bluuebunny/crossref_metadata_2025 huggingface dataset:
A predictive model for local recurrence after transanal endoscopic microsurgery for rectal cancer
Authors: Bach S P , Hill J , Monson J R T , Simson J N L , Lane L , Merrie A , Warren B , Mortensen N J McC
Published: February 2009

Background

The outcome of local excision of early rectal cancer using transanal endoscopic microsurgery (TEM) lacks consensus. Screening has substantially increased the early diagnosis of tumours. Patients need local treatments that are oncologically equivalent to radical surgery but safer and functionally superior.

Methods

A national database, collated prospectively from 21 regional centres, detailed TEM treatment in 487 subjects with rectal cancer. Data were used to construct a predictive model of local recurrence after TEM using semiparametric survival analyses. The model was internally validated using measures of calibration and discrimination.

Results

Postoperative morbidity and mortality were 14·9 and 1·4 per cent respectively. The Cox regression model predicted local recurrence with a concordance index of 0·76 using age, depth of tumour invasion, tumour diameter, presence of lymphovascular invasion, poor differentiation and conversion to radical surgery after histopathological examination of the TEM specimen.

Conclusion

Patient selection for TEM is frequently governed by fitness for radical surgery rather than suitable tumour biology. TEM can produce long-term outcomes similar to those published for radical total mesorectal excision surgery if applied to a select group of biologically favourable tumours. Conversion to radical surgery based on adverse TEM histopathology appears safe for p T1 and p T2 lesions.
Acute colonic pseudo-obstruction
Authors: De Giorgio R , Knowles C H
Published: February 2009

Background

Acute colonic pseudo-obstruction is characterized by clinical and radiological evidence of acute large bowel obstruction in the absence of a mechanical cause. The condition usually affects elderly people with underlying co-morbidities, and early recognition and appropriate management are essential to reduce the occurrence of life-threatening complications.

Methods

A part-systematic review was conducted. This was based on key publications focusing on advances in management.

Results and conclusions

Although acute colonic dilatation has been suggested to result from a functional imbalance in autonomic nerve supply, there is little direct evidence for this. Other aetiologies derived from the evolving field of neurogastroenterology remain underexplored. The rationale of treatment is to achieve prompt and effective colonic decompression. Initial management includes supportive interventions that may be followed by pharmacological therapy. Controlled clinical trials have shown that the acetylcholinesterase inhibitor neostigmine is an effective treatment with initial response rates of 60–90 per cent; other drugs for use in this area are in evolution. Colonoscopic decompression is successful in approximately 80 per cent of patients, with other minimally invasive strategies continuing to be developed. Surgery has thus become largely limited to those in whom complications occur. A contemporary management algorithm is provided on this basis.
Radioimmunotherapy prevents local recurrence of colonic cancer in an experimental model
Authors: de Jong G M , Boerman O C , Heskamp S , Aarts F , Bleichrodt R P , Hendriks T
Published: February 2009

Background

Radioimmunotherapy (RIT) is suitable for the treatment of microscopic residual disease and might therefore have an adjuvant role after colonic cancer surgery.

Methods

An anastomosis was constructed in male Wag/Rij rats after intraluminal injection of 2 × 106 CC531 tumour cells. The biodistribution of 111In-labelled MG1 monoclonal antibody was assessed after intraperitoneal administration. The therapeutic efficacy of 177Lu-labelled MG1 (74 MBq per rat), administered on the day of surgery (D0, n = 13) or 5 days later (D5, n = 13), was compared with that of carrier only (n = 13). The primary endpoint was perianastomotic tumour growth 28 days after surgery.

Results

111In-labelled MG1 preferentially accumulated in perianastomotic CC531 tumours. RIT resulted in a transient reduction in bodyweight in both treatment groups compared with controls, but there were no other signs of clinical discomfort. No macroscopic or microscopic perianastomotic tumour growth was found in eight of 11 animals in the D0 group and 11 of 13 in the D5 group, whereas 11 of 13 controls had macroscopic tumour (P = 0·011 and P = 0·001 respectively).

Conclusion

This study suggests that RIT may be an effective adjuvant treatment for preventing local recurrence after resection of colonic cancer.
Donor kidney disease and transplant outcome for kidneys donated after cardiac death
Authors: Wells A C , Rushworth L , Thiru S , Sharples L , Watson C J E , Bradley J A , Pettigrew G J
Published: February 2009

Background

Although outcomes of kidney transplants following donation after cardiac death (DCD) and donation after brainstem death (DBD) are similar, generally only optimal younger DCD donors are considered. This study examined the impact of pre-existing donor kidney disease on the outcome of DCD transplants.

Methods

This retrospective study compared the outcome of all DCD kidney transplants performed during 1996–2006 with contemporaneous kidney transplants from DBD donors. Implantation biopsies were scored for glomerular, tubular, parenchymal and vascular disease (global histology score). There were 104 DCD and 104 DBD kidney transplants.

Results

Delayed graft function (DGF) occurred more frequently in DCD than DBD kidneys (64·4 versus 28·8 per cent; P < 0·001). Long-term graft outcome was similar. The only donor factor that influenced outcome was baseline kidney disease, which was similar in both groups, even though DCD donors were younger, with a higher predonation estimated glomerular filtration rate. The global histology score predicted DGF (odds ratio 1·85 per unit; P = 0·006) and graft failure (relative risk 1·55 per unit; P = 0·001), although there was no difference for DCD and DBD kidneys.

Conclusion

Transplant outcomes for DCD and DBD kidneys are comparable. Baseline donor kidney disease influences DGF and graft survival but the impact is no greater for DCD kidneys.
Clinical, physiological and radiological assessment of rectovaginal septum reinforcement with mesh for complex rectocele (Br J Surg2008; 95: 1264–72)
Authors: Zbar A P , Ansari A
Published: February 2009

The Editors welcome topical correspondence from readers relating to articles published in the Journal. Responses should be sent electronically via the BJS website (www.bjs.co.uk). All letters will be reviewed and, if approved, appear on the website. A selection of these will be edited and published in the Journal. Letters must be no more than 250 words in length.
A Windows‐based interface for teaching image processing
Authors: Ayala Melvin , Adjouadi Malek , Cabrerizo Mercedes , Barreto Armando
Published: February 2009

The use of image processing in research represents a challenge to the scientific community interested in its various applications but is not familiar with this area of expertise. In academia as well as in industry, fundamental concepts such as image transformations, filtering, noise removal, morphology, convolution/deconvolution among others require extra efforts to be understood. Additionally, algorithms for image reading and visualization in computers are not always easy to develop by inexperienced researchers. This type of environment has lead to an adverse situation where most students and researchers develop their own image processing code for operations which are already standards in image processing, a redundant process which only exacerbates the situation. The research proposed in this article, with the aim to resolve this dilemma, is to propose a user‐friendly computer interface that has a dual objective which is to free students and researchers from the learning time needed for understanding/applying diverse imaging techniques but to also provide them with the option to enhance or reprogram such algorithms with direct access to the software code. The interface was thus developed with the intention to assist in understanding and performing common image processing operations through simple commands that can be performed mostly by mouse clicks. The visualization of pseudo code after each command execution makes the interface attractive, while saving time and facilitating to users the learning of such practical concepts. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 213–224, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20171
Dynamics simulation toolbox for industrial robot manipulators
Authors: Toz Metin , Kucuk Serdar
Published: February 2009

A new robot toolbox for dynamics simulation based on MATLAB Graphical User Interface (GUI) is developed for educational purposes. It is built on the previous version named as ROBOLAB performing only the kinematics analysis of robot manipulators. The toolbox presented in this paper provides interactive real‐time simulation and visualization of the industrial robot manipulator's dynamics based on Langrange–Euler and Newton–Euler formulations. Since most of the industrial robot manipulators are produced with six degrees of freedom (DOF) such as the PUMA 560, the Fanuc ArcMate 120iB and Stanford Arm, the library of the toolbox includes sixteen fundamental 6‐DOF robot manipulators with Euler wrist. The software can be used to interactively perform robotics analysis and off‐line programming of robot dynamics such as forward and inverse dynamics as well as to interactively teach and simulate the basic principles of robot dynamics in a very realistic way. In order to demonstrate the user‐friendly features of the toolbox much better, simulation of the NS robot manipulator (Stanford Arm) is provided as an example. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 319–330, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20262
Visual clustering of multidimensional educational data from an intelligent tutoring system
Authors: Dogan Buket , Camurcu A. Yilmaz
Published: February 2009

Data mining can be used in the educational field to make teaching more effective, to provide help for the student and teacher, and to analyze data. Data mining can be useful with educational software like intelligent tutoring systems which contain large quantities of data about students and their degree of success, scores, and errors. By analyzing these data, it is possible to obtain pedagogically reliable information as feedback for the teacher. The objectives of this study are to cluster the data available from an Intelligent Tutoring System (ITS) and to visualize the multidimensional data analysis results. In this study, the ITS data, which contain exam results on six different concepts, are clustered usingk‐means and fuzzyc‐means algorithms, and the clustering performance of the two algorithms is compared. Cluster analysis results are visualized using a parallel coordinate system. Clustering and visualizing of the concept‐level scores is used to provide meaningful and nontrivial insights into the workings of a course. Such information is useful for the teacher to discover which concepts give students difficulty and which do not. The paper also describes the data mining software developed in this study and the analytical results obtained. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 375–382, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20272
Integration of computations and experiments for flow control research with undergraduate students
Authors: Aradag Selin , Cohen Kelly , Seaver Christopher A. , McLaughlin Thomas
Published: February 2009

The methods and outcome of a senior undergraduate project related to the control of a turbulent cylinder wake flow using plasma actuators are summarized in this article. The study integrates computational fluid dynamics (CFD) with experimentation and combines fluid mechanics with flow control research, crossing the boundaries between engineering disciplines. Comput. Appl. Eng. Educ. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 727–735, 2010; View this article online at wileyonlinelibrary.com; DOI 10.1002/cae.20278
Investigating static and dynamic characteristics of electromechanical actuators (EMA) with MATLAB GUIs
Authors: Sefkat Gursel
Published: February 2009

This paper deals with the design of an electromechanical device considering some prescribed performance requirements, and static and dynamic analysis of this device are carried out. In studying the transient response of such a system, as part of dynamic analysis, two methods mostly used finite element method (FEM) and finite differences method (FDM). However, these methods need much CPU time. In this work, a computer simulator program is developed for an EMA. This technique is implemented in the MATLAB‐Simulink environment and tested for different design tasks such as electromagnetic valves or electromechanical brakes etc. Furthermore, by using GUIDE tools within MATLAB, a simple useful and user‐friendly GUI structure is developed to provide a visual approach to design and analysis process. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 383–396, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20279
A data logger for teaching data capturing and analysis to engineering students
Authors: Ibrahim Dogan
Published: February 2009

Data logging is the process of collecting and storing data from an experiment. Traditionally, data from science experiments was collected manually by hand and graphs were produced using pen and paper. By the introduction of cheap and powerful microcontrollers, all data logging operations are currently carried out using microcontroller‐based data logging devices. This article describes the design of an educational microcontroller‐based data logger device, which can be used to collect and save data for both offline and online analysis. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 397–405, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20281
Effects of caffeine and theophylline on coronary hyperemia induced by adenosine or dipyridamole
Authors: Salcedo Jonathan , Kern Morton J.
Published: February 2009

Objectives: The aims of this review are to examine the biochemical features of theophylline, caffeine, adenosine, and dipyridamole, their effects on coronary hyperemia, and to make recommendations on performing hyperemic lesion assessment after taking caffeine or theophylline. Background: It is commonly thought that caffeine and theophylline interfere with adenosine and dipyridamole induced coronary hyperemia, thus frequently delaying scheduled assessments after inadvertent consumption. However, a limited amount of studies address the interactions of these substances thus leaving no clear consensus on when to delay coronary assessment after their intake. Methods: For biochemical information on each substance, online and textbook references were utilized. For studies on the interactions of the substances with coronary hyperemia, broad search terms such as “caffeine AND adenosine” were applied in the major research data bases. Results: A serum caffeine level of 3 to 4 mg/L at the time of an adenosine‐hyperemia study does not affect the ability of perfusion stress imaging to detect coronary artery disease. The interactions of theophylline with adenosine‐hyperemia are less clear while both caffeine and theophylline show significant interaction with dipyridamole‐hyperemia. Conclusions: For dipyridamole‐stress myocardial perfusion studies, caffeine products and theophylline medications should be discontinued for 24 hr. For adenosine‐stress myocardial perfusion studies, theophylline medications should be discontinued for 12 hr; however, one cup of coffee may be taken up to 1 hr before the test without necessitating a delay or cancellation of the study. These same considerations hold true for patients undergoing cardiac catheterization and intravenous adenosine‐induced hyperemia. © 2009 Wiley‐Liss, Inc.
A novel stenting technique for coronary artery bifurcation stenosis
Authors: Y‐Hassan Shams , Lindroos Magnus C. , Sylvén Christer
Published: February 2009

A novel stenting technique, using one stent strategy, designed to treat type Medina 1,0,0 coronary bifurcation lesions, is described. The atherosclerotic plaque burden in this category of bifurcation lesions is located in the proximal segment of the main branch (MB) of a coronary bifurcation in which the side branch has a sharp angulation (T‐ or reverse‐shaped) relative to the MB. The advantages of this technique are the accurate placement of the stent tailored to cover solely the bifurcation lesion, shoving the plaque burden away from the side branch ostium during stent expansion and the ability to maintain guide wire access in the branch at highest risk of occlusion obviating the need for more cumbersome and time consuming percutaneous coronary intervention procedure. © 2009 Wiley‐Liss, Inc.
Percutaneous closure of patent foramen ovale with a bioabsorbable occluder device
Authors: Ussia Gian Paolo , Cammalleri Valeria , Mulè Massimiliano , Scarabelli Marilena , Barbanti Marco , Scardaci Francesco , Mangiafico Sarah , Immè Sebastiano , Capodanno Davide , Tamburino Corrado
Published: February 2009

Background:

Percutaneous closure of patent foramen ovale (PFO) is routinely performed with nonbiological devices, characterized by a persistent low‐grade inflammatory response. We report our experience about PFO closure with a bioabsorbable device, BioSTAR® (NMT Inc, USA).

Methods:

From September 2007 to September 2008, 14 patients with migraine (eight with aura) and cerebral magnetic resonance positive for silent ischemia and nine patients with prior cardiovascular accident (CVA) underwent closure of PFO using BioSTAR®. One patient had heterozygosis for sickle‐cell‐anaemia. Nickel allergy was present in eight patients. Echocardiogram was performed at 24 hr, one and 6 months. At 6 and 12 months a contrast‐transcranial‐doppler (c‐TCD) and a trans‐oesophageal echocardiogram (TOE) were scheduled, respectively.

Results:

BioSTAR® was successfully implanted in 22 patients (96%). The mean procedural time and the mean fluoroscopy time were 22 ± 6 and 4 ± 2 minutes, respectively. The mean in‐hospital stay was 3 ± 0.5 days. After a mean follow‐up of 7.8 ± 3.5 months there was an hemorrhagic stroke related to double antiaggregation. No other CVA or allergic reactions were registered. There were two cases of atrial arrhythmia. Fifteen patients had not residual shunts at c‐TCD, while in four patients we observed a trivial microbubbles passage. The TOE, achieved in nine patients without contrast, showed the device well positioned, with a low profile and without thrombus.

Conclusions:

In our experience PFO closure with BioSTAR® is safe and efficacious in preventing recurrent CVA. Its use could be advantageous in patients with nickel allergy and haematological disorders. The potential benefits of this device need to be certified in a larger cohort of patients with a longer follow‐up. © 2009 Wiley‐Liss, Inc.
Magnetic wire lock: Prevention and correction to avoid wire fracture
Authors: Hilst Kwame van der , Patterson Mark S.
Published: February 2009

This report illustrates an undescribed mechanism causing magnetic angioplasty wire fracture and describes how to avoid its occurrence and how to correct it, if it occurs. The cause is the transition point in the wire between a flexible wire shaft and the inflexible magnetic tip of a magnetically enabled wire. In the first stage of the problem, the wire becomes trapped in a doubled‐back position. Subsequently, traction causes the second stage that kinks the wire and hooks behind a structure, in this case, a stent, causing magnetic wire lock. Further traction has a high chance of wire fracture. Correction, although challenging, remains possible before wire fracture occurs. Although there is no intrinsic problem with the technology, attention to this problem by the operator will reduce its occurrence and therefore its sequelae. © 2009 Wiley‐Liss, Inc.
Survival analysis based on the proportional hazards model and survey data
Authors: Boudreau Christian , Lawless Jerald F.
Published: February 2009

The authors propose methods based on the stratified Cox proportional hazards model that account for the fact that the data have been collected according to a complex survey design. The methods they propose are based on the theory of estimating equations in conjunction with empirical process theory. The authors also discuss issues concerning ignorable sampling design, and the use of weighted and unweighted procedures. They illustrate their methodology by an analysis of jobless spells in Statistics Canada's Survey of Labour and Income Dynamics. They discuss briefly problems concerning weighting, model checking, and missing or mismeasured data. They also identify areas for further research.
A class of sequential tests for two‐sample composite hypotheses
Authors: Gombay Edit , Hussein Abdulkadir
Published: February 2009

The authors propose a class of statistics based on Rao's score for the sequential testing of composite hypotheses comparing two treatments (populations). Asymptotic approximations of the statistics lead them to propose sequential tests and to derive their monitoring boundaries. As special cases, they construct sequential versions of the two‐sample t‐test for normal populations and two‐sample z‐score tests for binomial populations. The proposed algorithms are simple and easy to compute, as no numerical integration is required. Furthermore, the user can analyze the data at any time regardless of how many inspections have been made. Monte Carlo simulations allow the authors to compare the power and the average stopping time (also known as average sample number) of the proposed tests to those of nonsequential and group sequential tests. A two‐armed comparative clinical trial in patients with adult leukemia allows them to illustrate the efficiency of their methods in the case of binary responses.
Estimation of regression parameters in missing data problems
Authors: Mcleish Donald L. , Struthers Cyntha A.
Published: February 2009

LetYbe a response variable, possibly multivariate, with a density functionf(y|x,v; β) conditional on vectorsxandvof covariates and a vector β of unknown parameters. The authors consider the problem of estimatingβwhen the values taken by the covariate vectorvare available for all observations while some of those taken by the covariatexare missing at random. They compare the profile estimator to several alternatives, both in terms of bias and standard deviation, when the response and covariates are discrete or continuous.
Robust inference in generalized linear models for longitudinal data
Authors: Sinha Sanjoy K.
Published: February 2009

The author develops a robust quasi‐likelihood method, which appears to be useful for down‐weighting any influential data points when estimating the model parameters. He illustrates the computational issues of the method in an example. He uses simulations to study the behaviour of the robust estimates when data are contaminated with outliers, and he compares these estimates to those obtained by the ordinary quasi‐likelihood method.
Approximating bayesian inference by weighted likelihood
Authors: Wang Xiaogang
Published: February 2009

The author proposes to use weighted likelihood to approximate Bayesian inference when no external or prior information is available. He proposes a weighted likelihood estimator that minimizes the empirical Bayes risk under relative entropy loss. He discusses connections among the weighted likelihood, empirical Bayes and James‐Stein estimators. Both simulated and real data sets are used for illustration purposes.
A bayesian signal detection procedure for scale‐space random fields
Authors: Rohani M. Farid , Shafie Khalil , Noorbaloochi Siamak
Published: February 2009

The authors consider the problem of searching for activation in brain images obtained from functional magnetic resonance imaging and the corresponding functional signal detection problem. They develop a Bayesian procedure to detect signals existing within noisy images when the image is modeled as a scale space random field. Their procedure is based on the Radon‐Nikodym derivative, which is used as the Bayes factor for assessing the point null hypothesis of no signal. They apply their method to data from the Montreal Neurological Institute.
Correlation analysis of ordered symmetrically dependent observations and their concomitants of order statistics
Authors: Viana Marios A. G. , Lee Hak‐Myung
Published: February 2009

Given two jointly observed random vectors Y and Z of the same dimension, let Y be a reordered version of Y and Z the resulting vector of concomitants of order statistics. When X is a covariate of interest, also jointly observed with Y, the authors obtain the joint covariance structure of (X, y, Z) and the related correlation parameters explicitly, under the assumption that the vector (X, Y, Z) is normal and that its joint covariance structure is permutation symmetric. They also discuss extensions to elliptically contoured distributions.
Pseudo‐likelihood estimation in ARCH models
Authors: Mukherjee Kanchan
Published: February 2009

The author presents asymptotic results for the class of pseudo‐likelihood estimators in the autoregressive conditional heteroscedastic models introduced by Engle (1982). Unlike what is required for the quasi‐likelihood estimator, some estimators in the class he considers do not require the finiteness of the fourth moment of the error density. Thus his method is applicable to heavy‐tailed error distributions for which moments higher than two may not exist.
Pseudo‐empirical likelihood ratio confidence intervals for complex surveys
Authors: Wu Changbao , Rao J. N. K.
Published: February 2009

The authors show how an adjusted pseudo‐empirical likelihood ratio statistic that is asymptotically distributed as a chi‐square random variable can be used to construct confidence intervals for a finite population mean or a finite population distribution function from complex survey samples. They consider both non‐stratified and stratified sampling designs, with or without auxiliary information. They examine the behaviour of estimates of the mean and the distribution function at specific points using simulations calling on the Rao‐Sampford method of unequal probability sampling without replacement. They conclude that the pseudo‐empirical likelihood ratio confidence intervals are superior to those based on the normal approximation, whether in terms of coverage probability, tail error rates or average length of the intervals.
Conservative prior distributions for variance parameters in hierarchical models
Authors: Gustafson Paul , Hossain Shahadut , Macnab Ying C.
Published: February 2009

Bayesian hierarchical models typically involve specifying prior distributions for one or more variance components. This is rather removed from the observed data, so specification based on expert knowledge can be difficult. While there are suggestions for “default” priors in the literature, often a conditionally conjugate inverse‐gamma specification is used, despite documented drawbacks of this choice. The authors suggest “conservative” prior distributions for variance components, which deliberately give more weight to smaller values. These are appropriate for investigators who are skeptical about the presence of variability in the second‐stage parameters (random effects) and want to particularly guard against inferring more structure than is really present. The suggested priors readily adapt to various hierarchical modelling settings, such as fitting smooth curves, modelling spatial variation and combining data from multiple sites.
On describing multivariate skewed distributions: A directional approach
Authors: Ferreira José T. A. S. , Steel Mark F. J.
Published: February 2009

Most multivariate measures of skewness in the literature measure the overall skewness of a distribution. These measures were designed for testing the hypothesis of distributional symmetry; their relevance for describing skewed distributions is less obvious. In this article, the authors consider the problem of characterizing the skewness of multivariate distributions. They define directional skewness as the skewness along a direction and analyze two parametric classes of skewed distributions using measures based on directional skewness. The analysis brings further insight into the classes, allowing for a more informed selection of classes of distributions for particular applications. The authors use the concept of directional skewness twice in the context of Bayesian linear regression under skewed error: first in the elicitation of a prior on the parameters of the error distribution, and then in the analysis of the skewness of the posterior distribution of the regression residuals.
Strong orthogonal decompositions and non‐linear impulse response functions for infinite‐variance processes
Authors: Hill Jonathan B.
Published: February 2009

The author proves that Wold‐type decompositions with strong orthogonal prediction innovations exist in smooth, reflexive Banach spaces of discrete time processes if and only if the projection operator generating the innovations satisfies the property of iterations. His theory includes as special cases all previous Wold‐type decompositions of discrete time processes, completely characterizes when non‐linear heavy‐tailed processes obtain a strong‐orthogonal moving average representation, and easily promotes a theory of non‐linear impulse response functions for infinite‐variance processes. The author exemplifies his theory by developing a non‐linear impulse response function for smooth transition threshold processes, and discusses how to test decomposition innovations for strong orthogonality and whether the proposed model represents the best predictor. A data set on currency exchange rates allows him to illustrate his methodology.
A unified view on skewed distributions arising from selections
Authors: Arellano‐Valle Reinaldo B. , Branco Máaarcia D. , Genton Marc G.
Published: February 2009

Parametric families of multivariate nonnormal distributions have received considerable attention in the past few decades. The authors propose a new definition of a selection distribution that encompasses many existing families of multivariate skewed distributions. Their work is motivated by examples that involve various forms of selection mechanisms and lead to skewed distributions. They give the main properties of selection distributions and show how various families of multivariate skewed distributions, such as the skew‐normal and skew‐elliptical distributions, arise as special cases. The authors further introduce several methods of constructing selection distributions based on linear and nonlinear selection mechanisms.
Some robust designs for polynomial regression models
Authors: Fang Zhide
Published: February 2009

The author identifies static optimal designs for polynomial regression models with or without intercept. His optimality criterion is an average between the D‐optimality criterion for the estimation of low‐degree terms and the D8‐optimality criterion for testing the significance of higher degree terms. His work relies on classical results concerning canonical moments and the theory of continued fractions.
Multiple imputation methods for recurrent event data with missing event category
Authors: Schaubel Douglas E. , Cai Jianwen
Published: February 2009

Frequently in clinical and epidemiologic studies, the event of interest is recurrent (i.e., can occur more than once per subject). When the events are not of the same type, an analysis which accounts for the fact that events fall into different categories will often be more informative. Often, however, although event times may always be known, information through which events are categorized may potentially be missing. Complete‐case methods (whose application may require, for example, that events be censored when their category cannot be determined) are valid only when event categories are missing completely at random. This assumption is rather restrictive. The authors propose two multiple imputation methods for analyzing multiple‐category recurrent event data under the proportional means/rates model. The use of a proper or improper imputation technique distinguishes the two approaches. Both methods lead to consistent estimation of regression parameters even when the missingness of event categories depends on covariates. The authors derive the asymptotic properties of the estimators and examine their behaviour in finite samples through simulation. They illustrate their approach using data from an international study on dialysis.
Classification with reject option
Authors: Herbei Radu , Wegkamp Marten H.
Published: February 2009

The authors study binary classification that allows for a reject option in which case no decision is made. This reject option is to be used for those observations for which the conditional class probabilities are close and as such are hard to classify. The authors generalize existing theory for both plug‐in rules and empirical risk minimizers to this setting.
On consistent testing for serial correlation in seasonal time series models
Authors: Duchesne Pierre
Published: February 2009

The author considers serial correlation testing in seasonal time series models. He proposes a test statistic based on a spectral approach. Many tests of this type rely on kernel‐based spectral density estimators that assign larger weights to low order lags than to high ones. Under seasonality, however, large autocorrelations may occur at seasonal lags that classical kernel estimators cannot take into account. The author thus proposes a test statistic that relies on the spectral density estimator of Shin (2004), whose weighting scheme is more adapted to this context. The distribution of his test statistic is derived under the null hypothesis and he studies its behaviour under fixed and local alternatives. He establishes the consistency of the test under a general fixed alternative. He also makes recommendations for the choice of the smoothing parameters. His simulation results suggest that his test is more powerful against seasonality than alternative procedures based on classical weighting schemes. He illustrates his procedure with monthly statistics on employment among young Americans.
On the multivariate spatial median for clustered data
Authors: Nevalainen Jaakko , Larocque Denis , Oja Hannu
Published: February 2009

The authors consider the multivariate one‐sample location problem with clustered data from a nonparametric viewpoint. They propose the spatial median and its affine equivariant version as companion estimators to the affine invariant sign test of Larocque (2003). They extend the asymptotics of the proposed estimators to cluster dependent data and explore the limiting as well as finite‐sample efficiencies for multivariate Student distributions. They demonstrate that the efficiency of the spatial median suffers less from intracluster correlation than the mean vector. They use data on the well‐being of pupils in Finnish schools to illustrate their work.
A unified approach to estimation of nonlinear mixed effects and Berkson measurement error models
Authors: Wang Liqun
Published: February 2009

Mixed effects models and Berkson measurement error models are widely used. They share features which the author uses to develop a unified estimation framework. He deals with models in which the random effects (or measurement errors) have a general parametric distribution, whereas the random regression coefficients (or unobserved predictor variables) and error terms have nonparametric distributions. He proposes a second‐order least squares estimator and a simulation‐based estimator based on the first two moments of the conditional response variable given the observed covariates. He shows that both estimators are consistent and asymptotically normally distributed under fairly general conditions. The author also reports Monte Carlo simulation studies showing that the proposed estimators perform satisfactorily for relatively small sample sizes. Compared to the likelihood approach, the proposed methods are computationally feasible and do not rely on the normality assumption for random effects or other variables in the model.
Objective Bayesian analysis of spatial data with measurement error
Authors: De Oliveira Victor
Published: February 2009

The author shows how geostatistical data that contain measurement errors can be analyzed objectively by a Bayesian approach using Gaussian random fields. He proposes a reference prior and two versions of Jeffreys' prior for the model parameters. He studies the propriety and the existence of moments for the resulting posteriors. He also establishes the existence of the mean and variance of the predictive distributions based on these default priors. His reference prior derives from a representation of the integrated likelihood that is particularly convenient for computation and analysis. He further shows that these default priors are not very sensitive to some aspects of the design and model, and that they have good frequentist properties. Finally, he uses a data set of carbon/nitrogen ratios from an agricultural field to illustrate his approach.
Objective priors for hypothesis testing in one‐way random effects models
Authors: García‐Donato Gonzalo , Sun Dongchu
Published: February 2009

The Bayes factor is a key tool in hypothesis testing. Nevertheless, the important issue of which priors should be used to develop objective Bayes factors remains open. The authors consider this problem in the context of the one‐way random effects model. They use concepts such as orthogonality, predictive matching and invariance to justify a specific form of the priors for common parameters and derive the intrinsic and divergence based prior for the new parameter. The authors show that both intrinsic priors or divergence‐based priors produce consistent Bayes factors. They illustrate the methods and compare them with other proposals.
Asymptotic properties of likelihood ratio test statistics in affected‐sib‐pair analysis
Authors: Feng Zeny Z. , Chen Jiahua , Thompson Mary E.
Published: February 2009

In an affected‐sib‐pair genetic linkage analysis, identical by descent data for affected sib pairs are routinely collected at a large number of markers along chromosomes. Under very general genetic assumptions, the IBD distribution at each marker satisfies the possible triangle constraint. Statistical analysis of IBD data should thus utilize this information to improve efficiency. At the same time, this constraint renders the usual regularity conditions for likelihood‐based statistical methods unsatisfied. In this paper, the authors study the asymptotic properties of the likelihood ratio test (LRT) under the possible triangle constraint. They derive the limiting distribution of the LRT statistic based on data from a single locus. They investigate the precision of the asymptotic distribution and the power of the test by simulation. They also study the test based on the supremum of the LRT statistics over the markers distributed throughout a chromosome. Instead of deriving a limiting distribution for this test, they use a mixture of chi‐squared distributions to approximate its true distribution. Their simulation results show that this approach has desirable simplicity and satisfactory precision.
Optimal designs for calibration of orientations
Authors: Shin Hwashin H. , Takahara Glen , Murdoch Duncan J.
Published: February 2009

This paper concerns designed experiments involving observations of orientations following the models of Prentice (1989) and Rivest &Chang (2006). The authors state minimal conditions on the designs for consistent least squares estimation of the matrix parameters in these models. The conditions are expressed in terms of the axes and rotation angles of the design orientations. The authors show that designs satisfyingU1+ … +Un= 0 are optimal in the sense of minimizing the estimation error average angular distance. The authors give constructions of optimaln‐point designs whenn≥ 4 and they compare the performance of several designs through approximations and simulation.
A new estimation procedure for a partially nonlinear model via a mixed‐effects approach
Authors: Li Runze , Nie Lei
Published: February 2009

The authors consider the estimation of the parametric component of a partially nonlinear semiparametric regression model whose nonparametric component is viewed as a nuisance parameter. They show how estimation can proceed through a nonlinear mixed‐effects model approach. They prove that under certain regularity conditions, the proposed estimate is consistent and asymptotically Gaussian. They investigate its finite‐sample properties through simulations and illustrate its use with data on the relation between the photosynthetically active radiation and the net ecosystem‐atmosphere exchange of carbon dioxide.
Testing noninferiority in three‐armed clinical trials based on likelihood ratio statistics
Authors: Munk Axel , Mielke Matthias , Freitag Gudrun , Skipka Guido
Published: February 2009

Clinical noninferiority trials with at least three groups have received much attention recently, perhaps due to the fact that regulatory agencies often require that a placebo group be evaluated along with a new experimental drug and an active control. The authors discuss likelihood ratio tests for binary endpoints and various noninferiority hypotheses. They find that, depending on the particular hypothesis, the test reduces asymptotically either to the intersection‐union test or to a test which follows asymptotically a mixture of generalized chi‐squared distributions. They investigate the performance of this asymptotic test and provide an exact modification. They show that this test considerably outperforms multiple testing methods such as the Bonferroni adjustment with respect to power. They illustrate their methods with a cancer study to compare antiemetic agents. Finally, they discuss the extension of the results to other settings, such as Gaussian endpoints.
Theoretical properties of tests for spatial clustering of count data
Authors: Jung Inkyung , Kulldorff Martin
Published: February 2009

Testing for spatial clustering of count data is an important problem in spatial data analysis. Several procedures have been proposed to this end but despite their extensive use, studies of their fundamental theoretical properties are almost non‐existent. The authors suggest two conditions that any reasonable test for spatial clustering should satisfy. The latter are based on the notion that the null hypothesis should be rejected almost surely as the amount of spatial clustering tends to infinity. The authors show that the chisquared test and the Potthoff—Whittinghill V have both properties but that other classical tests do not.
Nonresponse weighting adjustment using estimated response probability
Authors: Kim Jae Kwang , Kim Jay J.
Published: February 2009

To reduce nonresponse bias in sample surveys, a method of nonresponse weighting adjustment is often used which consists of multiplying the sampling weight of the respondent by the inverse of the estimated response probability. The authors examine the asymptotic properties of this estimator. They prove that it is generally more efficient than an estimator which uses the true response probability, provided that the parameters which govern this probability are estimated by maximum likelihood. The authors discuss variance estimation methods that account for the effect of using the estimated response probability; they compare their performances in a small simulation study. They also discuss extensions to the regression estimator.
A family of power‐divergence diagnostics for goodness‐of‐fit
Authors: Carota Cinzia
Published: February 2009

The author extends to the Bayesian nonparametric context the multinomial goodness‐of‐fit tests due to Cressie & Read (1984). Her approach is suitable when the model of interest is a discrete distribution. She provides an explicit form for the tests, which are based on power‐divergence measures between a prior Dirichlet process that is highly concentrated around the model of interest and the corresponding posterior Dirichlet process. In addition to providing interesting special cases and useful approximations, she discusses calibration and the choice of test through examples.
Empirical likelihood‐based inference for genetic mixture models
Authors: Huang Chiung‐Yu , Qin Jing , Zou Fei
Published: February 2009

The authors show how the genetic effect of a quantitative trait locus can be estimated by a nonparametric empirical likelihood method when the phenotype distributions are completely unspecified. They use an empirical likelihood ratio statistic for testing the genetic effect and obtaining confidence intervals. In addition to studying the asymptotic properties of these procedures, the authors present simulation results and illustrate their approach with a study on breast cancer resistance genes.
Distribution‐free statistical intervals via ranked‐set sampling
Authors: Frey Jesse
Published: February 2009

The author shows how to construct distribution‐free statistical intervals from ranked‐set sampling. He considers the cases of confidence, tolerance, and prediction intervals. He shows how to compute their coverage probabilities and he compares their performance to that of intervals based on simple random sampling. He finds that the ranked‐set sampling‐based intervals are at least as good as their classical counterpart in most settings of interest, although the nature of the advantage depends on the type of interval considered.
A multivariate von mises distribution with applications to bioinformatics
Authors: Mardia Kanti V. , Hughes Gareth , Taylor Charles C. , Singh Harshinder
Published: February 2009

Motivated by problems of modelling torsional angles in molecules, Singh, Hnizdo & Demchuk (2002) proposed a bivariate circular model which is a natural torus analogue of the bivariate normal distribution and a natural extension of the univariate von Mises distribution to the bivariate case. The authors present here a multivariate extension of the bivariate model of Singh, Hnizdo & Demchuk (2002). They study the conditional distributions and investigate the shapes of marginal distributions for a special case. The methods of moments and pseudo‐likelihood are considered for the estimation of parameters of the new distribution. The authors investigate the efficiency of the pseudo‐likelihood approach in three dimensions. They illustrate their methods with protein data of conformational angles