939 resultados para COVARIANCE


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We develop statistical procedures for estimating shape and orientation of arbitrary three-dimensional particles. We focus on the case where particles cannot be observed directly, but only via sections. Volume tensors are used for describing particle shape and orientation, and we derive stereological estimators of the tensors. These estimators are combined to provide consistent estimators of the moments of the so-called particle cover density. The covariance structure associated with the particle cover density depends on the orientation and shape of the particles. For instance, if the distribution of the typical particle is invariant under rotations, then the covariance matrix is proportional to the identity matrix. We develop a non-parametric test for such isotropy. A flexible Lévy-based particle model is proposed, which may be analysed using a generalized method of moments in which the volume tensors enter. The developed methods are used to study the cell organization in the human brain cortex.

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The Tibetan Plateau has a significant role with regard to atmospheric circulation and the monsoon in particular. Changes between a closed plant cover and open bare soil are one of the striking effects of land use degradation observed with unsustainable range management or climate change, but experiments investigating changes of surface properties and processes together with atmospheric feedbacks are rare and have not been undertaken in the world's two largest alpine ecosystems, the alpine steppe and the Kobresia pygmaea pastures of the Tibetan Plateau. We connected measurements of micro-lysimeter, chamber, 13C labelling, and eddy covariance and combined the observations with land surface and atmospheric models, adapted to the highland conditions. This allowed us to analyse how three degradation stages affect the water and carbon cycle of pastures on the landscape scale within the core region of the Kobresia pygmaea ecosystem. The study revealed that increasing degradation of the Kobresia turf affects carbon allocation and strongly reduces the carbon uptake, compromising the function of Kobresia pastures as a carbon sink. Pasture degradation leads to a shift from transpiration to evaporation while a change in the sum of evapotranspiration over a longer period cannot be confirmed. The results show an earlier onset of convection and cloud generation, likely triggered by a shift in evapotranspiration timing when dominated by evaporation. Consequently, precipitation starts earlier and clouds decrease the incoming solar radiation. In summary, the changes in surface properties by pasture degradation found on the highland have a significant influence on larger scales.

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BACKGROUND Psychomotor disturbances are a main clinical feature of major depressive disorder (MDD) but little is known about their EEG signature. One of the most replicated EEG findings in MDD is resting frontal asymmetry in the alpha band (FAA), which is thought to be a correlate of withdrawal behavior and reduced approach motivation. The purpose of this study was to assess psychomotor alterations, alpha band power, FAA and investigate the association between them. METHODS 20 MDD patients and 19 healthy subjects were enrolled. Alpha power and FAA scores were calculated from a resting state EEG. Wrist actigraphy was recorded from the non-dominant arm for 24 h and activity level scores (AL) were extrapolated from the wakeful periods. RESULTS MDD patients had a left-lateralized frontal alpha activity and lower AL scores when compared to healthy subjects. A significant correlation was found between mean FAA and AL scores. A negative covariance between power in the lower alpha range and AL scores over the motor cortex bilaterally was detected. LIMITATIONS Relatively small sample size. Patients were pharmacologically treated with antidepressants. CONCLUSIONS This study replicates the finding of left-lateralized FAA and lower AL scores in MDD patients, and establishes the first evidence of significant correlations between alpha power, FAA scores and measures of motor activity, which may be interpreted as an expression of impaired motivational drive in MDD.

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We explore a generalisation of the L´evy fractional Brownian field on the Euclidean space based on replacing the Euclidean norm with another norm. A characterisation result for admissible norms yields a complete description of all self-similar Gaussian random fields with stationary increments. Several integral representations of the introduced random fields are derived. In a similar vein, several non-Euclidean variants of the fractional Poisson field are introduced and it is shown that they share the covariance structure with the fractional Brownian field and converge to it. The shape parameters of the Poisson and Brownian variants are related by convex geometry transforms, namely the radial pth mean body and the polar projection transforms.

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The main objective of this preliminary study was to further clarify the association between testosterone (T) levels and depression by investigating symptom-based depression subtypes in a sample of 64 men. The data were taken from the ZInEP epidemiology survey. Gonadal hormones of a melancholic (n  = 25) and an atypical (n = 14) depression subtype, derived from latent class analysis, were compared with those of healthy controls (n  = 18). Serum T was assayed using an enzyme-linked immunosorbent assay procedure. Analysis of variance, analysis of covariance, non-parametrical tests, and generalized linear regression models were performed to examine group differences. The atypical depressive subtype showed significantly lower T levels compared with the melancholic depressives. While accumulative evidence indicates that, beyond psychosocial characteristics, the melancholic and atypical depressive subtypes are also distinguishable by biological correlates, the current study expanded this knowledge to include gonadal hormones. Further longitudinal research is warranted to disclose causality by linking the multiple processes in pathogenesis of depression.

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Patients with schizophrenia show abnormal dynamics and structure of temporally ­coherent networks (TCNs) assessed using fMRI, which undergo adaptive shifts in preparation for a cognitively demanding task. During working memory (WM) tasks, patients with schizophrenia show persistent deficits in TCNs as well as EEG indices of WM. Studying their temporal relationship during WM tasks might provide novel insights into WM performance deficits seen in schizophrenia. Simultaneous EEG-fMRI data were acquired during the performance of a verbal Sternberg WM task with two load levels (load 2 and load 5) in 17 patients with schizophrenia and 17 matched healthy controls. Using covariance mapping, we investigated the relationship of the activity in the TCNs before the memoranda were encoded and EEG spectral power during the retention interval. We assessed four TCNs – default mode network (DMN), dorsal attention network (dAN), left and right working memory networks (WMNs) – and three EEG bands – theta, alpha, and beta. In healthy controls, there was a load-dependent inverse relation between DMN and frontal midline theta power and an anti-correlation between DMN and dAN. Both effects were not significantly detectable in patients. In addition, healthy controls showed a left-lateralized load-dependent recruitment of the WMNs. Activation of the WMNs was bilateral in patients, suggesting more resources were recruited for successful performance on the WM task. Our findings support the notion of schizophrenia patients showing deviations in their neurophysiological responses before the retention of relevant information in a verbal WM task. Thus, treatment strategies as neurofeedback ­targeting prestates could be beneficial as task performance relies on the preparatory state of the brain.

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Using properties of moment stationarity we develop exact expressions for the mean and covariance of allele frequencies at a single locus for a set of populations subject to drift, mutation, and migration. Some general results can be obtained even for arbitrary mutation and migration matrices, for example: (1) Under quite general conditions, the mean vector depends only on mutation rates, not on migration rates or the number of populations. (2) Allele frequencies covary among all pairs of populations connected by migration. As a result, the drift, mutation, migration process is not ergodic when any finite number of populations is exchanging genes. in addition, we provide closed form expressions for the mean and covariance of allele frequencies in Wright's finite-island model of migration under several simple models of mutation, and we show that the correlation in allele frequencies among populations can be very large for realistic rates of mutation unless an enormous number of populations are exchanging genes. As a result, the traditional diffusion approximation provides a poor approximation of the stationary distribution of allele frequencies among populations. Finally, we discuss some implications of our results for measures of population structure based on Wright's F-statistics.

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It is widely acknowledged in theoretical and empirical literature that social relationships, comprising of structural measures (social networks) and functional measures (perceived social support) have an undeniable effect on health outcomes. However, the actual mechanism of this effect has yet to be clearly understood or explicated. In addition, comorbidity is found to adversely affect social relationships and health related quality of life (a valued outcome measure in cancer patients and survivors). ^ This cross sectional study uses selected baseline data (N=3088) from the Women's Healthy Eating and Living (WHEL) study. Lisrel 8.72 was used for the latent variable structural equation modeling. Due to the ordinal nature of the data, Weighted Least Squares (WLS) method of estimation using Asymptotic Distribution Free covariance matrices was chosen for this analysis. The primary exogenous predictor variables are Social Networks and Comorbidity; Perceived Social Support is the endogenous predictor variable. Three dimensions of HRQoL, physical, mental and satisfaction with current quality of life were the outcome variables. ^ This study hypothesizes and tests the mechanism and pathways between comorbidity, social relationships and HRQoL using latent variable structural equation modeling. After testing the measurement models of social networks and perceived social support, a structural model hypothesizing associations between the latent exogenous and endogenous variables was tested. The results of the study after listwise deletion (N=2131) mostly confirmed the hypothesized relationships (TLI, CFI >0.95, RMSEA = 0.05, p=0.15). Comorbidity was adversely associated with all three HRQoL outcomes. Strong ties were negatively associated with perceived social support; social network had a strong positive association with perceived social support, which served as a mediator between social networks and HRQoL. Mental health quality of life was the most adversely affected by the predictor variables. ^ This study is a preliminary look at the integration of structural and functional measures of social relationships, comorbidity and three HRQoL indicators using LVSEM. Developing stronger social networks and forming supportive relationships is beneficial for health outcomes such as HRQoL of cancer survivors. Thus, the medical community treating cancer survivors as well as the survivor's social networks need to be informed and cognizant of these possible relationships. ^

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The global social and economic burden of HIV/AIDS is great, with over forty million people reported to be living with HIV/AIDS at the end of 2005; two million of these are children from birth to 15 years of age. Antiretroviral therapy has been shown to improve growth and survival of HIV-infected individuals. The purpose of this study is to describe a cohort of HIV-infected pediatric patients and assess the association between clinical factors, with growth and mortality outcomes. ^ This was a historical cohort study. Medical records of infants and children receiving HIV care at Mulago Pediatric Infectious Disease Clinic (PIDC) in Uganda between July 2003 and March 2006 were analyzed. Height and weight measurements were age and sex standardized to Centers for Disease Control and prevention (CDC) 2000 reference. Descriptive and logistic regression analyses were performed to identify covariates associated with risk of stunting or being underweight, and mortality. Longitudinal regression analysis with a mixed model using autoregressive covariance structure was used to compare change in height and weight before and after initiation of highly active antiretroviral therapy (HAART). ^ The study population was comprised of 1059 patients 0-20 years of age, the majority of whom were aged thirteen years and below (74.6%). Mean height-for-age before initiation of HAART was in the 10th percentile, mean weight-for-age was in the 8th percentile, and the mean weight-for-height was in the 23rd percentile. Initiation of HAART resulted in improvement in both the mean standardized weight-for-age Z score and weight-for-age percentiles (p <0.001). Baseline age, and weight-for-age Z score were associated with stunting (p <0.001). A negative weight-for-age Z score was associated with stunting (OR 4.60, CI 3.04-5.49). Risk of death decreased from 84% in the >2-8 years age category to 21% in the >13 years age category respectively, compared to the 0-2 years of age (p <0.05). ^ This pediatric population gained weight significantly more rapidly than height after starting HAART. A low weight-for-age Z score was associated with poor survival in children. These findings suggest that age, weight, and height measurements be monitored closely at Mulago PIDC. ^

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Purpose. The purpose of this randomized control repeated measures trial was to determine the effectiveness of a self-management intervention led by community lay workers called promotoras on the health outcomes of Mexican Americans with type 2 diabetes living in a major city on the Texas - Mexico border. The specific aims of this study, in relation to the intervention group participants, were to: (1) decrease the glycosylated hemoglobin (A1c) blood levels at the six-month assessment, (2) increase diabetes knowledge at the three and six-month assessments, and (3) strengthen the participants' beliefs in their ability to manage diabetes at the three and six-month assessments.^ Methods. One hundred and fifty Mexican American participants were recruited at a Catholic faith-based clinic and randomized into an intervention group and a usual-care control group. Personal characteristics, acculturation and baseline A1c, diabetes knowledge and diabetes health beliefs were measured. The six-month, two-phase intervention was culturally specific and it was delivered entirely by promotoras. Phase One of the intervention consisted of sixteen hours of participative group education and bi-weekly telephone contact follow-up. Phase Two consisted of bi-weekly follow-up using inspirational faith-based health behavior change postcards. The A1c levels, diabetes knowledge and diabetes health beliefs were measured at baseline, and three and six months post-baseline. The mean changes between the groups were analyzed using analysis of covariance. ^ Results. The 80% female sample, with a mean age of 58 years, demonstrated very low: acculturation, income, education, health insurance coverage, and strong Catholicism. No significant changes were noted at the three-month assessment, but the mean change of the A1c levels (F (1, 148 = 10.28, p < .001) and the diabetes knowledge scores (F (1, 148 = 9.0, p < .002) of the intervention group improved significantly at six months, adjusting for health insurance coverage. The diabetes health belief scores decreased in both groups.^ Conclusions. This study demonstrated that an intervention led by promotoras could result in decreased A1c levels and increased diabetes knowledge in spite of the very low acculturation, educational level and insurance coverage of the intervention group participants. Clinical implications and recommendations for future research are suggested. ^

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With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

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Aim: The goal of this study was to evaluate the change in hemoglobin A1C and glycemic control after nutrition intervention among a population of type 1 diabetic pediatric patients. Methods: Data was collected from all type 1 diabetic patients who were scheduled for a consultation with the diabetes/endocrine RD from January 2006 through December 2006. Two groups were compared, those who kept their RD appointment and those who did not keep their appointment. The main outcome measure was HgbA1C. An independent samples t-test compared the two groups with respect to change in HbgA1C before and after the most recent scheduled appointment with the RD. Baseline characteristics were used as covariates and analyzed and controlled for using analysis of covariance (ANCOVA). Results: There was no difference in HgbA1c after either attending an RD appointment or not having attended an RD appointment. Those who arrived for and attended their RD appointment and those who did not arrive for and attend their RD appointment, had statistically different HgbA1C's before their scheduled appointment as well as after the RD appointment. However, the two groups were not equal at the beginning of the study period. Discussion: A study design with inclusion criteria of a specified range of HgbA1C values within which the study subjects needed to fall, would have potentially eliminated the difference between the two groups at the beginning of the study period. Conducting either another retrospective study that controlled for the initial HgbA1C value or conducting a prospective study that designated a range of HgbA1C values would be worth investigating to evaluate the impact of medical nutrition therapy intervention and the role of the RD in diabetes management. It is an interesting finding that there was a significant difference in the initial HgbA1c for those who came to the RD appointment compared to those who did not come. The fact that in this study those who did not arrive for their RD appointment had worse control of their diabetes suggests that this is a high-risk group. Targeting diabetes education toward this group of patients may prove to be beneficial. ^

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Purpose. The purpose of this study was to investigate the impact of a motivational weight management DVD on knowledge of obesity related diseases, readiness, motivation, and self-efficacy to lose weight, connectedness to their care provider, and patients return to clinic. Design. A randomized control trial was conducted in which 40 overweight/obese adolescents and their parents/caregivers were randomly assigned to standard care alone or standard care plus DVD. Subjects completed a set of pre- and post-questionnaire measures. A group of 22 patients was also formed as a historical control group in order to account for the potential effect of extra attention given to subjects prospectively enrolled. Methods. The adolescents and their parent/caregiver were placed into a patient room. Consent was obtained and a set of written pre-questionnaires were given to both the parent and the adolescent. Standard care was provided to all patients by the Registered Dietitian and physician; the DVD was shown in addition to standard care among the intervention group. A set of post-questionnaires were given and compensation was provided. Analysis. Groups were compared to determine equivalence at baseline. Analysis of covariance was used to evaluate changes over time, while controlling for pre-test scores and race/ethnicity. Results. Parents who viewed the DVD experienced greater changes in correct knowledge as compared to parents who did not view the DVD. Conclusion. Our study found only one substantial benefit of the DVD beyond standard clinical practices. This is an important area for change as it increased awareness of obesity as a serious disease and has future clinical implications.^

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Current statistical methods for estimation of parametric effect sizes from a series of experiments are generally restricted to univariate comparisons of standardized mean differences between two treatments. Multivariate methods are presented for the case in which effect size is a vector of standardized multivariate mean differences and the number of treatment groups is two or more. The proposed methods employ a vector of independent sample means for each response variable that leads to a covariance structure which depends only on correlations among the $p$ responses on each subject. Using weighted least squares theory and the assumption that the observations are from normally distributed populations, multivariate hypotheses analogous to common hypotheses used for testing effect sizes were formulated and tested for treatment effects which are correlated through a common control group, through multiple response variables observed on each subject, or both conditions.^ The asymptotic multivariate distribution for correlated effect sizes is obtained by extending univariate methods for estimating effect sizes which are correlated through common control groups. The joint distribution of vectors of effect sizes (from $p$ responses on each subject) from one treatment and one control group and from several treatment groups sharing a common control group are derived. Methods are given for estimation of linear combinations of effect sizes when certain homogeneity conditions are met, and for estimation of vectors of effect sizes and confidence intervals from $p$ responses on each subject. Computational illustrations are provided using data from studies of effects of electric field exposure on small laboratory animals. ^

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Diabetes mellitus occurs in two forms, insulin-dependent (IDDM, formerly called juvenile type) and non-insulin dependent (NIDDM, formerly called adult type). Prevalence figures from around the world for NIDDM, show that all societies and all races are affected; although uncommon in some populations (.4%), it is common (10%) or very common (40%) in others (Tables 1 and 2).^ In Mexican-Americans in particular, the prevalence rates (7-10%) are intermediate to those in Caucasians (1-2%) and Amerindians (35%). Information about the distribution of the disease and identification of high risk groups for developing glucose intolerance or its vascular manifestations by the study of genetic markers will help to clarify and solve some of the problems from the public health and the genetic point of view.^ This research was designed to examine two general areas in relation to NIDDM. The first aims to determine the prevalence of polymorphic genetic markers in two groups distinguished by the presence or absence of diabetes and to observe if there are any genetic marker-disease association (univariate analysis using two by two tables and logistic regression to study the individual and joint effects of the different variables). The second deals with the effect of genetic differences on the variation in fasting plasma glucose and percent glycosylated hemoglobin (HbAl) (analysis of Covariance for each marker, using age and sex as covariates).^ The results from the first analysis were not statistically significant at the corrected p value of 0.003 given the number of tests that were performed. From the analysis of covariance of all the markers studied, only Duffy and Phosphoglucomutase were statistically significant but poor predictors, given that the amount they explain in terms of variation in glycosylated hemoglobin is very small.^ Trying to determine the polygenic component of chronic disease is not an easy task. This study confirms the fact that a larger and random or representative sample is needed to be able to detect differences in the prevalence of a marker for association studies and in the genetic contribution to the variation in glucose and glycosylated hemoglobin. The importance that ethnic homogeneity in the groups studied and standardization in the methodology will have on the results has been stressed. ^