916 resultados para Auto-correlation function
Resumo:
Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.
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This paper proposes a linear quantile regression analysis method for longitudinal data that combines the between- and within-subject estimating functions, which incorporates the correlations between repeated measurements. Therefore, the proposed method results in more efficient parameter estimation relative to the estimating functions based on an independence working model. To reduce computational burdens, the induced smoothing method is introduced to obtain parameter estimates and their variances. Under some regularity conditions, the estimators derived by the induced smoothing method are consistent and have asymptotically normal distributions. A number of simulation studies are carried out to evaluate the performance of the proposed method. The results indicate that the efficiency gain for the proposed method is substantial especially when strong within correlations exist. Finally, a dataset from the audiology growth research is used to illustrate the proposed methodology.
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Objective To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens "Generalized Estimating Equations. Notes on the Choice of the Working Correlation Matrix". Methods Inviting an international group of experts to comment on this paper. Results Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data Applied statisticians; commented on practical aspects in data analysis. Conclusions In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations, (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data This particularly applies to the situation when data are missing at random.
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Selecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well-known criterion of QIC for selecting a working correlation Structure. and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads LIS to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study.
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We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.
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We had earlier proposed a hypothesis to explain the mechanism of perpetuation of immunological memory based on the operation of idiotypic network in the complete absence of antigen. Experimental evidences were provided for memory maintenance through anti-idiotypic antibody (Ab(2)) carrying the internal image of the antigen. In the present work, we describe a structural basis for such memory perpetuation by molecular modeling and structural analysis studies. A three-dimensional model of Ab(2) was generated and the structure of the antigenic site on the hemagglutinin protein H of Rinderpest virus was modeled using the structural template of hemagglutinin protein of Measles virus. Our results show that a large portion of heavy chain containing the CDR regions of Ab(2) resembles the domain of the hemagglutinin housing the epitope regions. The similarity demonstrates that an internal image of the H antigen is formed in Ab(2), which provides a structural basis for functional mimicry demonstrated earlier. This work brings out the importance of the structural similarity between a domain of hemagglutinin protein to that of its corresponding Ab(2). It provides evidence that Ab(2) is indeed capable of functioning as surrogate antigen and provides support to earlier proposed relay hypothesis which has provided a mechanism for the maintenance of immunological memory.
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We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "Working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.
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Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.
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Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.
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Prostate cancer is a leading contributor to male cancer-related deaths worldwide. Kallikrein-related peptidases (KLKs) are serine proteases that exhibit deregulated expression in prostate cancer, with KLK3, or prostate specific antigen (PSA), being the widely-employed clinical biomarker for prostate cancer. Other KLKs, such as KLK2, show promise as prostate cancer biomarkers and, additionally, their altered expression has been utilised for the design of KLK-targeted therapies. There is also a large body of in vitro and in vivo evidence supporting their role in cancer-related processes. Here, we review the literature on studies to date investigating the potential of other KLKs, in addition to PSA, as biomarkers and in therapeutic options, as well as their current known functional roles in cancer progression. Increased knowledge of these KLK-mediated functions, including degradation of the extracellular matrix, local invasion, cancer cell proliferation, interactions with fibroblasts, angiogenesis, migration, bone metastasis and tumour growth in vivo, may help define new roles as prognostic biomarkers and novel therapeutic targets for this cancer.
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Pancreatic exocrine dysfunction has been frequently recorded in protein-energy malnutrition in underdeveloped countries. In addition, the pancreas requires optimal nutrition for enzyme synthesis and potentially correctable pancreatic enzyme insufficiency may play a role in the continuation of protein-energy malnutrition. This problem has not been previously evaluated in Australian Aborigines. We have applied a screening test for pancreatic dysfunction (human immunoreactive trypsinogen [IRT] assay) to the study of 398 infants (6-36 months) admitted to the Alice Springs Hospital over a 20-month period. All infants were assessed by anthropometric measures and were assigned to to three nutritional groups (normal, moderate or severely malnourished) and two growth groups (stunted or not stunted). Of the 198 infants who had at least a single serum cationic trypsinogen measurement taken, normal values for serum IRT (with confidence limits) were obtained from 57 children, who were normally nourished. IRT levels were significantly correlated with the degree of underweight but there was no correlation with the degree of stunting or age. Mean IRT levels for the moderate and severely underweight groups were significantly greater than the mean for the normal group (P < 0.01). Seventeen children (8.6%) had trypsinogen levels in excess of the 95th percentile for the normally nourished group, reflecting acinar cell damage or ductal obstruction. We conclude that pancreatic dysfunction may be a common and important overlooked factor contributing to ongoing malnutrition and diseases in malnourished Australian Aboriginal children.
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Statistical methods are often used to analyse commercial catch and effort data to provide standardised fishing effort and/or a relative index of fish abundance for input into stock assessment models. Achieving reliable results has proved difficult in Australia's Northern Prawn Fishery (NPF), due to a combination of such factors as the biological characteristics of the animals, some aspects of the fleet dynamics, and the changes in fishing technology. For this set of data, we compared four modelling approaches (linear models, mixed models, generalised estimating equations, and generalised linear models) with respect to the outcomes of the standardised fishing effort or the relative index of abundance. We also varied the number and form of vessel covariates in the models. Within a subset of data from this fishery, modelling correlation structures did not alter the conclusions from simpler statistical models. The random-effects models also yielded similar results. This is because the estimators are all consistent even if the correlation structure is mis-specified, and the data set is very large. However, the standard errors from different models differed, suggesting that different methods have different statistical efficiency. We suggest that there is value in modelling the variance function and the correlation structure, to make valid and efficient statistical inferences and gain insight into the data. We found that fishing power was separable from the indices of prawn abundance only when we offset the impact of vessel characteristics at assumed values from external sources. This may be due to the large degree of confounding within the data, and the extreme temporal changes in certain aspects of individual vessels, the fleet and the fleet dynamics.
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Background Sensorimotor function is degraded in patients after lower limb arthroplasty. Sensorimotor training is thought to improve sensorimotor skills, however, the optimal training stimulus with regard to volume, frequency, duration, and intensity is still unknown. The aim of this study, therefore, was to firstly quantify the progression of sensorimotor function after total hip (THA) or knee (TKA) arthroplasty and, as second step, to evaluate effects of different sensorimotor training volumes. Methods 58 in-patients during their rehabilitation after THA or TKA participated in this prospective cohort study. Sensorimotor function was assessed using a test battery including measures of stabilization capacity, static balance, proprioception, and gait, along with a self-reported pain and function. All participants were randomly assigned to one of three intervention groups performing sensorimotor training two, four, or six times per week. Outcome measures were taken at three instances, at baseline (pre), after 1.5 weeks (mid) and at the conclusion of the 3 week program (post). Results All measurements showed significant improvements over time, with the exception of proprioception and static balance during quiet bipedal stance which showed no significant main effects for time or intervention. There was no significant effect of sensorimotor training volume on any of the outcome measures. Conclusion We were able to quantify improvements in measures of dynamic, but not static, sensorimotor function during the initial three weeks of rehabilitation following TKA/THA. Although sensorimotor improvements were independent of the training volume applied in the current study, long-term effects of sensorimotor training volume need to be investigated to optimize training stimulus recommendations.
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A simple volume dilatometer is described for the precise measurements of volume changes as a function of temperature in liquid mixtures. The expansivity of (cyclohexane + acetic anhydride) in the critical region was measured. The critical solution temperature Tc was approached to within 9 mK. For T > (Tc + 0.3 K), the results results follow both a logarithmic and a power-law behaviour with an exponent ≈ 1/8. But for T < (Tc + 0.3 K), the results seem to be affected possibly by gravity or temperature gradients. In this region, the expected expansivity anomaly is rounded off to a cusp. The expansivity shows a reduced anomaly for off-critical compositions. A discussion of the local extremum and a correlation between negative expansivity and the resistivity anomaly are also given.
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This book is a study on learning, teaching/counselling, and research on the two. My quest has been to find a pedagogically-motivated way of researching learning and teaching interaction, and in particular counselling, in an autonomous language-learning environment. I have tried to develop a method that would make room for lived experience, meaning-making and narrating, because in my view these all characterise learning encounters between language learners and counsellors, and learners and their peers. Lived experience as a source of meaning, telling and co-telling becomes especially significant when we try to listen to the diverse personal and academic voices of the past as expressed in autobiographical narratives. I have aimed at researching various ALMS dialogues (Autonomous Learning Modules, University of Helsinki Language Centre English course and programme), and autobiographical narratives within them, in a way that shows respect for the participants, and that is relevant, reflective and, most importantly, self-reflexive. My interest has been in autobiographical telling in (E)FL [(English as a) foreign language], both in students first-person written texts on their language- learning histories and in the sharing of stories between learners and a counsellor. I have turned to narrative inquiry in my quest and have written the thesis as an experiential narrative. In particular, I have studied learners and counsellors in one and the same story, as characters in one narrative, in an attempt to avoid the impression that I am telling yet another separate, anecdotal story, retrospectively. Through narrative, I have shed light on the subjective dimensions of language learning and experience, and have come closer to understanding the emotional aspects of learning encounters. I have questioned and rejected a distanced and objective approach to describing learning and teaching/counselling. I have argued for a holistic and experiential approach to (E)FL encounters in which there is a need to see emotion and cognition as intertwined, and thus to appreciate learners and counsellors emotionally-charged experiences as integral to their identities. I have also argued for a way of describing such encounters as they are situated in history, time, autobiography, and the learning context. I have turned my gaze on various constellations of lived experience: the data was collected on various occasions and in various settings during one course and consists of videotaped group sessions, individual counselling sessions between students and their group counsellor, biographic narrative interviews with myself, open-ended personally-inspired reflection texts written by the students about their language-learning histories, and student logs and diaries. I do not consider data collection an unproblematic occasion, or innocent practice, and I defend the integrity of the research process. Research writing cannot be separated from narrative field work and analysing and interpreting the data. The foci in my work have turned to be the following: 1) describing ALMS encounters and specifying their narrative aspects; 2) reconceptualising learner and teacher autonomy in ALMS and in (E)FL; 2) developing (E)FL methodologically through a teacher-researcher s identity work; 4) research writing as a dialogical narrative process, and the thesis as an experiential narrative. Identity and writing as inquiry, and the deeply narrative and autobiographical nature of the (E)FL teaching/counselling/researching have come to the fore in this research. Research writing as a relational activity and its implications for situated ways of knowing and knowledge turned out to be important foci. I have also focussed on the context-bound and local teacher knowledge and ways of knowing about being a teacher, and I have argued for personal ways of knowing about, and learning and studying foreign languages. I discuss research as auto/biography: as a practising counsellor I use my own life and (E)FL experience to understand and interpret the stories of the research participants even though I was not involved in their course work. The supposedly static binaries of learner/teacher, and also learner autonomy/teacher autonomy, are thus brought into the discussion. I have highlighted the infinite variability and ever-changing nature of learning and teaching English, but the book is also of relevance to foreign language education in general.