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Summary Longitudinal studies play a prominent role in research on growth, change and/or decline in individuals, and in characterising the environmental and social factors which influence change. The essential feature of a longitudinal study is taking repeated measures of an outcome on the same set of individuals at multiple timepoints, thereby allowing investigators to characterise within subject changes during the measurement period. This paper provides an overview of how the basic design features and analysis of longitudinal studies are related to other study designs, including longitudinal clinical trials as well as repeated measures studies. I summarise the use of the linear mixed model as described in Laird and Ware for the analysis of a broad class of designs and present some applications in health and medicine. [ABSTRACT FROM AUTHOR]

The Thai indigenous upland rice variety 'Niaw Dam Chaw Mai Pai 49' (NDCMP-49) exhibits two and three spikelet clusters, provides genetically stable panicle development, and produces well-developed fertile seeds. In this study, the inheritance pattern of multispikelet clusters, the minimum number of genes, and the mode of gene actions were investigated over six generations, namely, P1, P2, F1, F2, BCP1, and BCP2 from two different crosses, i.e., NDCMP-49 × 'LLR316' and NDCMP-49 × 'ULR291'. The presence of F1 phenotypes and the segregation of spikelet phenotypic clusters in the F2, BCP1, and BCP2 generations revealed that the multispikelet cluster traits of NDCMP-49 are controlled through monogenic inheritance with incomplete dominance. Therefore, careful selection based on the phenotypic values of the transgressive segregation of these characters in advanced generations would provide a reliable and effective method to determine the prospective grain yield per panicle. The results herein provide new data to clarify and expand the available information on the inheritance of multispikelet cluster characteristics in rice. [ABSTRACT FROM AUTHOR]

This article analyses configurations of legal subjectivity, sexuality and the right to travel at the inception of international law. It commences a project on a genealogy of the legal subject of the right to travel that attends to sexuality and ultimately aims to shed light on legal subjectivity and sexuality in current refugee law and policy debates. In particular, it analyses the key early 16th-century work on the law of nations of the Spanish theologian and jurisprudent, Francisco de Vitoria, which produces Christian Europeans as full legal subjects with the right to world travel, in opposition to Native Americans, who were relegated to the position partial legal subjects with duties of hospitality. It argues that the attribution of the 'Supersins' of human sacrifice, cannibalism, bestiality and sodomy to Native Americans, in part through analogy to Spain's long-time enemies the Muslims, was crucial to this partial legal subjectivity, positioning both indigenous peoples subjected to colonization, and religious others, as marginalized outsiders to the law of nations at its crucial beginnings. [ABSTRACT FROM AUTHOR]

Background: Telecommunication models promise to improve access to cancer genetic counseling. Little is known about their impact among the geographically underserved. This work examined knowledge and emotional outcomes and attitudes/beliefs regarding cancer telegenetic services (via live-interactive videoconferencing) in Maine. Materials and Methods: Cancer telegenetic patients seen at two remote sites and control (in-person) patients responded to pre-/postsurveys assessing care impact on hereditary breast and ovarian cancer (HBOC) knowledge and emotional health, ease of access to services, and telegenetics satisfaction/acceptability. Results: 158/174 (90%) participants returned pre- and immediate postcounseling surveys (90 remote and 68 in-person). Fewer returned 1-month postsurveys. Remote patients were older with lower education levels, more likely to live in rural counties and to have cancer histories. The two groups were matched relative to gender, race, and health insurance status. HBOC knowledge improved equally in both groups pre- versus immediately postcounseling and was maintained at 1 month in both groups. Decreased anxiety was evident postcounseling with no significant difference between groups. Depression improved significantly in remote patients immediately postcounseling; 1-month depression measures were lower in both groups. The availability of telegenetics eased transportation needs/work absences, and patients reported satisfaction with telecommunication quality. Despite overall acceptance of telegenetics, 32% of remote patients noted preference for in-person care. Conclusions: There were few differences in HBOC knowledge and emotional outcomes comparing traditional in-person cancer genetic services with telegenetics, and satisfaction with/acceptance of this model was high. These data relate to scalability of cancer telegenetics in rural regions regionally and nationally. [ABSTRACT FROM AUTHOR]

Millions of people are working abroad in countries other than their native ones. Among the largest group are those relocated for temporary assignments by their employers. Expatriate employees go through a psychological transition cycle as they prepare to leave their home country, arrive, adapt, and work in the host country, depart, return and re-adjust to their home country. Three social science disciplines, psychology, intercultural communications studies, and international management, have examined this progression of cultural transitions, recommended coping solutions and advanced our understanding of the process of working abroad. These literatures on expatriate adjustment are summarized in this article. An interdisciplinary approach is suggested which would pose research questions aimed at pragmatic solutions to the transition crises experienced by international employees. [ABSTRACT FROM AUTHOR]

Recent advances in next-generation sequencing technologies have made it possible to generate large amounts of sequence data with rare variants in a cost-effective way. Statistical methods that test variants individually are underpowered to detect rare variants, so it is desirable to perform association analysis of rare variants by combining the information from all variants. In this study, we use a Bayesian regression method to model all variants simultaneously to identify rare variants in a data set from Genetic Analysis Workshop 17. We studied the association between the quantitative risk traits Q1, Q2, and Q4 and the single-nucleotide polymorphisms and identified several positive single-nucleotide polymorphisms for traits Q1 and Q2. However, the model also generated several apparent false positives and missed many true positives, suggesting that there is room for improvement in this model. [ABSTRACT FROM AUTHOR]

(2011) Journal of Nursing Management 109-120 The purpose of the present study is to examine the barriers and facilitators to evidence-based practice (EBP) using Shortell's framework for continuous quality improvement (CQI). EBP is typically undertaken to improve practice. Although there have been many studies focused on the barriers and facilitators to adopting EBP, these have not been tied explicitly to CQI frameworks. CINAHL, Academic Search Premier, Medline, Psych Info, ABI/Inform and LISTA databases were searched using the keywords: nurses, information literacy, access to information, sources of knowledge, decision making, research utilization, information seeking behaviour and nursing practice, evidence-based practice. Shortell's framework was used to organize the barriers and facilitators. Across the articles, the most common barriers were lack of time and lack of autonomy to change practice which falls within the strategic and cultural dimensions in Shortell's framework. Barriers and facilitators to EBP adoption occur at the individual and institutional levels. Solutions to the barriers need to be directed to the dimension where the barrier occurs, while recognizing that multidimensional approaches are essential to the success of overcoming these barriers. The findings of the present study can help nurses identify barriers and implement strategies to promote EBP as part of CQI. [ABSTRACT FROM AUTHOR]

Compositional epistasis is said to be present when the effect of a genetic factor at one locus is masked by a variant at another locus. Although such compositional epistasis is not equivalent to the presence of an interaction in a statistical model, non-standard tests can sometimes be used to detect compositional epistasis. In this paper we consider empirical tests for compositional epistasis under models for the joint effect of two genetic factors which place no restrictions on the main effects of each factor but constrain the interactive effects of the two factors so as to be captured by a single parameter in the model. We describe the implications of these tests for cohort, case-control, case-only and family-based study designs and we illustrate the methods using an example of gene-gene interaction already reported in the literature. [ABSTRACT FROM AUTHOR]

Abstract: In this article, we propose and explore a multivariate logistic regression model for analyzing multiple binary outcomes with incomplete covariate data where auxiliary information is available. The auxiliary data are extraneous to the regression model of interest but predictive of the covariate with missing data. Horton and Laird [N.J. Horton, N.M. Laird, Maximum likelihood analysis of logistic regression models with incomplete covariate data and auxiliary information, Biometrics 57 (2001) 34–42] describe how the auxiliary information can be incorporated into a regression model for a single binary outcome with missing covariates, and hence the efficiency of the regression estimators can be improved. We consider extending the method of  to the case of a multivariate logistic regression model for multiple correlated outcomes, and with missing covariates and completely observed auxiliary information. We demonstrate that in the case of moderate to strong associations among the multiple outcomes, one can achieve considerable gains in efficiency from estimators in a multivariate model as compared to the marginal estimators of the same parameters. [ABSTRACT FROM AUTHOR]

We introduce a method of estimating disease prevalence from case–control family study data. Case–control family studies are performed to investigate the familial aggregation of disease; families are sampled via either a case or a control proband, and the resulting data contain information on disease status and covariates for the probands and their relatives. Here, we introduce estimators for overall prevalence and for covariate-stratum-specific (e.g., sex-specific) prevalence. These estimators combine the proportion of affected relatives of control probands with the proportion of affected relatives of case probands and are designed to yield approximately unbiased estimates of their population counterparts under certain commonly made assumptions. We also introduce corresponding confidence intervals designed to have good coverage properties even for small prevalences. Next, we describe simulation experiments where our estimators and intervals were applied to case–control family data sampled from fictional populations with various levels of familial aggregation. At all aggregation levels, the resulting estimates varied closely and symmetrically around their population counterparts, and the resulting intervals had good coverage properties, even for small sample sizes. Finally, we discuss the assumptions required for our estimators to be approximately unbiased, highlighting situations where an alternative estimator based only on relatives of control probands may perform better. [ABSTRACT FROM AUTHOR]

The recent emergence of massively parallel sequencing technologies has enabled an increasing number of human genome re-sequencing studies, notable among them being the 1000 Genomes Project. The main aim of these studies is to identify the yet unknown genetic variants in a genomic region, mostly low frequency variants (frequency less than 5%). We propose here a set of statistical tools that address how to optimally design such studies in order to increase the number of genetic variants we expect to discover. Within this framework, the tradeoff between lower coverage for more individuals and higher coverage for fewer individuals can be naturally solved. The methods here are also useful for estimating the number of genetic variants missed in a discovery study performed at low coverage. We show applications to simulated data based on coalescent models and to sequence data from the ENCODE project. In particular, we show the extent to which combining data from multiple populations in a discovery study may increase the number of genetic variants identified relative to studies on single populations. [ABSTRACT FROM AUTHOR]

Objective: To estimate the familiality and heritability of binge eating disorder (BED). Method: We used a new ACE structural equation model to estimate heritability from a case-control family study of BED conducted in the Boston area. The sample consisted of 150 overweight/obese probands with lifetime BED by DSM-IV criteria, 150 overweight/obese probands without lifetime BED, and 888 of their first-degree relatives. We compared our findings with those from a study of binge eating (in the absence of compensatory behaviors) among 7,831 Norwegian twins. Results: The prevalence of BED differed by sex and by age. In the case-control family study, BED was found to aggregate in families, and heritability was estimated as 57% (CI: 30–77%). Including shared environment did not substantially improve the model's fit, nor did allowing sex-specific heritability. Findings from the twin study were similar. Conclusion: BED appears to aggregate in families and have a significant genetic component. © 2007 by Wiley Periodicals, Inc. Int J Eat Disord, 2008 [ABSTRACT FROM AUTHOR]

Aims While studies of the social networks of injection drug users (IDUs) have provided insight into how the structures of interpersonal relationships among IDUs affect HIV risk behaviors , the majority of these studies have been cross-sectional. The present study examined the dynamics of IDUs’ social networks and HIV risk behaviors over time. Design Using data from a longitudinal HIV-intervention study conducted in Baltimore, MD, this study assessed changes in the composition of the personal networks of 409 IDUs. We used a multi-nomial logistic regression analysis to assess the association between changes in network composition and simultaneous changes in levels of injection HIV risk behaviors. Using the regression parameters generated by the multi-nomial model, we estimated the predicted probability of being in each of four HIV risk behavior change groups . Findings Compared to the base case, individuals who reported an entirely new set of drug-using network contacts at follow-up were more than three times as likely to be in the increasing risk group. In contrast, reporting all new non-drug-using contacts at follow-up increased the likelihood of being in the stable low-risk group by almost 50% and decreased the probability of being in the consistently high-risk group by more than 70%. Conclusions The findings from this study show that, over and above IDUs’ baseline characteristics, changes in their personal networks are associated with changes in individuals’ risky injection behaviors. They also suggest that interventions aimed at reducing HIV risk among IDUs might benefit from increasing IDUs’ social contacts with individuals who are not drug users. [ABSTRACT FROM AUTHOR]

Both population-based and family-based designs are commonly used in genetic association studies to locate genes that underlie complex diseases. The simplest version of the family-based design — the transmission disequilibrium test — is well known, but the numerous extensions that broaden its scope and power are less widely appreciated. Family-based designs have unique advantages over population-based designs, as they are robust against population admixture and stratification, allow both linkage and association to be tested for and offer a solution to the problem of model building. Furthermore, the fact that family-based designs contain both within- and between-family information has substantial benefits in terms of multiple-hypothesis testing, especially in the context of whole-genome association studies. [ABSTRACT FROM AUTHOR]

Abstract: The dynamics of labor force participation and joblessness during young adulthood influence access to social and material resources and shape exposure to different sources of psychosocial strain. Differences in these dynamics by race, ethnicity, and gender are related to changes in a behavioral determinant of poor health (tobacco use) for young adults aging into midlife. Using discrete-time hazards models, we estimate the relationship between labor force participation in the past year and smoking cessation for US adults (ages 14–21 years in 1979) followed in a population-representative sample until 1998 (i.e. the National Longitudinal Survey of Youth). We assess the unique role of racial, ethnic and gender differences in exposure, vulnerability, and reactivity to employment and joblessness by controlling for social and economic resources obtained through working and by controlling for early life factors that select individuals into certain labor force and smoking trajectories. There are three main findings: (1) joblessness is more strongly associated with persistent daily smoking among women than among men; (2) fewer social and economic resources for women out of the labor force compared to employed women explains their lower cessation rates; and (3) lower cessation among unemployed women compared to employed women can only partially be explained by these resources. These findings illustrate how differential access to work-related social and economic resources is an important mediator of poor health trajectories. Contextual factors such as social norms and psychosocial strains at work and at home may play a unique role among European American men and women in explaining gender differences in smoking. [Copyright &y& Elsevier]

As the data rate of integrated circuits dramatically increases, interconnection speed at the backplane and board levels are beginning to limit system performance, which drives investigations into alternative interconnection technologies. Critical factors to consider when evaluating alternative interconnection approaches include interconnect speed, power consumption, area, and compatibility with current backplane and board integration technologies. Optical interconnections can achieve very high speed with a significant reduction in interconnect footprint compared to transmission lines, robust signal quality in high-density interconnection systems because of immunity to electromagnetic interference, and potentially simple to design (compared to transmission lines) lines with materials which can be postprocessed onto printed wiring boards or integrated into the board structure. This paper explores design options for planar optical interconnections integrated onto boards, discusses fabrication options for both beam turning and embedded interconnections to optoelectronic devices, describes integration processes for creating embedded planar optical interconnections, and discusses measurement results for a number of integration schemes that have been demonstrated by the authors. In the area of optical interconnections with beams coupled to and from the board, the topics covered include integrated metal-coated polymer mirrors and volume holographic gratings for optical beam turning perpendicular to the board. Optical interconnections that utilize active thin film (approximately 1-5 μm thick) optoelectronic components embedded in the board are also discussed, using both Si and high temperature FR-4 substrates. Both direct and evanescent coupling of optical signals into and out of the waveguide are discussed using embedded optical lasers and photodetectors. [ABSTRACT FROM AUTHOR]

This paper reviews methods for assessing familial aggregation of disease based on simple logistic regression models. Studies are based on a case-control sampling design, where the disease status of the first degree relatives of both cases and controls are obtained. Both ‘proband predictive’ and ‘family predictive’ models are discussed, and an example is given using a case-control sample from a lung cancer study in non-smokers. The methods are extended to characterize co-aggregation of two disorders, that is, presence of one disorder in the proband increases the risk of a second disorder in the relative. An example involving eating disorders and depression is given. Copyright © 2003 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Using large-sample theory, we present a unified approach to power calculations for family-based association tests. Currently available methods for power calculations are restricted to special designs or require approximations or simulations. Our analytical approach to power calculations is broadly applicable in many settings. We discuss power calculations for two scenarios that have high practical relevance and in which power previously could only be assessed by simulation studies or by approximations: (1) studies using both affected and unaffected offspring and (2) studies with missing parental information. When the population prevalence is high, it can be worthwhile to genotype unaffected offspring. For many scenarios, high power can be achieved with reasonable sample sizes, even when no parental information is available. [ABSTRACT FROM AUTHOR]

This article describes the social psychological process that underlies the cultural transition of sojourners. Herein the empirical and theoretical literature on cultural transitions (and in particular cultural repatriation and the relevant literature on self-concept and identity) is analyzed, critiqued, and synthesized in an attempt to understand the near ubiquitous distress experienced during repatriation. The relation among self-concept, cultural identity, and cultural transitions is explored, and in light of the paucity of comprehensive repatriation models, a new predictive model is proposed that explicates these relations. Shifts in cultural identity are classified as subtractive, additive, affirmative, or intercultural, and research directions are suggested. [ABSTRACT FROM AUTHOR]

Introduction: Nowadays, there is promising evidence that psychosocial interventions could be helpful in paediatric oncology. Thus, this review aimed to describe the impact of psychosocial interventions on cancer‐related health outcomes in children. Methods: Fifteen English electronic databases were searched from October to December 2020. Only randomised controlled trials that (1) included children ≤18 years old diagnosed with cancer, (2) evaluated the effects of psychosocial interventions, and (3) reported health outcomes including quality of life, anxiety, depression, stress, distress, self‐esteem, psychological adjustment, treatment adherence, pain, fatigue, and academic performance were included. Results: Ten RCTs were included in this review. Six types of psychosocial interventions (social skill training, music‐based intervention, therapeutic play, cognitive therapy, wish intervention, and art therapy) were identified. The studies were assessed as having low to high risk of bias. Nine of the studies reported significant improvement in at least one outcome measure. But quantifying the pooled effect was not applicable due to the heterogeneity of interventions. Conclusion: Psychosocial interventions could be beneficial in paediatric oncology. Yet, the outcomes were reported in heterogeneous types of interventions and participants. The results underscore the need to conduct further studies that include participants with specific cancer diagnoses and types of interventions. [ABSTRACT FROM AUTHOR]

In this article we describe a likelihood-based regression model appropriate for analyzing incomplete multivariate binary responses. We focus on "marginal models"; that is, models where the marginal mean or expectation of the binary response is related to a set of covariates. The association between the binary responses is modeled in terms of conditional log odds ratios. When the nonresponse mechanism is ignorable, it is not necessary to specify a nonresponse model, and valid inferences can be obtained provided that the likelihood for the responses has been correctly specified. But when the nonresponse mechanism is nonignorable, valid inferences can only be obtained by incorporating a model for nonresponse. An unresolved issue with nonignorable models concerns the identifiability of the parameters. So far, no general and practically useful necessary and sufficient conditions for identifiability are available. Here we suggest some simple procedures for examining the identifiability status of nonignorable models when the response variable is discrete. Finally, we present results for an analysis of multiple informant data from the New Haven Child Survey and the Eastern Connecticut Child Survey. [ABSTRACT FROM AUTHOR]

This article presents a method of obtaining smoothed curves for a sample of individuals that permits an arbitrary number and spacing of observations for each individual. We consider the case where each individual's curve cannot be separately estimated because either the ni's are too small or no suitable parametric forms for the random effects are available. The model assumes a parametric form for the population mean curve and the correlation of the repeated measures. The assumed correlation structure is evaluated using the empirical semivariogram, a function of the sum of the squared differences of within-individual residuals. A method is proposed to validate the form and stationarity of the correlation structure. Maximum likelihood estimates for the population mean parameters and variance components are obtained simultaneously. These estimates may be used to create a semiparametric differentiable curve and to predict future values for each individual using a method called kriging. This method also yields instantaneous estimates of growth velocity. An example of this method is presented, and connections to kriging are discussed. [ABSTRACT FROM AUTHOR]

Developmental toxicity studies of laboratory animals play a crucial role in the testing and regulation of chemicals and pharmaceutical compounds. Exposure to developmental toxicants typically causes a variety of adverse effects, such as fetal malformations and reduced fetal weight at term. In this article, we discuss regression methods for jointly analyzing bivariate discrete and continuous outcomes that are motivated by the statistical problems that arise in analyzing data from developmental toxicity studies. We focus on marginal regression models; that is, models in which the marginal expectation of the bivariate response vector is related to a set of covariates by some known link functions. In these models the regression parameters for the marginal expectation are of primary scientific interest, whereas the association between the binary and continuous response is considered to be a nuisance characteristic of the data. We describe a likelihood-based approach, based on the general location model of Olkin and Tate, that yields maximum likelihood estimates of the marginal mean parameters that are robust to misspecification of distributional assumptions. Finally, we describe an extension of this model to allow for clustering, using generalized estimating equations, a multivariate analog of quasi-likelihood. A motivating example, using fetal weight and malformation data from a developmental toxicity study of ethylene glycol in mice, illustrates this methodology. [ABSTRACT FROM AUTHOR]

One approach to inference for means or linear regression parameters when the outcome is subject to nonignorable nonresponse is mixture modeling. Mixture models assume separate parameters for respondents and nonrespondents; implementation by multiple imputation consists of repeatedly filling in missing values for nonrespondents, estimating parameters using the filled-in data, and then adjusting for variability between imputations. We evaluated the performance of this scheme using simulated data with a 25% sample of nonrespondents followed up. We conclude that it provides a generally satisfactory and robust approach to inference for means and regression parameters in this case, although a greater number of imputations may be required for good performance compared to the number required for estimation when nonresponse is ignorable. [ABSTRACT FROM AUTHOR]

Intuition suggests that altering the covariance structure of a parametric model for repeated-measures data alters the variances of the model's estimated mean parameters. The purpose of this article is to sharpen such intuition for a family of growth-curve models with differing numbers of random effects for the individual sampling units and with a fixed structure on the mean. For every member of this family, the maximum likelihood (ML) estimator of the fixed effects is identical to the ordinary least squares (OLS) estimator. In addition, simple closed-form ML and restricted maximum likelihood estimators for the variance and covariance parameters exist for every member. As a consequence, closed-form expressions for the estimated variance-covariance matrix of the OLS estimator of the fixed effects also exist for the entire family. We derive explicit relationships between the variance and covariance parameter estimators from different members of the family and thereby extend some familiar results. For example, it is well known that for balanced and complete longitudinal designs the compound symmetry assumption for the covariance structure of the serial observations (i.e., assuming one random effect for each sampling unit) yields a more precise estimate of the slope of the population growth curve than of its intercept. It is also well known that for such designs the diagonal covariance structure assumption of OLS regression (i.e., no random effects for the units) yields a more precise estimate of the intercept than does the compound symmetry assumption, and a less precise estimate of the slope. We extend such relationships as these to growth-curve models whose covariance structures are of increasing linear... [ABSTRACT FROM AUTHOR]

This article reports results from a longitudinal study investigating the effects of low-to-moderate prenatal and postnatal lead exposure on the cognitive development of children during the first 18 months of life. Study hypotheses are expressed as a sequence of linear models for the outcome variable adjusted score on the Bayley Scales of Mental Development (MDIA), as a function of cord blood-lead concentration, infant blood-lead concentration at semiannual examinations, and other characteristics of study participants. These models are fitted to MDIA measurements on three occasions for as many as 214 infants, first assuming an arbitrary multivariate covariance structure for the repeated measurements and then with covariance structure arising from a random-effects model for errors. Estimates of the effects of lead exposure are not sensitive to the assumed covariance structure. The article describes several approaches to residual analysis and outlier detection in the longitudinal setting. In particular, it shows how empirical Bayes residuals can be used to estimate the partial regression coefficient of covariates not included in the linear model. The major findings concerning the effect of lead exposure on cognitive development are (a) a clear association between cord blood-lead concentration and Bayley scores in the first 18 months of life, (b) no clear evidence of an effect of cumulative postnatal exposure, and (c) a tendency for children who had higher lead concentrations at 6 months of age to exhibit poorer performance at 18 months than children with low lead concentrations. These findings have implications for acceptable blood-lead concentrations in children and pregnant women. [ABSTRACT FROM AUTHOR]

We develop a log-linear model for categorical response subject to nonignorable nonresponse. The paper differs from Fay (1986) in its focus on estimation and hypothesis testing in a regression setting, as opposed to imputation in a multivariate setting. We present several new results concerning the existence of solutions on the boundary of the parameter space and the construction of confidence intervals for estimates. We illustrate the method by estimating the proportion of voters preferring Truman in a 1948 preelection poll (Mosteller, Hyman, McCarthy, Marks, and Truman 1949). Results may depend strongly on the model assumed for nonresponse; goodness-of-fit tests are available for comparing alternative models. [ABSTRACT FROM AUTHOR]

Consider the model with data generated by the following two-stage process. First, a parameter theta is sampled from a prior distribution G, and then an observation is sampled from the conditional distribution f(y | theta). If the prior distribution is known, then the Bayes estimate under squared error loss is the posterior expectation of theta conditional on the data y. For example, if G is Gaussian with mean mu and variance tau[sup 2] and f(y | theta) is Gaussian with mean theta and variance sigma[sup 2], then the posterior distribution is Gaussian with mean beta mu + (1 - B)y and variance sigma[sup 2](1 - B), where B = sigma[sup 2]/(sigma[sup 2] + tau[sup 2]). Inferences about theta are based on this distribution. We study the application of the bootstrap to situations where the prior must be estimated from the data (empirical Bayes methods). For this model, we observe data Y[sup T] = [Y[sub 1], ..., Y[sub K]][sup T], each independent Y[sub k] following the compound model described previously. As first shown by James and Stein (1961), setting each. Theta[sub k] equal to its estimated posterior mean, (1 - B)Y[sub k] + B mu, where it = Y, B = min[1, (K - 3)sigma[sup 2]/S[sup 2], and S[sup 2] = SIGMA[sup K, sub k=1] (Y[sub k] - Y)[sup 2], produces estimates with smaller summed squared error loss than the maximum likelihood estimates theta[sub k] = Y[sub k]. In many applications, confidence intervals or other summaries are required, but computing them from the posterior based on an estimated prior (the naive approach) generally is inappropriate. These posterior distributions fail to account for the uncertainty in estimating the prior and, therefore, may be too compact or have an inappropriate shape. Several approaches have been proposed for incorporating this uncertainty, ranging from Bayes-empirical Bayes based on the introduction of a hyperprior (Deely and Lindley 1981), to use of the delta method (Morris 1983a,b). We develop and study bootstrap methods for... [ABSTRACT FROM AUTHOR]

Presents a 30-year follow-up study of inner-city children and their mothers in the Pathways to Adulthood Study. Associations in transgenerational timing of age at first birth between mothers and their daughters and sons; Relations between intergenerational age patterns and the children's family and personal characteristics during childhood and adolescence.

Presents a meta-analysis of empirical long-term antiarrhythmic therapy after myocardial infarction. Clinical characteristics of people who become victims of sudden cardiac death; Risk factors for increased mortality after myocardial infarction; Statistical methods used for summarizing data from individual studies concerning the condition.

Discusses selection models as an approach to dealing with the problem of nonignorable nonresponse in statistics. Nonparametric estimation of the mean response; Pattern-mixture models; Simple semiparametric pattern-mixture models.

The minimum 248 nm, 25 ns, and 532 nm, 15 ns laser fluences required to blow off thin gold films from optical quartz have been measured as a function of film thickness. The films apparently blow off when the gold-quartz interface reaches the normal boiling point of gold. Even though the initial reflectivities at the two wavelengths are very different, the actual laser fluences required to blow off the films are very similar. While the reflectivities above the melting point appear to be very low, as expected, large decreases in the reflectivity at 532 nm may also occur prior to film melting. [ABSTRACT FROM AUTHOR]

The transmission through thin gold films on optical quartz during laser blow-off with 15 ns, 532 nm laser pulses has been measured. Dramatic changes in transmission mark the duration of the blow-off event with laser fluences above the threshold for removal. The integrated laser fluence required to blow-off the films is roughly independent of incident laser fluence, and is close to that expected to raise the temperature of the film to the boiling point at the film-support interface. [ABSTRACT FROM AUTHOR]

Achilles tendon disorders, including tendinopathy and ruptures, are common among competitive runners. Relatively high complication rates, recurring injuries, and the need to return to sport have led to the use of regenerative medical treatment in tendon disorders in competitive athletes. Biologic therapies, including bone marrow aspirate concentrate (BMAC) injections, have been effective in restoring injured tissue in a limited number of cases. In this case, a collegiate cross country runner with Achilles tendon pain underwent years of failed, non-surgical conservative management. The patient's MRI demonstrated moderate distal calcaneus tendinosis with high-grade partial thickness tearing of the anterior fibers of the Achilles tendon (50% tear). The patient underwent peritendinous injection of BMAC. Post-procedure MRI demonstrated minimal tendinosis of the distal and lateral margins of the Achilles tendon, and no evidence of Achilles tendon tear. The patient followed a progressive return to running program, ultimately training 40 miles per week with minimal Achilles tendon pain. [ABSTRACT FROM AUTHOR]

The article provides information on a study which examined discrepancies in the health history form that incorporated the adverse childhood experiences (ACEs) reported by caregivers on the health history form versus those told to the social workers during therapy. Topics discussed include methodology of the study, ACEs with the greatest change, and limitations of the study.

The article presents a rejoinder by authors to comments made by scholars B. Efron, Joe R. Hill and C.N. Morris on their article " Empirical Bayes Confidence Intervals Based on Bootstrap Samples." Our article has several goals, introducing an empirical Bayes (EB) bootstrap, investigating the properties of one method of using the bootstrap for computing EB confidence intervals and generating discussion on philosophical and technical approaches. Discussants have contributed enormously to our efforts both by elucidating many important points of our article and making specific suggestions for modifications or alternate approaches that are likely to improve our method. Efron, Hill and Morris observe that our bootstrap uses the sampling distribution as a posterior distribution. Although there is no philosophical basis for this substitution, this bootstrap successfully adjusts for variation in estimating the prior. Its potential merit lies in EB properties and its true test will come in more complicated settings and in competition with other approaches. Efron suggests using the bootstrap samples in a different way, namely, to calibrate the naive intervals to have the appropriate EB coverage.

Study Objective Examine the association of age at first birth with body mass index (BMI), and explore the role of young maternal age and subsequent obesity. Design, Setting, Participants, and Interventions This study analyzed data from the Panel Study of Income Dynamics, a nationally representative longitudinal study of US families. Analyses were conducted using a mixed effects longitudinal linear regression with a random intercept to examine the effect of aging, age at first birth, and minority status using nested data. Study criteria yielded a final sample of 146 women with 707 observations. Main Outcome Measures BMI. Results Age at first birth exhibited a significant association with BMI. The association of age at first birth with BMI was greatest for women age 21 and younger. Overall, women who experienced their first birth at age 21 or younger had a BMI 5 units greater than women who delayed childbearing until at least age 30 (point estimate, 5.02; P = .02; 95% confidence interval, 0.65–9.40). Conclusion Young maternal age at first birth might be associated with increased BMI. Minority women also experience their first birth at younger ages compared with white women, suggesting possible linkages between the timing of reproductive events and obesity disparities. [ABSTRACT FROM AUTHOR]

The article reviews the book "Supervising the Reflective Practitioner: An Essential Guide to the Theory and Practice," by Joyce Scaife.

Motivation: Estimating the frequency distribution of copy number variants (CNVs) is an important aspect of the effort to characterize this new type of genetic variation. Currently, most studies report a strong skew toward low-frequency CNVs. In this article, our goal is to investigate the frequencies of CNVs. We employ a two-step procedure for the CNV frequency estimation process. We use family information a posteriori to select only the most reliable CNV regions, i.e. those showing high rates of Mendelian transmission. Results: Our results suggest that the current skew toward low-frequency CNVs may not be representative of the true frequency distribution, but may be due, among other reasons, to the non-negligible false negative rates that characterize CNV detection methods. Moreover, false positives are also likely, as low-frequency CNVs are hard to detect with small sample sizes and technologies that are not ideally suited for their detection. Without appropriate validation methods, such as incorporation of biologically relevant information (for example, in our case, the transmission of heritable CNVs from parents to offspring), it is difficult to assess the validity of specific CNVs, and even harder to obtain reliable frequency estimates. Availability: Software implementing the methods described in this article is available for download at the following address: http://www.isites.harvard.edu/icb/icb.do?keyword=k36162 Contact: iionita@hsph.harvard.edu Supplementary informantion: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Compares the transmission/disequilibrium test and parental-genotype reconstruction for X-chromosomal markers in inherited diseases. Mode of disease inheritance; Protection of X-linked markers against spurious association of population stratification; Presence of linkage disequilibrium between loci.

Background: The association between genetic variants on the X chromosome to risk of COPD has not been fully explored. We hypothesize that the X chromosome harbors variants important in determining risk of COPD related phenotypes and may drive sex differences in COPD manifestations. Methods: Using X chromosome data from three COPD-enriched cohorts of adult smokers, we performed X chromosome specific quality control, imputation, and testing for association with COPD case–control status, lung function, and quantitative emphysema. Analyses were performed among all subjects, then stratified by sex, and subsequently combined in meta-analyses. Results: Among 10,193 subjects of non-Hispanic white or European ancestry, a variant near TMSB4X, rs5979771, reached genome-wide significance for association with lung function measured by FEV1/FVC (β 0.020, SE 0.004, p 4.97 × 10–08), with suggestive evidence of association with FEV1 (β 0.092, SE 0.018, p 3.40 × 10–07). Sex-stratified analyses revealed X chromosome variants that were differentially trending in one sex, with significantly different effect sizes or directions. Conclusions: This investigation identified loci influencing lung function, COPD, and emphysema in a comprehensive genetic association meta-analysis of X chromosome genetic markers from multiple COPD-related datasets. Sex differences play an important role in the pathobiology of complex lung disease, including X chromosome variants that demonstrate differential effects by sex and variants that may be relevant through escape from X chromosome inactivation. Comprehensive interrogation of the X chromosome to better understand genetic control of COPD and lung function is important to further understanding of disease pathology. Trial registration Genetic Epidemiology of COPD Study (COPDGene) is registered at ClinicalTrials.gov, NCT00608764 (Active since January 28, 2008). Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints Study (ECLIPSE), GlaxoSmithKline study code SCO104960, is registered at ClinicalTrials.gov, NCT00292552 (Active since February 16, 2006). Genetics of COPD in Norway Study (GenKOLS) holds GlaxoSmithKline study code RES11080, Genetics of Chronic Obstructive Lung Disease. [ABSTRACT FROM AUTHOR]

Discusses the nursing intervention for the possible relapse of substance abusers. Line drawn between concern and interference; Evaluation of the ability of the patient to cope with stress; Responsibility of the nurse to help and not to coerce.

Summary Identifying population stratification and genotyping error are important for candidate gene association studies using the Transmission Disequilibrium Test (TDT). Although the TDT retains the prespecified Type I error in the presence of population stratification, the test may have decreased power in the presence of population stratification. Genotyping error can also cause the TDT to have an elevated Type I error. Differentiating population stratification from genotyping error remains a challenge for geneticists. Both genotyping error and population stratification can result in an increase in the observed homozygosity of a sample relative to that expected assuming Hardy-Weinberg Equilibrium (HWE). We show that when family data are available, even if a limited number of markers are genotyped, evaluating the markers that show statistically significant deviation from HWE with the Mating Type Distortion Test (MTDT) - a test based on the mating type distribution - can reliably differentiate genotyping error from population stratification. We simulate data based on several models of genotyping error in previously published literature, and show how this method could be used in practice to assist in differentiating population stratification from systematic genotyping error. [ABSTRACT FROM AUTHOR]

Increasing evidence has been provided for a connection between retinoid metabolism and the activity of peroxisome proliferator receptors (Ppars) in the control of body fat reserves. Two different precursors for retinoids exist in the diet as preformed vitamin A (all-trans-retinol) and provitamin A (β,β-arotene). For retinoid production, β,β-carotene is converted to retinaldehyde by β,β-carotene monooxygenase 1 (Bcmol). Previous analysis showed that Bcmol knock-out mice develop dyslipidemia and are more susceptible to diet-induced obesity. However, the role of Bcmol for adipocyte retinoid metabolism has yet not been well defined. Here, we showed that Bcmol mRNA and protein expression are induced during adipogenesis in NIH 3T3-L1 cells. In mature adipocytes, β,β-carotene hut not all-trans-retinol was metabolized to retinoic acid (RA). RA decreased the expression of Pparγ and CCAAT/enhancer-binding protein or, key lipogenic transcription factors, and reduced the lipid content of mature adipocytes. This process was inhibited by the retinoic acid receptor antagonist LE450, showing that it involves canonical retinoid signaling. Accordingly, gavage of β,β-carotene but not all-trans-retinol induced retinoid signaling and decreased Pparγ expression in white adipose tissue of vitamin A-deficient mice. Our study identifies β,β-carotene as a critical physiological precursor for RA production in adipocytes and implicates provitamin A as a dietary regulator of body fat reserves. [ABSTRACT FROM AUTHOR]

New technologies give nurse academicians the opportunity to incorporate innovative teaching-learning strategies into the nursing curricula. Mobile technology for learning, or m-learning, has considerable potential for the nursing classroom but lacks sufficient empirical evidence to support its use. Based on Mayer's multimedia learning theory, the effect of using cooperative and interactive m-learning techniques in enhancing classroom and clinical learning was explored. The relationship between m-learning and students' learning styles was determined through a multimethod educational research study involving nurse practitioner students at two mid-Atlantic universities. During the 16-month period, nurse practitioner students and their faculty used personal digital assistants (PDAs) to participate in various m-learning activities. Findings from focus group and survey responses concluded that PDAs, specifically the Pocket PC, are useful reference tools in the clinical setting and that all students, regardless of learning style, benefited from using PDAs. It was also demonstrated that connecting students with classmates and other nurse practitioner students at distant universities created a cooperative learning community providing additional support and knowledge acquisition. The authors concluded that in order to successfully prepare nurse practitioner graduates with the skills necessary to function in the present and future health care system, nurse practitioner faculty must be creative and innovative, incorporating various revolutionary technologies into their nurse practitioner curricula. [ABSTRACT FROM AUTHOR]

The different genetic variation discovery projects (The SNP Consortium, the International HapMap Project, the 1000 Genomes Project, etc.) aim to identify as much as possible of the underlying genetic variation in various human populations. The question we address in this article is how many new variants are yet to be found. This is an instance of the species problem in ecology, where the goal is to estimate the number of species in a closed population. We use a parametric beta-binomial model that allows us to calculate the expected number of new variants with a desired minimum frequency to be discovered in a new dataset of individuals of a specified size. The method can also be used to predict the number of individuals necessary to sequence in order to capture all (or a fraction of) the variation with a specified minimum frequency. We apply the method to three datasets: the ENCODE dataset, the Seattle SNPs dataset, and the National Institute of Environmental Health Sciences SNPs dataset. Consistent with previous descriptions, our results show that the African population is the most diverse in terms of the number of variants expected to exist, the Asian populations the least diverse, with the European population in-between. In addition, our results show a clear distinction between the Chinese and the Japanese populations, with the Japanese population being the less diverse. To find all common variants (frequency at least 1%) the number of individuals that need to be sequenced is small (∼350) and does not differ much among the different populations; our data show that, subject to sequence accuracy, the 1000 Genomes Project is likely to find most of these common variants and a high proportion of the rarer ones (frequency between 0.1 and 1%). The data reveal a rule of diminishing returns: a small number of individuals (∼150) is sufficient to identify 80% of variants with a frequency of at least 0.1%, while a much larger number (>3,000 individuals) is necessary to find all of those variants. Finally, our results also show a much higher diversity in environmental response genes compared with the average genome, especially in African populations. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this exploratory study of teacher beliefs was twofold: first, to determine whether the construct of academic optimism could be defined and measured as an individual teacher characteristic as it has been at the collective school level, and second, to identify sets of teacher beliefs and practices that were good predictors of academic optimism. With a diverse sample of American elementary teachers, a second-order principal components analysis supported the hypothesis that academic optimism was a general construct composed of efficacy, trust, and academic emphasis. In addition, dispositional optimism, humanistic classroom management, student-centred beliefs and practices, and organizational citizenship behaviour were individually and collectively related to the explanation of a teacher''s sense of academic optimism, controlling for SES. [Copyright &y& Elsevier]

For genomewide association (GWA) studies in family-based designs, we propose a novel two-stage strategy that weighs the association P values with the use of independently estimated weights. The association information contained in the family sample is partitioned into two orthogonal components—namely, the between-family information and the withinfamily information. The between-family component is used in the first (i.e., screening) stage to obtain a relative ranking of all the markers. The within-family component is used in the second (i.e., testing) stage in the framework of the standard family-based association test, and the resulting P values are weighted using the estimated marker ranking from the screening step. The approach is appealing, in that it ensures that all the markers are tested in the testing step and, at the same time, also uses information from the screening step. Through simulation studies, we show that testing all the markers is more powerful than testing only the most promising ones from the screening step, which was the method suggested by Van Steen et al. A comparison with a population-based approach shows that the approach achieves comparable power. In the presence of a reasonable level of population stratification, our approach is only slightly affected in terms of power and, since it is a family-based method, is completely robust to spurious effects. An application to a 100K scan in the Framingham Heart Study illustrates the practical advantages of our approach. The proposed method is of general applicability; it extends to any setting in which prior, independent ranking of hypotheses is available. [ABSTRACT FROM AUTHOR]