention (October 2008–December 2010) periods. Results For control, FI, CI and FI + CI clusters neonatal mortality rates were 34.0, 28.3, 29.9 and 27.0 neonatal deaths per 1000 live births and perinatal mortality rates were 56.2, 55.1, 48.0 and 48.4 per 1000 births, during the intervention period. Adjusting for clustering and stratification, the neonatal mortality rate was 22% lower in FI + CI than control clusters (OR = 0.78, 95% CI 0.60–1.01), and the perinatal mortality rate was 16% lower in CI clusters (OR = 0.84, 95% CI 0.72–0.97). We did not observe any intervention effects on maternal mortality. Conclusions Despite implementation problems, a combined community and facility approach using participatory women’s groups and quality improvement at health centres reduced newborn mortality in rural Malawi. PMID:24030269

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

PubMed Central

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

2009-01-01

Traditional lot quality assurance sampling (LQAS) methods require simple random sampling to guarantee valid results. However, cluster sampling has been proposed to reduce the number of random starting points. This study uses simulations to examine the classification error of two such designs, a 67×3 (67 clusters of three observations) and a 33×6 (33 clusters of six observations) sampling scheme to assess the prevalence of global acute malnutrition (GAM). Further, we explore the use of a 67×3 sequential sampling scheme for LQAS classification of GAM prevalence. Results indicate that, for independent clusters with moderate intracluster correlation for the GAM outcome, the three sampling designs maintain approximate validity for LQAS analysis. Sequential sampling can substantially reduce the average sample size that is required for data collection. The presence of intercluster correlation can impact dramatically the classification error that is associated with LQAS analysis. PMID:20011037

Cluster Headache: Epidemiology, Pathophysiology, Clinical Features, and Diagnosis

PubMed Central

Wei, Diana Yi-Ting; Yuan Ong, Jonathan Jia; Goadsby, Peter James

2018-01-01

Cluster headache is a primary headache disorder affecting up to 0.1% of the population. Patients suffer from cluster headache attacks lasting from 15 to 180 min up to 8 times a day. The attacks are characterized by the severe unilateral pain mainly in the first division of the trigeminal nerve, with associated prominent unilateral cranial autonomic symptoms and a sense of agitation and restlessness during the attacks. The male-to-female ratio is approximately 2.5:1. Experimental, clinical, and neuroimaging studies have advanced our understanding of the pathogenesis of cluster headache. The pathophysiology involves activation of the trigeminovascular complex and the trigeminal-autonomic reflex and accounts for the unilateral severe headache, the prominent ipsilateral cranial autonomic symptoms. In addition, the circadian and circannual rhythmicity unique to this condition is postulated to involve the hypothalamus and suprachiasmatic nucleus. Although the clinical features are distinct, it may be misdiagnosed, with patients often presenting to the otolaryngologist or dentist with symptoms. The prognosis of cluster headache remains difficult to predict. Patients with episodic cluster headache can shift to chronic cluster headache and vice versa. Longitudinally, cluster headache tends to remit with age with less frequent bouts and more prolonged periods of remission in between bouts. PMID:29720812

Cluster Headache: Epidemiology, Pathophysiology, Clinical Features, and Diagnosis.

PubMed

Wei, Diana Yi-Ting; Yuan Ong, Jonathan Jia; Goadsby, Peter James

2018-04-01

Cluster headache is a primary headache disorder affecting up to 0.1% of the population. Patients suffer from cluster headache attacks lasting from 15 to 180 min up to 8 times a day. The attacks are characterized by the severe unilateral pain mainly in the first division of the trigeminal nerve, with associated prominent unilateral cranial autonomic symptoms and a sense of agitation and restlessness during the attacks. The male-to-female ratio is approximately 2.5:1. Experimental, clinical, and neuroimaging studies have advanced our understanding of the pathogenesis of cluster headache. The pathophysiology involves activation of the trigeminovascular complex and the trigeminal-autonomic reflex and accounts for the unilateral severe headache, the prominent ipsilateral cranial autonomic symptoms. In addition, the circadian and circannual rhythmicity unique to this condition is postulated to involve the hypothalamus and suprachiasmatic nucleus. Although the clinical features are distinct, it may be misdiagnosed, with patients often presenting to the otolaryngologist or dentist with symptoms. The prognosis of cluster headache remains difficult to predict. Patients with episodic cluster headache can shift to chronic cluster headache and vice versa. Longitudinally, cluster headache tends to remit with age with less frequent bouts and more prolonged periods of remission in between bouts.

Life history factors, personality and the social clustering of sexual experience in adolescents.

PubMed

van Leeuwen, Abram J; Mace, Ruth

2016-10-01

Adolescent sexual behaviour may show clustering in neighbourhoods, schools and friendship networks. This study aims to assess how experience with sexual intercourse clusters across the social world of adolescents and whether predictors implicated by life history theory or personality traits can account for its between-individual variation and social patterning. Using data on 2877 adolescents from the Avon Longitudinal Study of Parents and Children, we ran logistic multiple classification models to assess the clustering of sexual experience by approximately 17.5 years in schools, neighbourhoods and friendship networks. We examined how much clustering at particular levels could be accounted for by life history predictors and Big Five personality factors. Sexual experience exhibited substantial clustering in friendship networks, while clustering at the level of schools and neighbourhoods was minimal, suggesting a limited role for socio-ecological influences at those levels. While life history predictors did account for some variation in sexual experience, they did not explain clustering in friendship networks. Personality, especially extraversion, explained about a quarter of friends' similarity. After accounting for life history factors and personality, substantial unexplained similarity among friends remained, which may reflect a tendency to associate with similar individuals or the social transmission of behavioural norms.

Life history factors, personality and the social clustering of sexual experience in adolescents

PubMed Central

2016-01-01

Adolescent sexual behaviour may show clustering in neighbourhoods, schools and friendship networks. This study aims to assess how experience with sexual intercourse clusters across the social world of adolescents and whether predictors implicated by life history theory or personality traits can account for its between-individual variation and social patterning. Using data on 2877 adolescents from the Avon Longitudinal Study of Parents and Children, we ran logistic multiple classification models to assess the clustering of sexual experience by approximately 17.5 years in schools, neighbourhoods and friendship networks. We examined how much clustering at particular levels could be accounted for by life history predictors and Big Five personality factors. Sexual experience exhibited substantial clustering in friendship networks, while clustering at the level of schools and neighbourhoods was minimal, suggesting a limited role for socio-ecological influences at those levels. While life history predictors did account for some variation in sexual experience, they did not explain clustering in friendship networks. Personality, especially extraversion, explained about a quarter of friends' similarity. After accounting for life history factors and personality, substantial unexplained similarity among friends remained, which may reflect a tendency to associate with similar individuals or the social transmission of behavioural norms. PMID:27853543

WWC Review of the Report "Closing the Achievement Gap through Modification of Neurocognitive and Neuroendocrine Function: Results from a Cluster Randomized Controlled Trial of an Innovative Approach to the Education of Children in Kindergarten." What Works Clearinghouse Single Study Review

ERIC Educational Resources Information Center

What Works Clearinghouse, 2015

2015-01-01

In the 2014 report, "Closing the Achievement Gap Through Modification of Neurocognitive and Neuroendocrine Function: Results from a Cluster Randomized Controlled Trial of an Innovative Approach to the Education of Children in Kindergarten," researchers examined the impacts of "Tools of the Mind" on cognitive and academic…

Chemical Distances for Percolation of Planar Gaussian Free Fields and Critical Random Walk Loop Soups

NASA Astrophysics Data System (ADS)

Ding, Jian; Li, Li

2018-05-01

We initiate the study on chemical distances of percolation clusters for level sets of two-dimensional discrete Gaussian free fields as well as loop clusters generated by two-dimensional random walk loop soups. One of our results states that the chemical distance between two macroscopic annuli away from the boundary for the random walk loop soup at the critical intensity is of dimension 1 with positive probability. Our proof method is based on an interesting combination of a theorem of Makarov, isomorphism theory, and an entropic repulsion estimate for Gaussian free fields in the presence of a hard wall.

Chemical Distances for Percolation of Planar Gaussian Free Fields and Critical Random Walk Loop Soups

NASA Astrophysics Data System (ADS)

Ding, Jian; Li, Li

2018-06-01

We initiate the study on chemical distances of percolation clusters for level sets of two-dimensional discrete Gaussian free fields as well as loop clusters generated by two-dimensional random walk loop soups. One of our results states that the chemical distance between two macroscopic annuli away from the boundary for the random walk loop soup at the critical intensity is of dimension 1 with positive probability. Our proof method is based on an interesting combination of a theorem of Makarov, isomorphism theory, and an entropic repulsion estimate for Gaussian free fields in the presence of a hard wall.

Assessment of three dead detector correction methods for cone-beam computed tomography

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

Nelms, David W.; Shukla, Hemant I.; Nixon, Earl

Purpose: Dead detectors due to manufacturing defects or radiation damage in the electronic portal imaging devices (EPIDs) used for cone-beam computed tomography (CBCT) can lead to image degradation and ring artifacts. In this work three dead detector correction methods were assessed using megavoltage CBCT (MVCBCT) as a test system, with the goals of assessing the relative effectiveness of the three methods and establishing the conditions for which they fail. Methods: MVCBCT projections acquired with four linacs at 8 and 60 MU (monitor units) were degraded with varying percentages (2%-95%) of randomly distributed dead single detectors (RDSs), randomly distributed dead detectormore » clusters (RDCs) of 2 mm diameter, and nonrandomly distributed dead detector disks (NRDDs) of varying diameter (4-16 mm). Correction algorithms were bidirectional linear interpolation (BLI), quad-directional linear interpolation (QLI), and a Laplacian solution (LS) method. Correction method failure was defined to occur if ring artifacts were present in the reconstructed phantom images from any linac or if the modulation transfer function (MTF) for any linac dropped below baseline with a p value, calculated with the two sample t test, of less than 0.01. Results: All correction methods failed at the same or lower RDC/RDS percentages and NRDD diameters for the 60 MU as for the 8 MU cases. The LS method tended to outperform or match the BLI and QLI methods. If ring artifacts anywhere in the images were considered unacceptable, the LS method failed for 60 MU at >33% RDS, >2% RDC, and >4 mm NRDD. If ring artifacts within 4 mm longitudinally of the phantom section interfaces were considered acceptable, the LS method failed for 60 MU at >90% RDS, >80% RDC, and >4 mm NRDD. LS failed due to MTF drop for 60 MU at >50% RDS, >25% RDC, and >4 mm NRDD. Conclusions: The LS method is superior to the BLI and QLI methods, and correction algorithm effectiveness decreases as imaging dose increases. All correction methods failed first due to ring artifacts and second due to MTF drop. If ring artifacts in axial slices within a 4 mm longitudinal distance from phantom section interfaces are acceptable, statistically significant loss in spatial resolution does not occur until over 25% of the EPID is covered in randomly distributed dead detectors, or NRDDs of 4 mm diameter are present.« less

Differential Susceptibility to Prevention: GABAergic, Dopaminergic, and Multilocus Effects

ERIC Educational Resources Information Center

Brody, Gene H.; Chen, Yi-fu; Beach, Steven R. H.

2013-01-01

Background: Randomized prevention trials provide a unique opportunity to test hypotheses about the interaction of genetic predispositions with contextual processes to create variations in phenotypes over time. Methods: Using two longitudinal, randomized prevention trials, molecular genetic and alcohol use outcome data were gathered from more than…

Left ventricular function in relation to chronic residential air pollution in a general population

PubMed Central

Yang, Wen-Yi; Zhang, Zhen-Yu; Thijs, Lutgarde; Bijnens, Esmée M; Janssen, Bram G; Vanpoucke, Charlotte; Lefebvre, Wouter; Cauwenberghs, Nicholas; Wei, Fang-Fei; Luttun, Aernout; Verhamme, Peter; Van Hecke, Etienne; Kuznetsova, Tatiana; D’hooge, Jan; Nawrot, Tim S

2017-01-01

Background In view of the increasing heart failure epidemic and awareness of the adverse impact of environmental pollution on human health, we investigated the association of left ventricular structure and function with air pollutants in a general population. Methods In 671 randomly recruited Flemish (51.7% women; mean age, 50.4 years) we echocardiographically assessed left ventricular systolic strain and strain rate and the early and late peak velocities of transmitral blood flow and mitral annular movement (2005−2009). Using subject-level data, left ventricular function was cross-sectionally correlated with residential long-term exposure to air pollutants, including black carbon, PM2.5, PM10 (particulate matter) and nitrogen dioxide (NO2), while accounting for clustering by residential address and confounders. Results Annual exposures to black carbon, PM2.5, PM10 and NO2 averaged 1.19, 13.0, 17.7, and 16.8 µg/m3. Systolic left ventricular function was worse (p ≤ 0.027) with higher black carbon, PM2.5, PM10 and NO2 with association sizes per interquartile interval increment ranging from −0.339 to −0.458% for longitudinal strain and from −0.033 to −0.049 s−1 for longitudinal strain rate. Mitral E and a′ peak velocities were lower (p ≤ 0.021) with higher black carbon, PM2.5 and PM10 with association sizes ranging from −1.727 to −1.947 cm/s and from −0.175 to −0.235 cm/s, respectively. In the geographic analysis, the systolic longitudinal strain sided with gradients in air pollution. The path analysis identified systemic inflammation as a possible mediator of associations with black carbon. Conclusions Long-term low-level air pollution is associated with subclinical impairment of left ventricular performance and might be a risk factor for heart failure. PMID:28617090

Recurrent star-spot activity and differential rotation in KIC 11560447

NASA Astrophysics Data System (ADS)

Özavcı, I.; Şenavcı, H. V.; Işık, E.; Hussain, G. A. J.; O'Neal, D.; Yılmaz, M.; Selam, S. O.

2018-03-01

We present a detailed analysis of surface inhomogeneities on the K1-type subgiant component of the rapidly rotating eclipsing binary KIC 11560447, using high-precision Kepler light curves spanning nearly 4 yr, which corresponds to about 2800 orbital revolutions. We determine the system parameters precisely, using high-resolution spectra from the 2.1-m Otto Struve Telescope at the McDonald Observatory. We apply the maximum entropy method to reconstruct the relative longitudinal spot occupancy. Our numerical tests show that the procedure can recover large-scale random distributions of individually unresolved spots, and it can track the phase migration of up to three major spot clusters. By determining the drift rates of various spotted regions in orbital longitude, we suggest a way to constrain surface differential rotation and we show that the results are consistent with periodograms. The K1IV star exhibits two mildly preferred longitudes of emergence, indications of solar-like differential rotation, and a 0.5-1.3-yr recurrence period in star-spot emergence, accompanied by a secular increase in the axisymmetric component of spot occupancy.

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…

On the design and analysis of clinical trials with correlated outcomes

PubMed Central

Follmann, Dean; Proschan, Michael

2014-01-01

SUMMARY The convention in clinical trials is to regard outcomes as independently distributed, but in some situations they may be correlated. For example, in infectious diseases, correlation may be induced if participants have contact with a common infectious source, or share hygienic tips that prevent infection. This paper discusses the design and analysis of randomized clinical trials that allow arbitrary correlation among all randomized volunteers. This perspective generalizes the traditional perspective of strata, where patients are exchangeable within strata, and independent across strata. For theoretical work, we focus on the test of no treatment effect μ1 − μ0 = 0 when the n dimensional vector of outcomes follows a Gaussian distribution with known n × n covariance matrix Σ, where the half randomized to treatment (placebo) have mean response μ1 (μ0). We show how the new test corresponds to familiar tests in simple situations for independent, exchangeable, paired, and clustered data. We also discuss the design of trials where Σ is known before or during randomization of patients and evaluate randomization schemes based on such knowledge. We provide two complex examples to illustrate the method, one for a study of 23 family clusters with cardiomyopathy, the other where the malaria attack rates vary within households and clusters of households in a Malian village. PMID:25111420

Mixture Modeling: Applications in Educational Psychology

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Hodis, Flaviu A.

2016-01-01

Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are…

Quantum Dynamics of Helium Clusters

DTIC Science & Technology

1993-03-01

the structure of both these and the HeN clusters in the body fixed frame by computing principal moments of inertia, thereby avoiding the...8217 of helium clusters, with the modification that we subtract 0.96 K from the computed values so that lor sufficiently large clusters we recover the...phonon spectrum of liquid He. To get a picture of these spectra one needs to compute the structure functions 51. Monte Carlo random walk simulations

A multifaceted intervention to narrow the evidence-based gap in the treatment of acute coronary syndromes: rationale and design of the Brazilian Intervention to Increase Evidence Usage in Acute Coronary Syndromes (BRIDGE-ACS) cluster-randomized trial.

PubMed

Berwanger, Otávio; Guimarães, Hélio P; Laranjeira, Ligia N; Cavalcanti, Alexandre B; Kodama, Alessandra; Zazula, Ana Denise; Santucci, Eliana; Victor, Elivane; Flato, Uri A; Tenuta, Marcos; Carvalho, Vitor; Mira, Vera Lucia; Pieper, Karen S; Mota, Luiz Henrique; Peterson, Eric D; Lopes, Renato D

2012-03-01

Translating evidence into clinical practice in the management of acute coronary syndromes (ACS) is challenging. Few ACS quality improvement interventions have been rigorously evaluated to determine their impact on patient care and clinical outcomes. We designed a pragmatic, 2-arm, cluster-randomized trial involving 34 clusters (Brazilian public hospitals). Clusters were randomized to receive a multifaceted quality improvement intervention (experimental group) or routine practice (control group). The 6-month educational intervention included reminders, care algorithms, a case manager, and distribution of educational materials to health care providers. The primary end point was a composite of evidence-based post-ACS therapies within 24 hours of admission, with the secondary measure of major cardiovascular clinical events (death, nonfatal myocardial infarction, nonfatal cardiac arrest, and nonfatal stroke). Prescription of evidence-based therapies at hospital discharge were also evaluated as part of the secondary outcomes. All analyses were performed by the intention-to-treat principle and took the cluster design into account using individual-level regression modeling (generalized estimating equations). If proven effective, this multifaceted intervention would have wide use as a means of promoting optimal use of evidence-based interventions for the management of ACS. Copyright © 2012 Mosby, Inc. All rights reserved.

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Choosing appropriate analysis methods for cluster randomised cross-over trials with a binary outcome.

PubMed

Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C

2017-01-30

In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

RANDOMNESS of Numbers DEFINITION(QUERY:WHAT? V HOW?) ONLY Via MAXWELL-BOLTZMANN CLASSICAL-Statistics(MBCS) Hot-Plasma VS. Digits-Clumping Log-Law NON-Randomness Inversion ONLY BOSE-EINSTEIN QUANTUM-Statistics(BEQS) .

NASA Astrophysics Data System (ADS)

Siegel, Z.; Siegel, Edward Carl-Ludwig

2011-03-01

RANDOMNESS of Numbers cognitive-semantics DEFINITION VIA Cognition QUERY: WHAT???, NOT HOW?) VS. computer-``science" mindLESS number-crunching (Harrel-Sipser-...) algorithmics Goldreich "PSEUDO-randomness"[Not.AMS(02)] mea-culpa is ONLY via MAXWELL-BOLTZMANN CLASSICAL-STATISTICS(NOT FDQS!!!) "hot-plasma" REPULSION VERSUS Newcomb(1881)-Weyl(1914;1916)-Benford(1938) "NeWBe" logarithmic-law digit-CLUMPING/ CLUSTERING NON-Randomness simple Siegel[AMS Joint.Mtg.(02)-Abs. # 973-60-124] algebraic-inversion to THE QUANTUM and ONLY BEQS preferentially SEQUENTIALLY lower-DIGITS CLUMPING/CLUSTERING with d = 0 BEC, is ONLY VIA Siegel-Baez FUZZYICS=CATEGORYICS (SON OF TRIZ)/"Category-Semantics"(C-S), latter intersection/union of Lawvere(1964)-Siegel(1964)] category-theory (matrix: MORPHISMS V FUNCTORS) "+" cognitive-semantics'' (matrix: ANTONYMS V SYNONYMS) yields Siegel-Baez FUZZYICS=CATEGORYICS/C-S tabular list-format matrix truth-table analytics: MBCS RANDOMNESS TRUTH/EMET!!!

Longitudinal Examination of Aggression and Study Skills from Middle to High School: Implications for Dropout Prevention

ERIC Educational Resources Information Center

Orpinas, Pamela; Raczynski, Katherine; Hsieh, Hsien-Lin; Nahapetyan, Lusine; Horne, Arthur M.

2018-01-01

Background: High school completion provides health and economic benefits. The purpose of this study is to describe dropout rates based on longitudinal trajectories of aggression and study skills using teacher ratings. Methods: The sample consisted of 620 randomly selected sixth graders. Every year from Grade 6 to 12, a teacher completed a…

Contemporary Options for Longitudinal Follow-Up: Lessons Learned from a Cohort of Urban Adolescents

ERIC Educational Resources Information Center

Tobler, Amy L.; Komro, Kelli A.

2011-01-01

This study reports efforts to locate and survey participants in Project Northland Chicago (PNC), a longitudinal, group-randomized trial of an alcohol preventive intervention for racial/ethnic minority, urban, early-adolescents, 3-4 years following the end of the intervention. Data were collected annually among students from 6th-8th grade and then…

A Correlated Random Effects Model for Nonignorable Missing Data in Value-Added Assessment of Teacher Effects

ERIC Educational Resources Information Center

Karl, Andrew T.; Yang, Yan; Lohr, Sharon L.

2013-01-01

Value-added models have been widely used to assess the contributions of individual teachers and schools to students' academic growth based on longitudinal student achievement outcomes. There is concern, however, that ignoring the presence of missing values, which are common in longitudinal studies, can bias teachers' value-added scores.…

Computer Assisted English Language Learning in Costa Rican Elementary Schools: An Experimental Study

ERIC Educational Resources Information Center

Alvarez-Marinelli, Horacio; Blanco, Marta; Lara-Alecio, Rafael; Irby, Beverly J.; Tong, Fuhui; Stanley, Katherine; Fan, Yinan

2016-01-01

This study presents first-year findings of a 25-week longitudinal project derived from a two-year longitudinal randomized trial study at the elementary school level in Costa Rica on effective computer-assisted language learning (CALL) approaches in an English as a foreign language (EFL) setting. A pre-test-post-test experimental group design was…

Bridging the Gap: A Longitudinal Study of the Relationship between Pedagogical Continuity and Early Chinese Literacy Acquisition

ERIC Educational Resources Information Center

Li, Hui; Rao, Nirmala; Tse, Shek Kam

2011-01-01

This longitudinal study examined the relationship between pedagogical continuity in literacy education and early literacy development by comparing Chinese children in Hong Kong and Shenzhen. Stratified random sampling was used to select 24 preschool and Primary 1 classes in four communities catering to middle-class families in each city. The 24…

A Study of Ontogenetic and Generational Change in Adolescent Personality by Means of Multivariate Longitudinal Sequences: Phase II. Final Report.

ERIC Educational Resources Information Center

Nesselroade, John R.; Baltes, Paul B.

Assessment of the relationship between ontogenetic (individual) and generational (historical) change in adolescent personality development was the focus of this study. The total sample included 1000 male and female adolescents (ages 13-18) randomly drawn from 32 public school systems in West Virginia following a design using longitudinal sequences…

The Longitudinal Impact of a Universal School-Based Social-Emotional and Literacy Intervention on Classroom Climate and Teacher Processes and Practices

ERIC Educational Resources Information Center

Brown, Joshua L.; Jones, Stephanie M.; Aber, J. Lawrence

2010-01-01

This presentation capitalizes on a three-year, longitudinal, school-randomized trial of the 4Rs Program, a comprehensive, school-based social-emotional and literacy program for elementary schools, to test intervention induced changes in features of classroom climate and key dimensions of teacher affective and pedagogical processes and practices…

The Problem of “Just for Fun”: Patterns of Use Situations among Active Club Drug Users

PubMed Central

Starks, Tyrel J.; Golub, Sarit; Kelly, Brian C.; Parsons, Jeffrey T.

2010-01-01

Existing research has demonstrated the significance of situational antecedents to substance use. The current study used a cluster analytic approach to identify groups of club drug users who report using substances in similar situations (assessed by the Inventory of Drug Taking Situations) with longitudinal data from 400 active drug users. A three-cluster solution emerged in baseline data and was replicated in 12-month follow-up data. Groups were identified as Situationally Restricted, Pleasure Driven, and Situationally Broad users. Group differences were observed on measures of mental health, attitudes towards substance use, amount of substance use, and rates of substance dependence. Cluster membership predicted substance dependence after controlling for past dependence, current use, and current depression/anxiety. PMID:20696530

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.

Dental caries clusters among adolescents.

PubMed

Warren, John J; Van Buren, John M; Levy, Steven M; Marshall, Teresa A; Cavanaugh, Joseph E; Curtis, Alexandra M; Kolker, Justine L; Weber-Gasparoni, Karin

2017-12-01

There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioural data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For this study, only participants with decayed and filled surface (DFS) caries data at ages 9, 13 and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward's hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioural data from 9 to 17 years. Model selection was based on the akaike information criterion (AIC). Several different trajectory schemes were considered, and a three-trajectory scheme-no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109)-was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favoured models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. The use of a clustering algorithm and use of Akaike's Information Criterion (AIC) to determine the best representation of the data were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Is Scientifically Based Reading Instruction Effective for Students with Below-Average IQs?

ERIC Educational Resources Information Center

Allor, Jill H.; Mathes, Patricia G.; Roberts, J. Kyle; Cheatham, Jennifer P.; Al Otaiba, Stephanie

2014-01-01

This longitudinal randomized-control trial investigated the effectiveness of scientifically based reading instruction for students with IQs ranging from 40 to 80, including students with intellectual disability (ID). Students were randomly assigned into treatment (n = 76) and contrast (n = 65) groups. Students in the treatment group received…

Differential Cost Avoidance and Successful Criminal Careers: Random or Rational?

ERIC Educational Resources Information Center

Kazemian, Lila; Le Blanc, Marc

2007-01-01

Using a sample of adjudicated French Canadian males from the Montreal Two Samples Longitudinal Study, this article investigates individual and social characteristics associated with differential cost avoidance. The main objective of this study is to determine whether such traits are randomly distributed across differential degrees of cost…

Aircraft adaptive learning control

NASA Technical Reports Server (NTRS)

Lee, P. S. T.; Vanlandingham, H. F.

1979-01-01

The optimal control theory of stochastic linear systems is discussed in terms of the advantages of distributed-control systems, and the control of randomly-sampled systems. An optimal solution to longitudinal control is derived and applied to the F-8 DFBW aircraft. A randomly-sampled linear process model with additive process and noise is developed.

Evaluation of Effectiveness and Cost‐Effectiveness of a Clinical Decision Support System in Managing Hypertension in Resource Constrained Primary Health Care Settings: Results From a Cluster Randomized Trial

PubMed Central

Anchala, Raghupathy; Kaptoge, Stephen; Pant, Hira; Di Angelantonio, Emanuele; Franco, Oscar H.; Prabhakaran, D.

2015-01-01

Background Randomized control trials from the developed world report that clinical decision support systems (DSS) could provide an effective means to improve the management of hypertension (HTN). However, evidence from developing countries in this regard is rather limited, and there is a need to assess the impact of a clinical DSS on managing HTN in primary health care center (PHC) settings. Methods and Results We performed a cluster randomized trial to test the effectiveness and cost‐effectiveness of a clinical DSS among Indian adult hypertensive patients (between 35 and 64 years of age), wherein 16 PHC clusters from a district of Telangana state, India, were randomized to receive either a DSS or a chart‐based support (CBS) system. Each intervention arm had 8 PHC clusters, with a mean of 102 hypertensive patients per cluster (n=845 in DSS and 783 in CBS groups). Mean change in systolic blood pressure (SBP) from baseline to 12 months was the primary endpoint. The mean difference in SBP change from baseline between the DSS and CBS at the 12th month of follow‐up, adjusted for age, sex, height, waist, body mass index, alcohol consumption, vegetable intake, pickle intake, and baseline differences in blood pressure, was −6.59 mm Hg (95% confidence interval: −12.18 to −1.42; P=0.021). The cost‐effective ratio for CBS and DSS groups was $96.01 and $36.57 per mm of SBP reduction, respectively. Conclusion Clinical DSS are effective and cost‐effective in the management of HTN in resource‐constrained PHC settings. Clinical Trial Registration URL: http://www.ctri.nic.in. Unique identifier: CTRI/2012/03/002476. PMID:25559011

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Who Benefits from Gender Responsive Treatment? Accounting for Abuse History on Longitudinal Outcomes for Women in Prison.

PubMed

Saxena, Preeta; Messina, Nena; Grella, Christine E

2014-04-01

This study explores outcome variation among women offenders who participated in gender-responsive substance abuse treatment (GRT). In order to identify subgroups of participants that may differentially benefit from this treatment, secondary analyses examined the interaction between randomization into GRT and a history of abuse (physical/sexual) on depression and number of substances used post- treatment. The sample consisted of 115 incarcerated women assessed at baseline and 6- and 12-months post parole. Longitudinal regression showed that women reporting abuse randomized into GRT had significantly reduced odds of depression ( OR = .29, p < .05, 95% CI = .10 - .86) and lowered rates of number of substances used ( IRR = .52, p < .05, 95% CI = 0.28-0.98), in comparison to those who reported abuse and were randomized to the non-GRT group. GRT for women offenders who have experienced prior abuse would maximize the benefits of the trauma-informed, gender-sensitive intervention.

Comparison of an alternative schedule of extended care contacts to a self-directed control: a randomized trial of weight loss maintenance.

PubMed

Dutton, Gareth R; Gowey, Marissa A; Tan, Fei; Zhou, Dali; Ard, Jamy; Perri, Michael G; Lewis, Cora E

2017-08-15

Behavioral interventions for obesity produce clinically meaningful weight loss, but weight regain following treatment is common. Extended care programs attenuate weight regain and improve weight loss maintenance. However, less is known about the most effective ways to deliver extended care, including contact schedules. We compared the 12-month weight regain of an extended care program utilizing a non-conventional, clustered campaign treatment schedule and a self-directed program among individuals who previously achieved ≥5% weight reductions. Participants (N = 108; mean age = 51.6 years; mean weight = 92.6 kg; 52% African American; 95% female) who achieved ≥5% weight loss during an initial 16-week behavioral obesity treatment were randomized into a 2-arm, 12-month extended care trial. A clustered campaign condition included 12 group-based visits delivered in three, 4-week clusters. A self-directed condition included provision of the same printed intervention materials but no additional treatment visits. The study was conducted in a U.S. academic medical center from 2011 to 2015. Prior to randomization, participants lost an average of -7.55 ± 3.04 kg. Participants randomized to the 12-month clustered campaign program regained significantly less weight (0.35 ± 4.62 kg) than self-directed participants (2.40 ± 3.99 kg), which represented a significant between-group difference of 2.28 kg (p = 0.0154) after covariate adjustments. This corresponded to maintaining 87% and 64% of lost weight in the clustered campaign and self-directed conditions, respectively, which was a significant between-group difference of 29% maintenance of lost weight after covariate adjustments, p = 0.0396. In this initial test of a clustered campaign treatment schedule, this novel approach effectively promoted 12-month maintenance of lost weight. Future trials should directly compare the clustered campaigns with conventional (e.g., monthly) extended care schedules. Clinicaltrials.gov NCT02487121 . Registered 06/26/2015 (retrospectively registered).

The Statistical Power of the Cluster Randomized Block Design with Matched Pairs--A Simulation Study

ERIC Educational Resources Information Center

Dong, Nianbo; Lipsey, Mark

2010-01-01

This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from…

Optical amplification of photothermal therapy with gold nanoparticles and nanoclusters

NASA Astrophysics Data System (ADS)

Khlebtsov, Boris; Zharov, Vladimir; Melnikov, Andrei; Tuchin, Valery; Khlebtsov, Nikolai

2006-10-01

Recently, several groups (Anderson, Halas, Zharov, and their co-workers, 2003; El-Sayed and co-workers, 2006) demonstrated, through pioneering results, the great potential of photothermal (PT) therapy for the selective treatment of cancer cells, bacteria, viruses, and DNA targeted with gold nanospheres, nanoshells, nanorods, and nanosphere clusters. However, the current understanding of the relationship between the nanoparticle/cluster parameters (size, shape, particle/cluster structure, etc) and the efficiency of PT therapy is limited. Here, we report theoretical simulations aimed at finding the optimal single-particle and cluster structures to achieve its maximal absorption, which is crucial for PT therapeutic effects. To characterize the optical amplification in laser-induced thermal effects, we introduce relevant parameters such as the ratio of the absorption cross section to the gold mass of a single-particle structure and absorption amplification, defined as the ratio of cluster absorption to the total absorption of non-interacting particles. We consider the absorption efficiency of single nanoparticles (gold spheres, rods, and silica/gold nanoshells), linear chains, 2D lattice arrays, 3D random volume clusters, and the random aggregated N-particle ensembles on the outer surface of a larger dielectric sphere, which mimic aggregation of nanosphere bioconjugates on or within cancer cells. The cluster particles are bare or biopolymer-coated gold nanospheres. The light absorption of cluster structures is studied by using the generalized multiparticle Mie solution and the T-matrix method. The gold nanoshells with (silica core diameter)/(gold shell thickness) parameters of (50-100)/(3-8) nm and nanorods with minor/major sizes of (15-20)/(50-70) nm are shown to be more efficient PT labels and sensitizers than the equivolume solid single gold spheres. In the case of nanosphere clusters, the interparticle separations and the short linear-chain fragments are the main structural parameters determining the absorption efficiency and its spectral shifting to the red. Although we have not found a noticeable dependence of absorption amplification on the cluster sphere size, 20-40 nm particles are found to be most effective, in accordance with our experimental observations. The long-wavelength absorption efficiency of random clusters increases with the cluster particle number N at small N and reveals a saturation behaviour at N>20.

Study of the photon remnant in resolved photoproduction at HERA

NASA Astrophysics Data System (ADS)

Derrick, M.; Krakauer, D.; Magill, S.; Mikunas, D.; Musgrave, B.; Repond, J.; Stanek, R.; Talaga, R. L.; Zhang, H.; Ayad, R.; Bari, G.; Basile, M.; Bellagamba, L.; Boscherini, D.; Bruni, A.; Bruni, G.; Bruni, P.; Cara Romeo, G.; Castellini, G.; Chiarini, M.; Cifarelli, L.; Cindolo, F.; Contin, A.; Corradi, M.; Gialas, I.; Giusti, P.; Iacobucci, G.; Laurenti, G.; Levi, G.; Margotti, A.; Massam, T.; Nania, R.; Nemoz, C.; Palmonari, F.; Polini, A.; Sartorelli, G.; Timellini, R.; Zamora Garcia, Y.; Zichichi, A.; Bargende, A.; Crittenden, J.; Desch, K.; Diekmann, B.; Doeker, T.; Eckert, M.; Feld, L.; Frey, A.; Geerts, M.; Geitz, G.; Grothe, M.; Haas, T.; Hartmann, H.; Heinloth, K.; Hilger, E.; Jakob, H.-P.; Katz, U. F.; Mari, S. M.; Mass, A.; Mengel, S.; Mollen, J.; Paul, E.; Rembser, Ch; Schramm, D.; Stamm, J.; Wedemeyer, R.; Campbell-Robson, S.; Cassidy, A.; Dyce, N.; Foster, B.; George, S.; Gilmore, R.; Heath, G. P.; Heath, H. F.; Llewellyn, T. J.; Morgado, C. J. S.; Norman, D. J. P.; O'Mara, J. A.; Tapper, R. J.; Wilson, S. S.; Yoshida, R.; Rau, R. R.; Arneodo, M.; Iannotti, L.; Schioppa, M.; Susinno, G.; Bernstein, A.; Caldwell, A.; Cartiglia, N.; Parsons, J. A.; Ritz, S.; Sciulli, F.; Straub, P. B.; Wai, L.; Yang, S.; Zhu, Q.; Borzemski, P.; Chwastowski, J.; Eskreys, A.; Piotrzkowski, K.; Zachara, M.; Zawiejski, L.; Adamczyk, L.; Bednarek, B.; Jeleń, K.; Kisielewska, D.; Kowalski, T.; Rulikowska-Zarȩbska, E.; Suszycki, L.; Zajaç, J.; Kotański, A.; Przybycień, M.; Bauerdick, L. A. T.; Behrens, U.; Beier, H.; Bienlein, J. K.; Coldewey, C.; Deppe, O.; Desler, K.; Drews, G.; Flasiński, M.; Gilkinson, D. J.; Glasman, C.; Göttlicher, P.; Große-Knetter, J.; Gutjahr, B.; Hain, W.; Hasell, D.; Heßling, H.; Iga, Y.; Joos, P.; Kasemann, M.; Klanner, R.; Koch, W.; Köpke, L.; Kötz, U.; Kowalski, H.; Labs, J.; Ladage, A.; Löhr, B.; Löwe, M.; Lüke, D.; Mainusch, J.; Mańczak, O.; Monteiro, T.; Ng, J. S. T.; Nickel, S.; Notz, D.; Ohrenberg, K.; Roco, M.; Rohde, M.; Roldán, J.; Schneekloth, U.; Schulz, W.; Selonke, F.; Stiliaris, E.; Surrow, B.; Voß, T.; Westphal, D.; Wolf, G.; Youngman, C.; Zhou, J. F.; Grabosch, H. J.; Kharchilava, A.; Leich, A.; Mattingly, M. C. K.; Meyer, A.; Schlenstedt, S.; Wulff, N.; Barbagli, G.; Pelfer, P.; Anzivino, G.; Maccarrone, G.; De Pasquale, S.; Votano, L.; Bamberger, A.; Eisenhardt, S.; Freidhof, A.; Söldner-Rembold, S.; Schroeder, J.; Trefzger, T.; Brook, N. H.; Bussey, P. J.; Doyle, A. T.; Fleck, J. I.; Saxon, D. H.; Utley, M. L.; Wilson, A. S.; Dannemann, A.; Holm, U.; Horstmann, D.; Neumann, T.; Sinkus, R.; Wick, K.; Badura, E.; Burow, B. D.; Hagge, L.; Lohrmann, E.; Milewski, J.; Nakahata, M.; Pavel, N.; Poelz, G.; Schott, W.; Zetsche, F.; Bacon, T. C.; Butterworth, I.; Gallo, E.; Harris, V. L.; Hung, B. Y. H.; Long, K. R.; Miller, D. B.; Morawitz, P. P. O.; Prinias, A.; Sedgbeer, J. K.; Whitfield, A. F.; Mallik, U.; McCliment, E.; Wang, M. Z.; Wang, S. M.; Wu, J. T.; Zhang, Y.; Cloth, P.; Filges, D.; An, S. H.; Hong, S. M.; Nam, S. W.; Park, S. K.; Suh, M. H.; Yon, S. H.; Imlay, R.; Kartik, S.; Kim, H.-J.; McNeil, R. R.; Metcalf, W.; Nadendla, V. K.; Barreiro, F.; Cases, G.; Fernandez, J. P.; Graciani, R.; Hernández, J. M.; Hervás, L.; Labarga, L.; Martinez, M.; del Peso, J.; Puga, J.; Terron, J.; de Trocóniz, J. F.; Smith, G. R.; Corriveau, F.; Hanna, D. S.; Hartmann, J.; Hung, L. W.; Lim, J. N.; Matthews, C. G.; Patel, P. M.; Sinclair, L. E.; Stairs, D. G.; St. Laurent, M.; Ullmann, R.; Zacek, G.; Bashkirov, V.; Dolgoshein, B. A.; Stifutkin, A.; Bashindzhagyan, G. L.; Ermolov, P. F.; Gladilin, L. K.; Golubkov, Y. A.; Kobrin, V. D.; Kuzmin, V. A.; Proskuryakov, A. S.; Savin, A. A.; Shcheglova, L. M.; Solomin, A. N.; Zotov, N. P.; Botje, M.; Chlebana, F.; Dake, A.; Engelen, J.; de Kamps, M.; Kooijman, P.; Kruse, A.; Tiecke, H.; Verkerke, W.; Vreeswijk, M.; Wiggers, L.; de Wolf, E.; van Woudenberg, R.; Acosta, D.; Bylsma, B.; Durkin, L. S.; Honscheid, K.; Li, C.; Ling, T. Y.; McLean, K. W.; Murray, W. N.; Park, I. H.; Romanowski, T. A.; Seidlein, R.; Bailey, D. S.; Byrne, A.; Cashmore, R. J.; Cooper-Sarkar, A. M.; Devenish, R. C. E.; Harnew, N.; Lancaster, M.; Lindemann, L.; McFall, J. D.; Nath, C.; Noyes, V. A.; Quadt, A.; Tickner, J. R.; Uijterwaal, H.; Walczak, R.; Waters, D. S.; Wilson, F. F.; Yip, T.; Abbiendi, G.; Bertolin, A.; Brugnera, R.; Carlin, R.; Dal Corso, F.; De Giorgi, M.; Dosselli, U.; Limentani, S.; Morandin, M.; Posocco, M.; Stanco, L.; Stroili, R.; Voci, C.; Bulmahn, J.; Butterworth, J. M.; Feild, R. G.; Oh, B. Y.; Whitmore, J. J.; D'Agostini, G.; Marini, G.; Nigro, A.; Tassi, E.; Hart, J. C.; McCubbin, N. A.; Prytz, K.; Shah, T. P.; Short, T. L.; Barberis, E.; Dubbs, T.; Heusch, C.; Van Hook, M.; Hubbard, B.; Lockman, W.; Rahn, J. T.; Sadrozinski, H. F.-W.; Seiden, A.; Biltzinger, J.; Seifert, R. J.; Schwarzer, O.; Walenta, A. H.; Zech, G.; Abramowicz, H.; Briskin, G.; Dagan, S.; Levy, A.; Hasegawa, T.; Hazumi, M.; Ishii, T.; Kuze, M.; Mine, S.; Nagasawa, Y.; Nakao, M.; Suzuki, I.; Tokushuku, K.; Yamada, S.; Yamazaki, Y.; Chiba, M.; Hamatsu, R.; Hirose, T.; Homma, K.; Kitamura, S.; Nakamitsu, Y.; Yamauchi, K.; Cirio, R.; Costa, M.; Ferrero, M. I.; Lamberti, L.; Maselli, S.; Peroni, C.; Sacchi, R.; Solano, A.; Staiano, A.; Dardo, M.; Bailey, D. C.; Bandyopadhyay, D.; Benard, F.; Brkic, M.; Crombie, M. B.; Gingrich, D. M.; Hartner, G. F.; Joo, K. K.; Levman, G. M.; Martin, J. F.; Orr, R. S.; Sampson, C. R.; Teuscher, R. J.; Catterall, C. D.; Jones, T. W.; Kaziewicz, P. B.; Lane, J. B.; Saunders, R. L.; Shulman, J.; Blankenship, K.; Lu, B.; Mo, L. W.; Bogusz, W.; Charchuła, K.; Ciborowski, J.; Gajewski, J.; Grzelak, G.; Kasprzak, M.; Krzyżanowski, M.; Muchorowski, K.; Nowak, R. J.; Pawlak, J. M.; Tymieniecka, T.; Wróblewski, A. K.; Zakrzewski, J. A.; Żarnecki, A. F.; Adamus, M.; Eisenberg, Y.; Karshon, U.; Revel, D.; Zer-Zion, D.; Ali, I.; Badgett, W. F.; Behrens, B.; Dasu, S.; Fordham, C.; Foudas, C.; Goussiou, A.; Loveless, R. J.; Reeder, D. D.; Silverstein, S.; Smith, W. H.; Vaiciulis, A.; Wodarczyk, M.; Tsurugai, T.; Bhadra, S.; Cardy, M. L.; Fagerstroem, C.-P.; Frisken, W. R.; Furutani, K. M.; Khakzad, M.; Schmidke, W. B.; ZEUS Collaboration

1995-02-01

Photoproduction at HERA is studied in ep collisions, with the ZEUS detector, for γp centre-of-mass energies ranging from 130-270 GeV. A sample of events with two high- pT jets ( pT > 6 GeV, η < 1.6) and a third cluster in the approximate direction of the electron beam is isolated using a clustering algorithm. These events are mostly due to resolved photoproduction. The third cluster is identified as the photon remnant. Its properties, such as the transverse and longitudinal energy flows around the axis of the cluster, are consistent with those commonly attributed to jets, and in particular with those found for the two jets in these events. The mean value of the photon remnant pT with respect to the beam axis is measured to be 2.1 ± 0.2 GeV, which demonstrates substantial mean transverse momenta for the photon remnant.

On aggregation in CA models in biology

NASA Astrophysics Data System (ADS)

Alber, Mark S.; Kiskowski, Audi

2001-12-01

Aggregation of randomly distributed particles into clusters of aligned particles is modeled using a cellular automata (CA) approach. The CA model accounts for interactions between more than one type of particle, in which pressures for angular alignment with neighbors compete with pressures for grouping by cell type. In the case of only one particle type clusters tend to unite into one big cluster. In the case of several types of particles the dynamics of clusters is more complicated and for specific choices of parameters particle sorting occurs simultaneously with the formation of clusters of aligned particles.

Clustering and switching processes in semantic verbal fluency in the course of Alzheimer's disease subjects: results from the PAQUID longitudinal study.

PubMed

Raoux, Nadine; Amieva, Hélène; Le Goff, Mélanie; Auriacombe, Sophie; Carcaillon, Laure; Letenneur, Luc; Dartigues, Jean-François

2008-10-01

Reduced semantic fluency performances have been reported in the preclinical phase of Alzheimer's disease (AD). To investigate the cognitive processes underlying this early deficit, this study analyzed the verbal production of predemented subjects for the animals category with the qualitative parameters related to clustering (i.e. the ability to generate words belonging to semantic subcategories of animals) and switching (i.e. the ability to shift from one subcategory to another) proposed by Troyer. This qualitative analysis was applied to the PAQUID (Personnes Agées QUID) cohort, a 17-year longitudinal population-based study. The performances on the animal verbal fluency task of 51 incident cases of possible and probable AD were analyzed at the onset of dementia, 2 years and 5 years before dementia onset. Each case was matched for age, sex and education to two control subjects leading to a sample of 153 subjects. The mean cluster size and the raw number of switches were compared in the two samples. The results revealed a significantly lower switching index in the future AD subjects than in the elderly controls including 5 years before dementia incidence. A significant decline in this parameter was evidenced all along the prodromal phase until the clinical diagnosis of dementia. In contrast, the mean cluster size could not discriminate the two groups. Therefore the results support the hypothesis that impaired shifting abilities - rather than semantic memory storage degradation - could explain the early decline in semantic fluency performance occurring in the predementia phase of AD.

Does optimism act as a buffer against posttraumatic stress over time? A longitudinal study of the protective role of optimism after the 2011 Oslo bombing.

PubMed

Birkeland, Marianne Skogbrott; Blix, Ines; Solberg, Øivind; Heir, Trond

2017-03-01

Cross-sectional studies have revealed that high levels of optimism can protect against high levels of posttraumatic stress after exposure to trauma. However, this is the first study to explore (a) the protective role of optimism in a longitudinal perspective and (b) optimism's protective effects on specific symptom clusters within the posttraumatic stress symptomatology. This study used prospective survey data from ministerial employees (n = 256) collected approximately 1, 2, and 3 years after the 2011 Oslo bombing. To examine relationships between optimism and development of posttraumatic stress, we applied a series of latent growth curve analyses of both overall posttraumatic stress and the 5 clusters within the posttraumatic stress symptomatology (intrusions, avoidance, numbing, dysphoric arousal, and anxious arousal) with predictors and interaction terms. The results showed that levels of exposure and optimism had main effects on starting levels of all clusters of posttraumatic stress. In addition, optimism had a protective-stabilizing effect on starting levels of avoidance, numbing, and dysphoric arousal. No associations between optimism and rate of change in symptoms clusters were found. These results suggest that optimism may help to neutralize the effects of high exposure on levels of symptoms of avoidance, numbing, and dysphoric arousal but not on the symptoms of intrusions and anxious arousal. Thus, individuals high in optimism still experience intrusions and anxious arousal after trauma, but may be better equipped to cope with these so they do not develop into avoidance, numbing and dyshorical arousal. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

RECRUITING FOR A LONGITUDINAL STUDY OF CHILDREN'S HEALTH USING A HOUSEHOLD-BASED PROBABILITY SAMPLING APPROACH

EPA Science Inventory

The sampling design for the National Children¿s Study (NCS) calls for a population-based, multi-stage, clustered household sampling approach (visit our website for more information on the NCS : www.nationalchildrensstudy.gov). The full sample is designed to be representative of ...

Parental Behavioural Control and Academic Achievement: Striking the Balance between Control and Involvement

ERIC Educational Resources Information Center

Kramer, Karen Z.

2012-01-01

Using a longitudinal US dataset (N = 6,134) we examine the relationship between parental behavioural control and academic achievement and explore the moderating role of parental involvement and parental warmth. Analyses using multiple hierarchical regression with clustering controls shows that parental behavioural control is negatively associated…

Clusters of Colleges and Universities: An Empirically Determined System.

ERIC Educational Resources Information Center

Korb, Roslyn

A technique for classifying higher education institutions was developed in order to identify homogenous subsets of institutions and to compare an institution with its empirically determined peers. The majority of the data were obtained from a 4-year longitudinal file that merged the finance, faculty, enrollment, and institutional characteristics…

Three estimates of the association between linear growth failure and cognitive ability.

PubMed

Cheung, Y B; Lam, K F

2009-09-01

To compare three estimators of association between growth stunting as measured by height-for-age Z-score and cognitive ability in children, and to examine the extent statistical adjustment for covariates is useful for removing confounding due to socio-economic status. Three estimators, namely random-effects, within- and between-cluster estimators, for panel data were used to estimate the association in a survey of 1105 pairs of siblings who were assessed for anthropometry and cognition. Furthermore, a 'combined' model was formulated to simultaneously provide the within- and between-cluster estimates. Random-effects and between-cluster estimators showed strong association between linear growth and cognitive ability, even after adjustment for a range of socio-economic variables. In contrast, the within-cluster estimator showed a much more modest association: For every increase of one Z-score in linear growth, cognitive ability increased by about 0.08 standard deviation (P < 0.001). The combined model verified that the between-cluster estimate was significantly larger than the within-cluster estimate (P = 0.004). Residual confounding by socio-economic situations may explain a substantial proportion of the observed association between linear growth and cognition in studies that attempt to control the confounding by means of multivariable regression analysis. The within-cluster estimator provides more convincing and modest results about the strength of association.

A Random Walk Approach to Query Informative Constraints for Clustering.

PubMed

Abin, Ahmad Ali

2017-08-09

This paper presents a random walk approach to the problem of querying informative constraints for clustering. The proposed method is based on the properties of the commute time, that is the expected time taken for a random walk to travel between two nodes and return, on the adjacency graph of data. Commute time has the nice property of that, the more short paths connect two given nodes in a graph, the more similar those nodes are. Since computing the commute time takes the Laplacian eigenspectrum into account, we use this property in a recursive fashion to query informative constraints for clustering. At each recursion, the proposed method constructs the adjacency graph of data and utilizes the spectral properties of the commute time matrix to bipartition the adjacency graph. Thereafter, the proposed method benefits from the commute times distance on graph to query informative constraints between partitions. This process iterates for each partition until the stop condition becomes true. Experiments on real-world data show the efficiency of the proposed method for constraints selection.

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.

Outcomes of a Pilot Hand Hygiene Randomized Cluster Trial to Reduce Communicable Infections Among US Office-Based Employees

PubMed Central

DuBois, Cathy L.Z.; Grey, Scott F.; Kingsbury, Diana M.; Shakya, Sunita; Scofield, Jennifer; Slenkovich, Ken

2015-01-01

Objective: To determine the effectiveness of an office-based multimodal hand hygiene improvement intervention in reducing self-reported communicable infections and work-related absence. Methods: A randomized cluster trial including an electronic training video, hand sanitizer, and educational posters (n = 131, intervention; n = 193, control). Primary outcomes include (1) self-reported acute respiratory infections (ARIs)/influenza-like illness (ILI) and/or gastrointestinal (GI) infections during the prior 30 days; and (2) related lost work days. Incidence rate ratios calculated using generalized linear mixed models with a Poisson distribution, adjusted for confounders and random cluster effects. Results: A 31% relative reduction in self-reported combined ARI-ILI/GI infections (incidence rate ratio: 0.69; 95% confidence interval, 0.49 to 0.98). A 21% nonsignificant relative reduction in lost work days. Conclusions: An office-based multimodal hand hygiene improvement intervention demonstrated a substantive reduction in self-reported combined ARI-ILI/GI infections. PMID:25719534

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…

Instability of Hierarchical Cluster Analysis Due to Input Order of the Data: The PermuCLUSTER Solution

ERIC Educational Resources Information Center

van der Kloot, Willem A.; Spaans, Alexander M. J.; Heiser, Willem J.

2005-01-01

Hierarchical agglomerative cluster analysis (HACA) may yield different solutions under permutations of the input order of the data. This instability is caused by ties, either in the initial proximity matrix or arising during agglomeration. The authors recommend to repeat the analysis on a large number of random permutations of the rows and columns…

Longitudinal Measurement Invariance of Posttraumatic Stress Disorder in Deployed Marines.

PubMed

Contractor, Ateka A; Bolton, Elisa; Gallagher, Matthew W; Rhodes, Charla; Nash, William P; Litz, Brett

2017-06-01

The meaningful interpretation of longitudinal study findings requires temporal stability of the constructs assessed (i.e., measurement invariance). We sought to examine measurement invariance of the construct of posttraumatic stress disorder (PTSD) as based on the Diagnostic and Statistical Manual of Mental Disorders indexed by the PTSD Checklist (PCL) and the Clinician-Administered PTSD Scale (CAPS) in a sample of 834 Marines with significant combat experience. PTSD was assessed 1-month predeployment (T0), and again at 1-month (T1), 5-months (T2), and 8-months postdeployment (T3). We tested configural (pattern of item/parcel loadings), metric (item/parcel loadings on latent factors), and scalar (item/parcel-level severity) invariance and explored sources of measurement instability (partial invariance testing). The T0 best-fitting emotional numbing model factor structure informed the conceptualization of PTSD's latent factors and parcel formations. We found (1) scalar noninvariance for the construct of PTSD as measured by the PCL and the CAPS, and for PTSD symptom clusters as assessed by the CAPS; and (2) metric noninvariance for PTSD symptom clusters as measured by the PCL. Exploratory analyses revealed factor-loading and intercept differences from pre- to postdeployment for avoidance symptoms, numbing symptoms (mainly psychogenic amnesia and foreshortened future), and the item assessing startle, each of which reduced construct stability. Implications of these findings for longitudinal studies of PTSD are discussed. Copyright © 2017 International Society for Traumatic Stress Studies.

A Bimodal Hybrid Model for Time-Dependent Probabilistic Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Yaghmaei-Sabegh, Saman; Shoaeifar, Nasser; Shoaeifar, Parva

2018-03-01

The evaluation of evidence provided by geological studies and historical catalogs indicates that in some seismic regions and faults, multiple large earthquakes occur in cluster. Then, the occurrences of large earthquakes confront with quiescence and only the small-to-moderate earthquakes take place. Clustering of large earthquakes is the most distinguishable departure from the assumption of constant hazard of random occurrence of earthquakes in conventional seismic hazard analysis. In the present study, a time-dependent recurrence model is proposed to consider a series of large earthquakes that occurs in clusters. The model is flexible enough to better reflect the quasi-periodic behavior of large earthquakes with long-term clustering, which can be used in time-dependent probabilistic seismic hazard analysis with engineering purposes. In this model, the time-dependent hazard results are estimated by a hazard function which comprises three parts. A decreasing hazard of last large earthquake cluster and an increasing hazard of the next large earthquake cluster, along with a constant hazard of random occurrence of small-to-moderate earthquakes. In the final part of the paper, the time-dependent seismic hazard of the New Madrid Seismic Zone at different time intervals has been calculated for illustrative purpose.

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

PubMed

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

Spatial location influences vocal interactions in bullfrog choruses

PubMed Central

Bates, Mary E.; Cropp, Brett F.; Gonchar, Marina; Knowles, Jeffrey; Simmons, James A.; Simmons, Andrea Megela

2010-01-01

A multiple sensor array was employed to identify the spatial locations of all vocalizing male bullfrogs (Rana catesbeiana) in five natural choruses. Patterns of vocal activity collected with this array were compared with computer simulations of chorus activity. Bullfrogs were not randomly spaced within choruses, but tended to cluster into closely spaced groups of two to five vocalizing males. There were nonrandom, differing patterns of vocal interactions within clusters of closely spaced males and between different clusters. Bullfrogs located within the same cluster tended to overlap or alternate call notes with two or more other males in that cluster. These near-simultaneous calling bouts produced advertisement calls with more pronounced amplitude modulation than occurred in nonoverlapping notes or calls. Bullfrogs located in different clusters more often alternated entire calls or overlapped only small segments of their calls. They also tended to respond sequentially to calls of their farther neighbors compared to their nearer neighbors. Results of computational analyses showed that the observed patterns of vocal interactions were significantly different than expected based on random activity. The use of a multiple sensor array provides a richer view of the dynamics of choruses than available based on single microphone techniques. PMID:20370047

Students' Changing Attitudes and Aspirations Towards Physics During Secondary School

NASA Astrophysics Data System (ADS)

Sheldrake, Richard; Mujtaba, Tamjid; Reiss, Michael J.

2017-11-01

Many countries desire more students to study science subjects, although relatively few students decide to study non-compulsory physics at upper-secondary school and at university. To gain insight into students' intentions to study non-compulsory physics, a longitudinal sample (covering 2258 students across 88 secondary schools in England) was surveyed in year 8 (age 12/13) and again in year 10 (age 14/15). Predictive modelling highlighted that perceived advice, perceived utility of physics, interest in physics, self-concept beliefs (students' subjective beliefs of their current abilities and performance) and home support specifically orientated to physics were key predictors of students' intentions. Latent-transition analysis via Markov models revealed clusters of students, given these factors at years 8 and 10. Students' intentions varied across the clusters, and at year 10 even varied when accounting for the students' underlying attitudes and beliefs, highlighting that considering clusters offered additional explanatory power and insight. Regardless of whether three-cluster, four-cluster, or five-cluster models were considered, the majority of students remained in the same cluster over time; for those who transitioned clusters, more students changed clusters reflecting an increase in attitudes than changed clusters reflecting a decrease. Students in the cluster with the most positive attitudes were most likely to remain within that cluster, while students in clusters with less positive attitudes were more likely to change clusters. Overall, the cluster profiles highlighted that students' attitudes and beliefs may be more closely related than previously assumed, but that changes in their attitudes and beliefs were indeed possible.

Improving Nursing Home Care through Feedback On PerfoRMance Data (INFORM): Protocol for a cluster-randomized trial.

PubMed

Hoben, Matthias; Norton, Peter G; Ginsburg, Liane R; Anderson, Ruth A; Cummings, Greta G; Lanham, Holly J; Squires, Janet E; Taylor, Deanne; Wagg, Adrian S; Estabrooks, Carole A

2017-01-10

Audit and feedback is effective in improving the quality of care. However, methods and results of international studies are heterogeneous, and studies have been criticized for a lack of systematic use of theory. In TREC (Translating Research in Elder Care), a longitudinal health services research program, we collect comprehensive data from care providers and residents in Canadian nursing homes to improve quality of care and life of residents, and quality of worklife of caregivers. The study aims are to a) systematically feed back TREC research data to nursing home care units, and b) compare the effectiveness of three different theory-based feedback strategies in improving performance within care units. INFORM (Improving Nursing Home Care through Feedback On PerfoRMance Data) is a 3.5-year pragmatic, three-arm, parallel, cluster-randomized trial. We will randomize 67 Western Canadian nursing homes with 203 care units to the three study arms, a standard feedback strategy and two assisted and goal-directed feedback strategies. Interventions will target care unit managerial teams. They are based on theory and evidence related to audit and feedback, goal setting, complex adaptive systems, and empirical work on feeding back research results. The primary outcome is the increased number of formal interactions (e.g., resident rounds or family conferences) involving care aides - non-registered caregivers providing up to 80% of direct care. Secondary outcomes are a) other modifiable features of care unit context (improved feedback, social capital, slack time) b) care aides' quality of worklife (improved psychological empowerment, job satisfaction), c) more use of best practices, and d) resident outcomes based on the Resident Assessment Instrument - Minimum Data Set 2.0. Outcomes will be assessed at baseline, immediately after the 12-month intervention period, and 18 months post intervention. INFORM is the first study to systematically assess the effectiveness of different strategies to feed back research data to nursing home care units in order to improve their performance. Results of this study will enable development of a practical, sustainable, effective, and cost-effective feedback strategy for routine use by managers, policy makers and researchers. The results may also be generalizable to care settings other than nursing homes. ClinicalTrials.gov Identifier: NCT02695836 . Date of registration: 24 February 2016.

Efficacy of a Community-Based Physical Activity Program KM2H2 for Stroke and Heart Attack Prevention among Senior Hypertensive Patients: A Cluster Randomized Controlled Phase-II Trial.

PubMed

Gong, Jie; Chen, Xinguang; Li, Sijian

2015-01-01

To evaluate the efficacy of the program Keep Moving toward Healthy Heart and Healthy Brain (KM2H2) in encouraging physical activities for the prevention of heart attack and stroke among hypertensive patients enrolled in the Community-Based Hypertension Control Program (CBHCP). Cluster randomized controlled trial with three waves of longitudinal assessments at baseline, 3 and 6 months post intervention. Community-based and patient-centered self-care for behavioral intervention in urban settings of China. A total of 450 participants diagnosed with hypertension from 12 community health centers in Wuhan, China were recruited, and were randomly assigned by center to receive either KM2H2 plus standard CBHCP care (6 centers and 232 patients) or the standard care only (6 centers and 218 patients). KM2H2 is a behavioral intervention guided by the Transtheoretical Model, the Model of Personalized Medicine and Social Capital Theory. It consists of six intervention sessions and two booster sessions engineered in a progressive manner. The purpose is to motivate and maintain physical activities for the prevention of heart attack and stroke. Heart attack and stroke (clinically diagnosed, primary outcome), blood pressure (measured, secondary outcome), and physical activity (self-report, tertiary outcome) were assessed at the individual level during the baseline, 3- and 6-month post-intervention. Relative to the standard care, receiving KM2H2 was associated with significant reductions in the incidence of heart attack (3.60% vs. 7.03%, p < .05) and stroke (5.11% vs. 9.90%, p<0.05), and moderate reduction in blood pressure (-3.72 mmHg in DBP and -2.92 mmHg in DBP) at 6-month post-intervention; and significant increases in physical activity at 3- (d = 0.53, 95% CI: 0.21, 0.85) and 6-month (d = 0.45, 95% CI: 0.04, 0.85) post-intervention, respectively. The program KM2H2 is efficacious to reduce the risk of heart attack and stroke among senior patients who are on anti-hypertensive medication. Findings of this study provide solid data supporting a formal phase-III trial to establish the effectiveness of KM2H2 for use in community settings for prevention. ISRCTN Register ISRCTN12608966.

Magnetic cluster expansion model for random and ordered magnetic face-centered cubic Fe-Ni-Cr alloys

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

Lavrentiev, M. Yu., E-mail: Mikhail.Lavrentiev@ukaea.uk; Nguyen-Manh, D.; Dudarev, S. L.

A Magnetic Cluster Expansion model for ternary face-centered cubic Fe-Ni-Cr alloys has been developed, using DFT data spanning binary and ternary alloy configurations. Using this Magnetic Cluster Expansion model Hamiltonian, we perform Monte Carlo simulations and explore magnetic structures of alloys over the entire range of compositions, considering both random and ordered alloy structures. In random alloys, the removal of magnetic collinearity constraint reduces the total magnetic moment but does not affect the predicted range of compositions where the alloys adopt low-temperature ferromagnetic configurations. During alloying of ordered fcc Fe-Ni compounds with Cr, chromium atoms tend to replace nickel rathermore » than iron atoms. Replacement of Ni by Cr in ordered alloys with high iron content increases the Curie temperature of the alloys. This can be explained by strong antiferromagnetic Fe-Cr coupling, similar to that found in bcc Fe-Cr solutions, where the Curie temperature increase, predicted by simulations as a function of Cr concentration, is confirmed by experimental observations. In random alloys, both magnetization and the Curie temperature decrease abruptly with increasing chromium content, in agreement with experiment.« less

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

Application of an Extended Parabolic Equation to the Calculation of the Mean Field and the Transverse and Longitudinal Mutual Coherence Functions Within Atmospheric Turbulence

NASA Technical Reports Server (NTRS)

Manning, Robert M.

2005-01-01

Solutions are derived for the generalized mutual coherence function (MCF), i.e., the second order moment, of a random wave field propagating through a random medium within the context of the extended parabolic equation. Here, "generalized" connotes the consideration of both the transverse as well as the longitudinal second order moments (with respect to the direction of propagation). Such solutions will afford a comparison between the results of the parabolic equation within the pararaxial approximation and those of the wide-angle extended theory. To this end, a statistical operator method is developed which gives a general equation for an arbitrary spatial statistical moment of the wave field. The generality of the operator method allows one to obtain an expression for the second order field moment in the direction longitudinal to the direction of propagation. Analytical solutions to these equations are derived for the Kolmogorov and Tatarskii spectra of atmospheric permittivity fluctuations within the Markov approximation.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Feasibility, Acceptability, and Initial Efficacy of a Knowledge-Contact Program to Reduce Mental Illness Stigma and Improve Mental Health Literacy in Adolescents

PubMed Central

Pinto-Foltz, Melissa D.; Logsdon, M. Cynthia; Myers, John A.

2011-01-01

The purpose of this school-based cluster-randomized trial was to determine the initial acceptability, feasibility, and efficacy of an existing community-based intervention, In Our Own Voice, in a sample of US adolescent girls aged 13–17 years (n=156). In Our Own Voice is a knowledge-contact intervention that provides knowledge about mental illness to improve mental health literacy and facilitates intergroup contact with persons with mental illness as a means to reduce mental illness stigma. This longitudinal study was set in two public high schools located in a southern urban community of the U.S. Outcomes included measures of mental illness stigma and mental health literacy. Findings support the acceptability and feasibility of the intervention for adolescents who enrolled in the study. Findings to support the efficacy of In Our Own Voice to reduce stigma and improve mental health literacy are mixed. The intervention did not reduce mental illness stigma or improve mental health literacy at one week follow up. The intervention did not reduce mental illness stigma at 4 and 8 weeks follow up. The intervention did improve mental health literacy at 4 and 8 weeks follow up. Previous studies have assessed the preliminary efficacy In Our Own Voice among young adults; rarely has In Our Own Voice been investigated longitudinally and with adolescents in the United States. This study provides initial data on the effects of In Our Own Voice for this population and can be used to further adapt the intervention for adolescents. PMID:21624729

Multiple filters affect tree species assembly in mid-latitude forest communities.

PubMed

Kubota, Y; Kusumoto, B; Shiono, T; Ulrich, W

2018-05-01

Species assembly patterns of local communities are shaped by the balance between multiple abiotic/biotic filters and dispersal that both select individuals from species pools at the regional scale. Knowledge regarding functional assembly can provide insight into the relative importance of the deterministic and stochastic processes that shape species assembly. We evaluated the hierarchical roles of the α niche and β niches by analyzing the influence of environmental filtering relative to functional traits on geographical patterns of tree species assembly in mid-latitude forests. Using forest plot datasets, we examined the α niche traits (leaf and wood traits) and β niche properties (cold/drought tolerance) of tree species, and tested non-randomness (clustering/over-dispersion) of trait assembly based on null models that assumed two types of species pools related to biogeographical regions. For most plots, species assembly patterns fell within the range of random expectation. However, particularly for cold/drought tolerance-related β niche properties, deviation from randomness was frequently found; non-random clustering was predominant in higher latitudes with harsh climates. Our findings demonstrate that both randomness and non-randomness in trait assembly emerged as a result of the α and β niches, although we suggest the potential role of dispersal processes and/or species equalization through trait similarities in generating the prevalence of randomness. Clustering of β niche traits along latitudinal climatic gradients provides clear evidence of species sorting by filtering particular traits. Our results reveal that multiple filters through functional niches and stochastic processes jointly shape geographical patterns of species assembly across mid-latitude forests.

Community-based trial of annual versus biannual single-dose ivermectin plus albendazole against Wuchereria bancrofti infection in human and mosquito populations: study protocol for a cluster randomised controlled trial.

PubMed

de Souza, Dziedzom K; Ahorlu, Collins S; Adu-Amankwah, Susan; Otchere, Joseph; Mensah, Sedzro K; Larbi, Irene A; Mensah, George E; Biritwum, Nana-Kwadwo; Boakye, Daniel A

2017-10-02

The Global Programme for the Elimination of Lymphatic Filariasis (GPELF) has been in operation since the year 2000, with the aim of eliminating the disease by the year 2020, following five to six rounds of effective annual mass drug administration (MDA). The treatment regimen is ivermectin (IVM) in combination with diethylcarbamazine (DEC) or albendazole (ALB). In Ghana, MDA has been undertaken since 2001. While the disease has been eliminated in many areas, transmission has persisted in some implementation units that had experienced 15 or more rounds of MDA. Thus, new intervention strategies could eliminate residual infection in areas of persistent transmission and speed up the lymphatic filariasis (LF)-elimination process. This study, therefore, seeks to test the hypothesis that biannual treatment of LF-endemic communities will accelerate the interruption of LF in areas of persistent transmission. A cluster randomised trial will be implemented in LF-endemic communities in Ghana. The interventions will be yearly or twice-yearly MDA delivered to entire endemic communities. Allocation to study group will be by clusters identified using the prevalence of LF. Clusters will be randomised to one of two groups: receiving either (1) annual treatment with IVM + ALB or (2) annual MDA with IVM + ALB, followed by an additional MDA 6 months later. The primary outcome measure is the prevalence of LF infection, assessed by four cross-sectional surveys. Entomological assessments will also be undertaken to evaluate the transmission intensity of the disease in the study clusters. Costs and cost-effectiveness will be evaluated. Among a random subsample of participants, microfilaria prevalence will be assessed longitudinally. A nested process evaluation, using semi-structured interviews, focus group discussions and a stakeholder analysis, will investigate the community acceptability, feasibility and scale-up of each delivery system. It is expected that this study will add to the existing evidence on the need for alternative intervention strategies for the elimination of LF in Ghana and in other African countries that are facing similar challenges or are at the beginning of their LF-elimination programmes. ClinicalTrials.gov, ID: NCT03036059 . Registered on 26 January 2017. Pan African Clinical Trials Registry, ID: PACTR201702002012425 . Registered on 23 February 2017.

What It's Like to Grow Older: The Aging Perceptions of People with an Intellectual Disability in Ireland

ERIC Educational Resources Information Center

Burke, Eilish; McCarron, Mary; Carroll, Rachael; McGlinchey, Eimear; McCallion, Philip

2014-01-01

The Intellectual Disability Supplement to The Irish Longitudinal Study on Ageing is a national longitudinal study on the aging of people with an intellectual disability (ID) using a randomly selected sample of people with ID over the age of 40. In total, 367 people with an ID completed the aging perception self-report only section. Over 57% of…

Longitudinal Study of a Cooperation-Driven, Socio-Scientific Issue Intervention on Promoting Students' Critical Thinking and Self-Regulation in Learning Science

ERIC Educational Resources Information Center

Wang, Hsin-Hui; Chen, Hsiang-Ting; Lin, Huann-shyang; Huang, Yu-Ning; Hong, Zuway-R

2017-01-01

This longitudinal study explored the effects of a Cooperation-driven Socioscientific Issue (CDSSI) intervention on junior high school students' perceptions of critical thinking (CT) and self-regulation (SR) in Taiwan. Forty-nine grade 7 students were randomly selected as an experimental group (EG) to attend a 3-semester 72-hour intervention; while…

The Philadelphia Education Longitudinal Study (PELS): Report on the Transition to High School in the School District of Philadelphia.

ERIC Educational Resources Information Center

Neild, Ruth Curran; Weiss, Christopher C.

The Philadelphia Education Longitudinal Study (PELS) on the transition to ninth grade in Philadelphia highlights the high school choice process, course failure rates during ninth grade, and parents' responses to the transition to high school. The PELS study followed a city-wide random sample of public school students from the summer after eighth…

Longitudinal Andhra Pradesh Eye Disease Study: rationale, study design and research methodology.

PubMed

Khanna, Rohit C; Murthy, Gudlavalleti Vs; Marmamula, Srinivas; Mettla, Asha Latha; Giridhar, Pyda; Banerjee, Seema; Shekhar, Konegari; Chakrabarti, Subhabrata; Gilbert, Clare; Rao, Gullapalli N

2016-03-01

The rationale, objectives, study design and procedures for the longitudinal Andhra Pradesh Eye Disease Study are described. A longitudinal cohort study was carried out. Participants include surviving cohort from the rural component of Andhra Pradesh Eye Disease Study. During 1996-2000, Andhra Pradesh Eye Disease Survey was conducted in three rural (n = 7771) and one urban (n = 2522) areas (now called Andhra Pradesh Eye Disease Study 1). In 2009-2010, a feasibility exercise (Andhra Pradesh Eye Disease Study 2) for a longitudinal study (Andhra Pradesh Eye Disease Study 3) was undertaken in the rural clusters only, as urban clusters no longer existed. In Andhra Pradesh Eye Disease Study 3, a detailed interview will be carried out to collect data on sociodemographic factors, ocular and systemic history, risk factors, visual function, knowledge of eye diseases and barriers to accessing services. All participants will also undergo a comprehensive eye examination including photography of lens, optic disc and retina, Optic Coherence Tomography of the posterior segment, anthropometry, blood pressure and frailty measures. Measures include estimates of the incidence of visual impairment and age-related eye disease (lens opacities, glaucoma and age-related macular degeneration) and the progression of eye disease (lens opacities and myopia) and associated risk factors. Of the 7771 respondents examined in rural areas in Andhra Pradesh Eye Disease Study 1, 5447 (70.1%) participants were traced in Andhra Pradesh Eye Disease Study 2. These participants will be re-examined. Andhra Pradesh Eye Disease Study 3 will provide data on the incidence and progression of visual impairment and major eye diseases and their associated risk factors in India. The study will provide further evidence to aid planning eye care services. © 2015 Royal Australian and New Zealand College of Ophthalmologists.

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.

Model Selection with the Linear Mixed Model for Longitudinal Data

ERIC Educational Resources Information Center

Ryoo, Ji Hoon

2011-01-01

Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

Cluster randomized trials in comparative effectiveness research: randomizing hospitals to test methods for prevention of healthcare-associated infections.

PubMed

Platt, Richard; Takvorian, Samuel U; Septimus, Edward; Hickok, Jason; Moody, Julia; Perlin, Jonathan; Jernigan, John A; Kleinman, Ken; Huang, Susan S

2010-06-01

The need for evidence about the effectiveness of therapeutics and other medical practices has triggered new interest in methods for comparative effectiveness research. Describe an approach to comparative effectiveness research involving cluster randomized trials in networks of hospitals, health plans, or medical practices with centralized administrative and informatics capabilities. We discuss the example of an ongoing cluster randomized trial to prevent methicillin-resistant Staphylococcus aureus (MRSA) infection in intensive care units (ICUs). The trial randomizes 45 hospitals to: (a) screening cultures of ICU admissions, followed by Contact Precautions if MRSA-positive, (b) screening cultures of ICU admissions followed by decolonization if MRSA-positive, or (c) universal decolonization of ICU admissions without screening. All admissions to adult ICUs. The primary outcome is MRSA-positive clinical cultures occurring >or=2 days following ICU admission. Secondary outcomes include blood and urine infection caused by MRSA (and, separately, all pathogens), as well as the development of resistance to decolonizing agents. Recruitment of hospitals is complete. Data collection will end in Summer 2011. This trial takes advantage of existing personnel, procedures, infrastructure, and information systems in a large integrated hospital network to conduct a low-cost evaluation of prevention strategies under usual practice conditions. This approach is applicable to many comparative effectiveness topics in both inpatient and ambulatory settings.

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.

PubMed

Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R

2015-12-01

The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

A new approach for the assessment of temporal clustering of extratropical wind storms

NASA Astrophysics Data System (ADS)

Schuster, Mareike; Eddounia, Fadoua; Kuhnel, Ivan; Ulbrich, Uwe

2017-04-01

A widely-used methodology to assess the clustering of storms in a region is based on dispersion statistics of a simple homogeneous Poisson process. This clustering measure is determined by the ratio of the variance and the mean of the local storm statistics per grid point. Resulting values larger than 1, i.e. when the variance is larger than the mean, indicate clustering; while values lower than 1 indicate a sequencing of storms that is more regular than a random process. However, a disadvantage of this methodology is that the characteristics are valid for a pre-defined climatological time period, and it is not possible to identify a temporal variability of clustering. Also, the absolute value of the dispersion statistics is not particularly intuitive. We have developed an approach to describe temporal clustering of storms which offers a more intuitive comprehension, and at the same time allows to assess temporal variations. The approach is based on the local distribution of waiting times between the occurrence of two individual storm events, the former being computed through the post-processing of individual windstorm tracks which in turn are obtained by an objective tracking algorithm. Based on this distribution a threshold can be set, either by the waiting time expected from a random process or by a quantile of the observed distribution. Thus, it can be determined if two consecutive wind storm events count as part of a (temporal) cluster. We analyze extratropical wind storms in a reanalysis dataset and compare the results of the traditional clustering measure with our new methodology. We assess what range of clustering events (in terms of duration and frequency) is covered and identify if the historically known clustered seasons are detectable by the new clustering measure in the reanalysis.

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data

PubMed Central

Borri, Marco; Schmidt, Maria A.; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M.; Partridge, Mike; Bhide, Shreerang A.; Nutting, Christopher M.; Harrington, Kevin J.; Newbold, Katie L.; Leach, Martin O.

2015-01-01

Purpose To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. Material and Methods The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. Results The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. Conclusion The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes. PMID:26398888

On the estimation of intracluster correlation for time-to-event outcomes in cluster randomized trials.

PubMed

Kalia, Sumeet; Klar, Neil; Donner, Allan

2016-12-30

Cluster randomized trials (CRTs) involve the random assignment of intact social units rather than independent subjects to intervention groups. Time-to-event outcomes often are endpoints in CRTs. Analyses of such data need to account for the correlation among cluster members. The intracluster correlation coefficient (ICC) is used to assess the similarity among binary and continuous outcomes that belong to the same cluster. However, estimating the ICC in CRTs with time-to-event outcomes is a challenge because of the presence of censored observations. The literature suggests that the ICC may be estimated using either censoring indicators or observed event times. A simulation study explores the effect of administrative censoring on estimating the ICC. Results show that ICC estimators derived from censoring indicators or observed event times are negatively biased. Analytic work further supports these results. Observed event times are preferred to estimate the ICC under minimum frequency of administrative censoring. To our knowledge, the existing literature provides no practical guidance on the estimation of ICC when substantial amount of administrative censoring is present. The results from this study corroborate the need for further methodological research on estimating the ICC for correlated time-to-event outcomes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning.

PubMed

Kesler, Shelli R; Rao, Arvind; Blayney, Douglas W; Oakley-Girvan, Ingrid A; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34-65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy ( p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables ( p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment.

Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning

PubMed Central

Kesler, Shelli R.; Rao, Arvind; Blayney, Douglas W.; Oakley-Girvan, Ingrid A.; Karuturi, Meghan; Palesh, Oxana

2017-01-01

We aimed to determine if resting state functional magnetic resonance imaging (fMRI) acquired at pre-treatment baseline could accurately predict breast cancer-related cognitive impairment at long-term follow-up. We evaluated 31 patients with breast cancer (age 34–65) prior to any treatment, post-chemotherapy and 1 year later. Cognitive testing scores were normalized based on data obtained from 43 healthy female controls and then used to categorize patients as impaired or not based on longitudinal changes. We measured clustering coefficient, a measure of local connectivity, by applying graph theory to baseline resting state fMRI and entered these metrics along with relevant patient-related and medical variables into random forest classification. Incidence of cognitive impairment at 1 year follow-up was 55% and was predicted by classification algorithms with up to 100% accuracy (p < 0.0001). The neuroimaging-based model was significantly more accurate than a model involving patient-related and medical variables (p = 0.005). Hub regions belonging to several distinct functional networks were the most important predictors of cognitive outcome. Characteristics of these hubs indicated potential spread of brain injury from default mode to other networks over time. These findings suggest that resting state fMRI is a promising tool for predicting future cognitive impairment associated with breast cancer. This information could inform treatment decision making by identifying patients at highest risk for long-term cognitive impairment. PMID:29187817

Lessons Learned in Evaluating a Multisite, Comprehensive Teen Dating Violence Prevention Strategy: Design and Challenges of the Evaluation of Dating Matters: Strategies to Promote Healthy Teen Relationships.

PubMed

Niolon, Phyllis Holditch; Taylor, Bruce G; Latzman, Natasha E; Vivolo-Kantor, Alana M; Valle, Linda Anne; Tharp, Andra T

2016-03-01

This paper describes the multisite, longitudinal cluster randomized controlled trial (RCT) design of the evaluation of the Dating Matters: Strategies to Promote Healthy Relationships initiative, and discusses challenges faced in conducting this evaluation. Health departments in 4 communities are partnering with middle schools in high-risk, urban communities to implement 2 models of teen dating violence (TDV) prevention over 4 years. Schools were randomized to receive either the Dating Matters comprehensive strategy or the "standard of care" strategy (an existing, evidence-based TDV prevention curriculum). Our design permits comparison of the relative effectiveness of the comprehensive and standard of care strategies. Multiple cohorts of students from 46 middle schools are surveyed in middle school and high school, and parents and educators from participating schools are also surveyed. Challenges discussed in conducting a multisite RCT include site variability, separation of implementation and evaluation responsibilities, school retention, parent engagement in research activities, and working within the context of high-risk urban schools and communities. We discuss the strengths and weaknesses of our approaches to these challenges in the hopes of informing future research. Despite multiple challenges, the design of the Dating Matters evaluation remains strong. We hope this paper provides researchers who are conducting complex evaluations of behavioral interventions with thoughtful discussion of the challenges we have faced and potential solutions to such challenges.

Lessons Learned in Evaluating a Multisite, Comprehensive Teen Dating Violence Prevention Strategy: Design and Challenges of the Evaluation of Dating Matters: Strategies to Promote Healthy Teen Relationships

PubMed Central

Niolon, Phyllis Holditch; Taylor, Bruce G.; Latzman, Natasha E.; Vivolo-Kantor, Alana M.; Valle, Linda Anne; Tharp, Andra T.

2018-01-01

Objective This paper describes the multisite, longitudinal cluster randomized controlled trial (RCT) design of the evaluation of the Dating Matters: Strategies to Promote Healthy Relationships initiative, and discusses challenges faced in conducting this evaluation. Method Health departments in 4 communities are partnering with middle schools in high-risk, urban communities to implement 2 models of teen dating violence (TDV) prevention over 4 years. Schools were randomized to receive either the Dating Matters comprehensive strategy or the “standard of care” strategy (an existing, evidence-based TDV prevention curriculum). Our design permits comparison of the relative effectiveness of the comprehensive and standard of care strategies. Multiple cohorts of students from 46 middle schools are surveyed in middle school and high school, and parents and educators from participating schools are also surveyed. Results Challenges discussed in conducting a multisite RCT include site variability, separation of implementation and evaluation responsibilities, school retention, parent engagement in research activities, and working within the context of high-risk urban schools and communities. We discuss the strengths and weaknesses of our approaches to these challenges in the hopes of informing future research. Conclusions Despite multiple challenges, the design of the Dating Matters evaluation remains strong. We hope this paper provides researchers who are conducting complex evaluations of behavioral interventions with thoughtful discussion of the challenges we have faced and potential solutions to such challenges. PMID:29607239

Higher-order clustering in networks

NASA Astrophysics Data System (ADS)

Yin, Hao; Benson, Austin R.; Leskovec, Jure

2018-05-01

A fundamental property of complex networks is the tendency for edges to cluster. The extent of the clustering is typically quantified by the clustering coefficient, which is the probability that a length-2 path is closed, i.e., induces a triangle in the network. However, higher-order cliques beyond triangles are crucial to understanding complex networks, and the clustering behavior with respect to such higher-order network structures is not well understood. Here we introduce higher-order clustering coefficients that measure the closure probability of higher-order network cliques and provide a more comprehensive view of how the edges of complex networks cluster. Our higher-order clustering coefficients are a natural generalization of the traditional clustering coefficient. We derive several properties about higher-order clustering coefficients and analyze them under common random graph models. Finally, we use higher-order clustering coefficients to gain new insights into the structure of real-world networks from several domains.

Trajectories of Symptom Clusters, Performance Status, and Quality of Life During Concurrent Chemoradiotherapy in Patients With High-Grade Brain Cancers.

PubMed

Kim, Sang-Hee; Byun, Youngsoon

Symptom clusters must be identified in patients with high-grade brain cancers for effective symptom management during cancer-related therapy. The aims of this study were to identify symptom clusters in patients with high-grade brain cancers and to determine the relationship of each cluster with the performance status and quality of life (QOL) during concurrent chemoradiotherapy (CCRT). Symptoms were assessed using the Memorial Symptom Assessment Scale, and the performance status was evaluated using the Karnofsky Performance Scale. Quality of life was assessed using the Functional Assessment of Cancer Therapy-General. This prospective longitudinal survey was conducted before CCRT and at 2 to 3 weeks and 4 to 6 weeks after the initiation of CCRT. A total of 51 patients with newly diagnosed primary malignant brain cancer were included. Six symptom clusters were identified, and 2 symptom clusters were present at each time point (ie, "negative emotion" and "neurocognitive" clusters before CCRT, "negative emotion and decreased vitality" and "gastrointestinal and decreased sensory" clusters at 2-3 weeks, and "body image and decreased vitality" and "gastrointestinal" clusters at 4-6 weeks). The symptom clusters at each time point demonstrated a significant relationship with the performance status or QOL. Differences were observed in symptom clusters in patients with high-grade brain cancers during CCRT. In addition, the symptom clusters were correlated with the performance status and QOL of patients, and these effects could change during CCRT. The results of this study will provide suggestions for interventions to treat or prevent symptom clusters in patients with high-grade brain cancer during CCRT.

Pathological and non-pathological variants of restrictive eating behaviors in middle childhood: A latent class analysis.

PubMed

Schmidt, Ricarda; Vogel, Mandy; Hiemisch, Andreas; Kiess, Wieland; Hilbert, Anja

2018-08-01

Although restrictive eating behaviors are very common during early childhood, their precise nature and clinical correlates remain unclear. Especially, there is little evidence on restrictive eating behaviors in older children and their associations with children's shape concern. The present population-based study sought to delineate subgroups of restrictive eating patterns in N = 799 7-14 year old children. Using Latent Class Analysis, children were classified based on six restrictive eating behaviors (for example, picky eating, food neophobia, and eating-related anxiety) and shape concern, separately in three age groups. For cluster validation, sociodemographic and objective anthropometric data, parental feeding practices, and general and eating disorder psychopathology were used. The results showed a 3-cluster solution across all age groups: an asymptomatic class (Cluster 1), a class with restrictive eating behaviors without shape concern (Cluster 2), and a class showing restrictive eating behaviors with prominent shape concern (Cluster 3). The clusters differed in all variables used for validation. Particularly, the proportion of children with symptoms of avoidant/restrictive food intake disorder was greater in Cluster 2 than Clusters 1 and 3. The study underlined the importance of considering shape concern to distinguish between different phenotypes of children's restrictive eating patterns. Longitudinal data are needed to evaluate the clusters' predictive effects on children's growth and development of clinical eating disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

Developing a "Productive" Account of Young People's Transition Perspectives

ERIC Educational Resources Information Center

Vaughan, Karen; Roberts, Josie

2007-01-01

This article draws on the first two years of a longitudinal study of young people's pathway and career-related experiences and perspectives. It argues for a richer conceptualisation of young people's transition to study, training and employment than what simple school-to-labour market models allow. We present four clusters of young people's…

Physiological Profiles during Delay of Gratification: Associations with Emotionality, Self-Regulation, and Adjustment Problems

ERIC Educational Resources Information Center

Wilson, Anna C.; Lengua, Liliana J.; Tininenko, Jennifer; Taylor, Adam; Trancik, Anika

2009-01-01

This longitudinal study utilized a community sample of children (N = 91, 45% female, 8-11 years at time 1) to investigate physiological responses (heart rate reactivity [HRR] and electrodermal responding [EDR]) during delay of gratification in relation to emotionality, self-regulation, and adjustment problems. Cluster analyses identified three…

Latinas' Transition to First Marriage: An Examination of Four Theoretical Perspectives

ERIC Educational Resources Information Center

Lloyd, Kim M.

2006-01-01

National Longitudinal Survey of Youth and census data are used to examine the effect of both individual- and contextual-level determinants on Latinas' transition to first marriage (n = 745). Hypotheses derived from 4 leading theories of marriage timing are evaluated. Discrete-time event-history models that control for clustering within Labor…

Bias and inference from misspecified mixed-effect models in stepped wedge trial analysis.

PubMed

Thompson, Jennifer A; Fielding, Katherine L; Davey, Calum; Aiken, Alexander M; Hargreaves, James R; Hayes, Richard J

2017-10-15

Many stepped wedge trials (SWTs) are analysed by using a mixed-effect model with a random intercept and fixed effects for the intervention and time periods (referred to here as the standard model). However, it is not known whether this model is robust to misspecification. We simulated SWTs with three groups of clusters and two time periods; one group received the intervention during the first period and two groups in the second period. We simulated period and intervention effects that were either common-to-all or varied-between clusters. Data were analysed with the standard model or with additional random effects for period effect or intervention effect. In a second simulation study, we explored the weight given to within-cluster comparisons by simulating a larger intervention effect in the group of the trial that experienced both the control and intervention conditions and applying the three analysis models described previously. Across 500 simulations, we computed bias and confidence interval coverage of the estimated intervention effect. We found up to 50% bias in intervention effect estimates when period or intervention effects varied between clusters and were treated as fixed effects in the analysis. All misspecified models showed undercoverage of 95% confidence intervals, particularly the standard model. A large weight was given to within-cluster comparisons in the standard model. In the SWTs simulated here, mixed-effect models were highly sensitive to departures from the model assumptions, which can be explained by the high dependence on within-cluster comparisons. Trialists should consider including a random effect for time period in their SWT analysis model. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Bias and inference from misspecified mixed‐effect models in stepped wedge trial analysis

PubMed Central

Fielding, Katherine L.; Davey, Calum; Aiken, Alexander M.; Hargreaves, James R.; Hayes, Richard J.

2017-01-01

Many stepped wedge trials (SWTs) are analysed by using a mixed‐effect model with a random intercept and fixed effects for the intervention and time periods (referred to here as the standard model). However, it is not known whether this model is robust to misspecification. We simulated SWTs with three groups of clusters and two time periods; one group received the intervention during the first period and two groups in the second period. We simulated period and intervention effects that were either common‐to‐all or varied‐between clusters. Data were analysed with the standard model or with additional random effects for period effect or intervention effect. In a second simulation study, we explored the weight given to within‐cluster comparisons by simulating a larger intervention effect in the group of the trial that experienced both the control and intervention conditions and applying the three analysis models described previously. Across 500 simulations, we computed bias and confidence interval coverage of the estimated intervention effect. We found up to 50% bias in intervention effect estimates when period or intervention effects varied between clusters and were treated as fixed effects in the analysis. All misspecified models showed undercoverage of 95% confidence intervals, particularly the standard model. A large weight was given to within‐cluster comparisons in the standard model. In the SWTs simulated here, mixed‐effect models were highly sensitive to departures from the model assumptions, which can be explained by the high dependence on within‐cluster comparisons. Trialists should consider including a random effect for time period in their SWT analysis model. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28556355

A Bayesian, generalized frailty model for comet assays.

PubMed

Ghebretinsae, Aklilu Habteab; Faes, Christel; Molenberghs, Geert; De Boeck, Marlies; Geys, Helena

2013-05-01

This paper proposes a flexible modeling approach for so-called comet assay data regularly encountered in preclinical research. While such data consist of non-Gaussian outcomes in a multilevel hierarchical structure, traditional analyses typically completely or partly ignore this hierarchical nature by summarizing measurements within a cluster. Non-Gaussian outcomes are often modeled using exponential family models. This is true not only for binary and count data, but also for, example, time-to-event outcomes. Two important reasons for extending this family are for (1) the possible occurrence of overdispersion, meaning that the variability in the data may not be adequately described by the models, which often exhibit a prescribed mean-variance link, and (2) the accommodation of a hierarchical structure in the data, owing to clustering in the data. The first issue is dealt with through so-called overdispersion models. Clustering is often accommodated through the inclusion of random subject-specific effects. Though not always, one conventionally assumes such random effects to be normally distributed. In the case of time-to-event data, one encounters, for example, the gamma frailty model (Duchateau and Janssen, 2007 ). While both of these issues may occur simultaneously, models combining both are uncommon. Molenberghs et al. ( 2010 ) proposed a broad class of generalized linear models accommodating overdispersion and clustering through two separate sets of random effects. Here, we use this method to model data from a comet assay with a three-level hierarchical structure. Although a conjugate gamma random effect is used for the overdispersion random effect, both gamma and normal random effects are considered for the hierarchical random effect. Apart from model formulation, we place emphasis on Bayesian estimation. Our proposed method has an upper hand over the traditional analysis in that it (1) uses the appropriate distribution stipulated in the literature; (2) deals with the complete hierarchical nature; and (3) uses all information instead of summary measures. The fit of the model to the comet assay is compared against the background of more conventional model fits. Results indicate the toxicity of 1,2-dimethylhydrazine dihydrochloride at different dose levels (low, medium, and high).

Spread of information and infection on finite random networks

NASA Astrophysics Data System (ADS)

Isham, Valerie; Kaczmarska, Joanna; Nekovee, Maziar

2011-04-01

The modeling of epidemic-like processes on random networks has received considerable attention in recent years. While these processes are inherently stochastic, most previous work has been focused on deterministic models that ignore important fluctuations that may persist even in the infinite network size limit. In a previous paper, for a class of epidemic and rumor processes, we derived approximate models for the full probability distribution of the final size of the epidemic, as opposed to only mean values. In this paper we examine via direct simulations the adequacy of the approximate model to describe stochastic epidemics and rumors on several random network topologies: homogeneous networks, Erdös-Rényi (ER) random graphs, Barabasi-Albert scale-free networks, and random geometric graphs. We find that the approximate model is reasonably accurate in predicting the probability of spread. However, the position of the threshold and the conditional mean of the final size for processes near the threshold are not well described by the approximate model even in the case of homogeneous networks. We attribute this failure to the presence of other structural properties beyond degree-degree correlations, and in particular clustering, which are present in any finite network but are not incorporated in the approximate model. In order to test this “hypothesis” we perform additional simulations on a set of ER random graphs where degree-degree correlations and clustering are separately and independently introduced using recently proposed algorithms from the literature. Our results show that even strong degree-degree correlations have only weak effects on the position of the threshold and the conditional mean of the final size. On the other hand, the introduction of clustering greatly affects both the position of the threshold and the conditional mean. Similar analysis for the Barabasi-Albert scale-free network confirms the significance of clustering on the dynamics of rumor spread. For this network, though, with its highly skewed degree distribution, the addition of positive correlation had a much stronger effect on the final size distribution than was found for the simple random graph.

Hospital recruitment for a pragmatic cluster-randomized clinical trial: Lessons learned from the COMPASS study.

PubMed

Johnson, Anna M; Jones, Sara B; Duncan, Pamela W; Bushnell, Cheryl D; Coleman, Sylvia W; Mettam, Laurie H; Kucharska-Newton, Anna M; Sissine, Mysha E; Rosamond, Wayne D

2018-01-26

Pragmatic randomized clinical trials are essential to determine the effectiveness of interventions in "real-world" clinical practice. These trials frequently use a cluster-randomized methodology, with randomization at the site level. Despite policymakers' increased interest in supporting pragmatic randomized clinical trials, no studies to date have reported on the unique recruitment challenges faced by cluster-randomized pragmatic trials. We investigated key challenges and successful strategies for hospital recruitment in the Comprehensive Post-Acute Stroke Services (COMPASS) study. The COMPASS study is designed to compare the effectiveness of the COMPASS model versus usual care in improving functional outcomes, reducing the numbers of hospital readmissions, and reducing caregiver strain for patients discharged home after stroke or transient ischemic attack. This model integrates early supported discharge planning with transitional care management, including nurse-led follow-up phone calls after 2, 30, and 60 days and an in-person clinic visit at 7-14 days involving a functional assessment and neurological examination. We present descriptive statistics of the characteristics of successfully recruited hospitals compared with all eligible hospitals, reasons for non-participation, and effective recruitment strategies. We successfully recruited 41 (43%) of 95 eligible North Carolina hospitals. Leading, non-exclusive reasons for non-participation included: insufficient staff or financial resources (n = 33, 61%), lack of health system support (n = 16, 30%), and lack of support of individual decision-makers (n = 11, 20%). Successful recruitment strategies included: building and nurturing relationships, engaging team members and community partners with a diverse skill mix, identifying gatekeepers, finding mutually beneficial solutions, having a central institutional review board, sharing published pilot data, and integrating contracts and review board administrators. Although we incorporated strategies based on the best available evidence at the outset of the study, hospital recruitment required three times as much time and considerably more staff than anticipated. To reach our goal, we tailored strategies to individuals, hospitals, and health systems. Successful recruitment of a sufficient number and representative mix of hospitals requires considerable preparation, planning, and flexibility. Strategies presented here may assist future trial organizers in implementing cluster-randomized pragmatic trials. Clinicaltrials.gov, NCT02588664 . Registered on 23 October 2015.

Interrupting transmission of soil-transmitted helminths: a study protocol for cluster randomised trials evaluating alternative treatment strategies and delivery systems in Kenya

PubMed Central

Brooker, Simon J; Mwandawiro, Charles S; Halliday, Katherine E; Njenga, Sammy M; Mcharo, Carlos; Gichuki, Paul M; Wasunna, Beatrice; Kihara, Jimmy H; Njomo, Doris; Alusala, Dorcas; Chiguzo, Athuman; Turner, Hugo C; Teti, Caroline; Gwayi-Chore, Claire; Nikolay, Birgit; Truscott, James E; Hollingsworth, T Déirdre; Balabanova, Dina; Griffiths, Ulla K; Freeman, Matthew C; Allen, Elizabeth; Pullan, Rachel L; Anderson, Roy M

2015-01-01

Introduction In recent years, an unprecedented emphasis has been given to the control of neglected tropical diseases, including soil-transmitted helminths (STHs). The mainstay of STH control is school-based deworming (SBD), but mathematical modelling has shown that in all but very low transmission settings, SBD is unlikely to interrupt transmission, and that new treatment strategies are required. This study seeks to answer the question: is it possible to interrupt the transmission of STH, and, if so, what is the most cost-effective treatment strategy and delivery system to achieve this goal? Methods and analysis Two cluster randomised trials are being implemented in contrasting settings in Kenya. The interventions are annual mass anthelmintic treatment delivered to preschool- and school-aged children, as part of a national SBD programme, or to entire communities, delivered by community health workers. Allocation to study group is by cluster, using predefined units used in public health provision—termed community units (CUs). CUs are randomised to one of three groups: receiving either (1) annual SBD; (2) annual community-based deworming (CBD); or (3) biannual CBD. The primary outcome measure is the prevalence of hookworm infection, assessed by four cross-sectional surveys. Secondary outcomes are prevalence of Ascaris lumbricoides and Trichuris trichiura, intensity of species infections and treatment coverage. Costs and cost-effectiveness will be evaluated. Among a random subsample of participants, worm burden and proportion of unfertilised eggs will be assessed longitudinally. A nested process evaluation, using semistructured interviews, focus group discussions and a stakeholder analysis, will investigate the community acceptability, feasibility and scale-up of each delivery system. Ethics and dissemination Study protocols have been reviewed and approved by the ethics committees of the Kenya Medical Research Institute and National Ethics Review Committee, and London School of Hygiene and Tropical Medicine. The study has a dedicated web site. Trial registration number NCT02397772. PMID:26482774

Network Analysis in Disorders of Consciousness: Four Problems and One Proposed Solution (Exponential Random Graph Models)

PubMed Central

Dell'Italia, John; Johnson, Micah A.; Vespa, Paul M.; Monti, Martin M.

2018-01-01

In recent years, the study of the neural basis of consciousness, particularly in the context of patients recovering from severe brain injury, has greatly benefited from the application of sophisticated network analysis techniques to functional brain data. Yet, current graph theoretic approaches, as employed in the neuroimaging literature, suffer from four important shortcomings. First, they require arbitrary fixing of the number of connections (i.e., density) across networks which are likely to have different “natural” (i.e., stable) density (e.g., patients vs. controls, vegetative state vs. minimally conscious state patients). Second, when describing networks, they do not control for the fact that many characteristics are interrelated, particularly some of the most popular metrics employed (e.g., nodal degree, clustering coefficient)—which can lead to spurious results. Third, in the clinical domain of disorders of consciousness, there currently are no methods for incorporating structural connectivity in the characterization of functional networks which clouds the interpretation of functional differences across groups with different underlying pathology as well as in longitudinal approaches where structural reorganization processes might be operating. Finally, current methods do not allow assessing the dynamics of network change over time. We present a different framework for network analysis, based on Exponential Random Graph Models, which overcomes the above limitations and is thus particularly well suited for clinical populations with disorders of consciousness. We demonstrate this approach in the context of the longitudinal study of recovery from coma. First, our data show that throughout recovery from coma, brain graphs vary in their natural level of connectivity (from 10.4 to 14.5%), which conflicts with the standard approach of imposing arbitrary and equal density thresholds across networks (e.g., time-points, subjects, groups). Second, we show that failure to consider the interrelation between network measures does lead to spurious characterization of both inter- and intra-regional brain connectivity. Finally, we show that Separable Temporal ERGM can be employed to describe network dynamics over time revealing the specific pattern of formation and dissolution of connectivity that accompany recovery from coma. PMID:29946293

Does treatment of intestinal helminth infections influence malaria? Background and methodology of a longitudinal study of clinical, parasitological and immunological parameters in Nangapanda, Flores, Indonesia (ImmunoSPIN Study)

PubMed Central

2010-01-01

Background Given that helminth infections are thought to have strong immunomodulatory activity, the question whether helminth infections might affect responses to malaria antigens needs to be addressed. Different cross-sectional studies using diverse methodologies have reported that helminth infections might either exacerbate or reduce the severity of malaria attacks. The same discrepancies have been reported for parasitemia. Methods/Design To determine the effect of geohelminth infections and their treatment on malaria infection and disease outcome, as well as on immunological parameters, the area of Nangapanda on Flores Island, Indonesia, where malaria and helminth parasites are co-endemic was selected for a longitudinal study. Here a Double-blind randomized trial will be performed, incorporating repeated treatment with albendazole (400 mg) or placebo at three monthly intervals. Household characteristic data, anthropometry, the presence of intestinal helminth and Plasmodium spp infections, and the incidence of malaria episodes are recorded. In vitro cultures of whole blood, stimulated with a number of antigens, mitogens and toll like receptor ligands provide relevant immunological parameters at baseline and following 1 and 2 years of treatment rounds. The primary outcome of the study is the prevalence of Plasmodium falciparum and P. vivax infection. The secondary outcome will be incidence and severity of malaria episodes detected via both passive and active follow-up. The tertiary outcome is the inflammatory cytokine profile in response to parasite antigens. The project also facilitates the transfer of state of the art methodologies and technologies, molecular diagnosis of parasitic diseases, immunology and epidemiology from Europe to Indonesia. Discussion The study will provide data on the effect of helminth infections on malaria. It will also give information on anthelminthic treatment efficacy and effectiveness and could help develop evidence-based policymaking. Trial registration This study was approved by The Ethical Committee of Faculty of Medicine, University of Indonesia, ref:194/PT02.FK/Etik/2006 and has been filed by ethics committee of the Leiden University Medical Center. Clinical trial number:ISRCTN83830814. The study is reported in accordance with the CONSORT guidelines for cluster-randomized studies. PMID:20338054

Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England using M-quantile random-effects regression.

PubMed

Tzavidis, Nikos; Salvati, Nicola; Schmid, Timo; Flouri, Eirini; Midouhas, Emily

2016-02-01

Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M -quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.

Estimating the Standard Error of the Impact Estimator in Individually Randomized Trials with Clustering

ERIC Educational Resources Information Center

Weiss, Michael J.; Lockwood, J. R.; McCaffrey, Daniel F.

2016-01-01

In the "individually randomized group treatment" (IRGT) experimental design, individuals are first randomly assigned to a treatment arm or a control arm, but then within each arm, are grouped together (e.g., within classrooms/schools, through shared case managers, in group therapy sessions, through shared doctors, etc.) to receive…

A varying-coefficient method for analyzing longitudinal clinical trials data with nonignorable dropout

PubMed Central

Forster, Jeri E.; MaWhinney, Samantha; Ball, Erika L.; Fairclough, Diane

2011-01-01

Dropout is common in longitudinal clinical trials and when the probability of dropout depends on unobserved outcomes even after conditioning on available data, it is considered missing not at random and therefore nonignorable. To address this problem, mixture models can be used to account for the relationship between a longitudinal outcome and dropout. We propose a Natural Spline Varying-coefficient mixture model (NSV), which is a straightforward extension of the parametric Conditional Linear Model (CLM). We assume that the outcome follows a varying-coefficient model conditional on a continuous dropout distribution. Natural cubic B-splines are used to allow the regression coefficients to semiparametrically depend on dropout and inference is therefore more robust. Additionally, this method is computationally stable and relatively simple to implement. We conduct simulation studies to evaluate performance and compare methodologies in settings where the longitudinal trajectories are linear and dropout time is observed for all individuals. Performance is assessed under conditions where model assumptions are both met and violated. In addition, we compare the NSV to the CLM and a standard random-effects model using an HIV/AIDS clinical trial with probable nonignorable dropout. The simulation studies suggest that the NSV is an improvement over the CLM when dropout has a nonlinear dependence on the outcome. PMID:22101223

Multilevel Models for Intensive Longitudinal Data with Heterogeneous Autoregressive Errors: The Effect of Misspecification and Correction with Cholesky Transformation

PubMed Central

Jahng, Seungmin; Wood, Phillip K.

2017-01-01

Intensive longitudinal studies, such as ecological momentary assessment studies using electronic diaries, are gaining popularity across many areas of psychology. Multilevel models (MLMs) are most widely used analytical tools for intensive longitudinal data (ILD). Although ILD often have individually distinct patterns of serial correlation of measures over time, inferences of the fixed effects, and random components in MLMs are made under the assumption that all variance and autocovariance components are homogenous across individuals. In the present study, we introduced a multilevel model with Cholesky transformation to model ILD with individually heterogeneous covariance structure. In addition, the performance of the transformation method and the effects of misspecification of heterogeneous covariance structure were investigated through a Monte Carlo simulation. We found that, if individually heterogeneous covariances are incorrectly assumed as homogenous independent or homogenous autoregressive, MLMs produce highly biased estimates of the variance of random intercepts and the standard errors of the fixed intercept and the fixed effect of a level 2 covariate when the average autocorrelation is high. For intensive longitudinal data with individual specific residual covariance, the suggested transformation method showed lower bias in those estimates than the misspecified models when the number of repeated observations within individuals is 50 or more. PMID:28286490

Nature of alpha and beta particles in glycogen using molecular size distributions.

PubMed

Sullivan, Mitchell A; Vilaplana, Francisco; Cave, Richard A; Stapleton, David; Gray-Weale, Angus A; Gilbert, Robert G

2010-04-12

Glycogen is a randomly hyperbranched glucose polymer. Complex branched polymers have two structural levels: individual branches and the way these branches are linked. Liver glycogen has a third level: supramolecular clusters of beta particles which form larger clusters of alpha particles. Size distributions of native glycogen were characterized using size exclusion chromatography (SEC) to find the number and weight distributions and the size dependences of the number- and weight-average masses. These were fitted to two distinct randomly joined reference structures, constructed by random attachment of individual branches and as random aggregates of beta particles. The z-average size of the alpha particles in dimethylsulfoxide does not change significantly with high concentrations of LiBr, a solvent system that would disrupt hydrogen bonding. These data reveal that the beta particles are covalently bonded to form alpha particles through a hitherto unsuspected enzyme process, operative in the liver on particles above a certain size range.

Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

NASA Astrophysics Data System (ADS)

Li, X. L.; Zhao, Q. H.; Li, Y.

2017-09-01

Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

Study on the thermal resistance in secondary particles chain of silica aerogel by molecular dynamics simulation

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

Liu, M.; Department of Physics, University of Chinese Academy of Sciences, Beijing 100049; Qiu, L., E-mail: qiulin111@sina.com, E-mail: jzzhengxinghua@163.com

2014-09-07

In this article, molecular dynamics simulation was performed to study the heat transport in secondary particles chain of silica aerogel. The two adjacent particles as the basic heat transport unit were modelled to characterize the heat transfer through the calculation of thermal resistance and vibrational density of states (VDOS). The total thermal resistance of two contact particles was predicted by non-equilibrium molecular dynamics simulations (NEMD). The defects were formed by deleting atoms in the system randomly first and performing heating and quenching process afterwards to achieve the DLCA (diffusive limited cluster-cluster aggregation) process. This kind of treatment showed a verymore » reasonable prediction of thermal conductivity for the silica aerogels compared with the experimental values. The heat transport was great suppressed as the contact length increased or defect concentration increased. The constrain effect of heat transport was much significant when contact length fraction was in the small range (<0.5) or the defect concentration is in the high range (>0.5). Also, as the contact length increased, the role of joint thermal resistance played in the constraint of heat transport was increasing. However, the defect concentration did not affect the share of joint thermal resistance as the contact length did. VDOS of the system was calculated by numerical method to characterize the heat transport from atomic vibration view. The smaller contact length and greater defect concentration primarily affected the longitudinal acoustic modes, which ultimately influenced the heat transport between the adjacent particles.« less

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.