bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Vitamin D Pretreatment of Human Mesenchymal Stem Cells on Ectopic Bone Formation
Authors: De Kok I. J. , Hicok K. C. , Padilla R. J. , Young R. G. , Cooper L. F. 
Published: June 2006

Abstract
Adult mesenchymal stem cells (MSCs) are used in contemporary strategies for tissue engineering. The MSC is able to form bone following implantation as undifferentiated cells adherent to hydroxyapatite (HA)/tricalcium phosphate (TCP) scaffolds. Previous investigators have demonstrated that human MSCs (hMSCs) can be differentiated to osteoblasts in vitro by the inclusion of vitamin D and ascorbic acid. The aim of this study was to compare the osteogenic potential of predifferentiated and undifferentiated bone marrow–derived, culture-expanded hMSCs adherent to synthetic HA/TCP (60%/40%) following subcutaneous engraftment in severe combined immunodeficiency (SCID) mice. During the final 3 days of culture, cells were grown in Dulbecco's modified Eagle's medium containing 10% fetal calf serum and antibiotics or media containing 25-mM calcium supplementation with vitamin D and ascorbic acid. Four weeks following implantation in SCID mice, scoring analysis of bone formation within the cubes revealed the absence of bone formation in unloaded cubes. Bone formation compared by a qualitative bone index was 7.23% for undifferentiated cells compared to 5.20% for differentiated cells. Minimal resorption was observed at this early time point. In this ectopic model, predifferentiation using a combination of vitamin D and ascorbic acid failed to increase subsequent bone formation by implanted cells. Following implantation of hMSCs adherent to an osteoconductive scaffold, host factors may contribute dominant osteoinductive signals or impose inhibitory signals to control the fate of the implanted cell. Predifferentiation strategies require confirmation in vivo.
Maxillary Sinus Augmentation Using an Engineered Porous Hydroxyapatite: A Clinical, Histological, and Transmission Electron Microscopy Study in Man
Authors: Mangano Carlo , Scarano Antonio , Iezzi Giovanna , Orsini Giovanna , Perrotti Vittoria , Mangano Francesco , Montini Sergio , Piccirilli Marcello , Piattelli Adriano 
Published: June 2006

AbstractPorous hydroxyapatite (HA) is a calcium-phosphate–based material that is biocompatible, nonimmunological, and osteoconductive, and has a macroporosity of about 200 to 800 μm. The pores seem to be able to induce migration, adhesion, and proliferation of osteoblasts inside the pore network and to promote angiogenesis inside the pore system. The aim of this study was to evaluate the clinical behavior and the histological and ultrastructural aspects of porous HA in maxillary sinus augmentation procedures. Twenty-four patients (19 men, 5 women; average age 53.4 years) in good general physical and mental health and with partially or completely edentulous maxillae were selected for this study. Six months after sinus floor elevation, at the time of dental implant placement, biopsies were carried out under local anesthesia. These bone cores were cut in half and were processed for light and transmission electron microscopy. After a mean 3 years after implantation, all implants are clinically in function and no surgical or prosthetic complications have occurred. Under light microscopy, newly formed bone was 38.5% ± 4.5%, whereas the residual biomaterial represented 12% ± 2.3% and the marrow spaces represented 44.6% ± 4.2%. In addition, in the majority of cases, the biomaterial particles were in close contact with the bone, which appeared compact with the characteristic features of well-organized lamellar bone. A cement-like line was slightly visible at the bone-biomaterial interface, but there were no gaps or interposed connective tissue in between. A high quantity (about 40%) of newly formed bone was present. Bone was closely apposed to the biomaterials particles as shown in light microscopy and transmission electron microscopy. Moreover, no signs of inflammatory cell infiltrate or foreign body reaction were present. Also, most of the biomaterial was resorbed and only a small quantity (a little more than 10%) was still present. The results of our study show that porous HA can be a suitable synthetic material for bone regeneration in maxillary sinus augmentation procedures.
Nonparametric standard errors and confidence intervals
Authors: Efron Bradley 
Published: June 2006

AbstractWe investigate several nonparametric methods; the bootstrap, the jackknife, the delta method, and other related techniques. The first and simplest goal is the assignment of nonparametric standard errors to a real‐valued statistic. More ambitiously, we consider setting nonparametric confidence intervals for a real‐valued parameter. Building on the well understood case of confidence intervals for the median, some hopeful evidence is presented that such a theory may be possible.
Interval estimates for variance components
Authors: Wild C. J. 
Published: June 2006

AbstractThe fiducial approach to the two components of variance random effects model developed by Venables and James (1978) is related to the Bayesian approach of Box and Tiao (1973). The operating characteristics, under repeated sampling, of the resulting interval estimators for the “within classes” variance component are investigated, and the behaviour of the two sets of intervals is found to be very similar, the coverage frequency of 95% probability intervals being approximately 91% when the “between classes” variance component is zero but rising rapidly to 95% as the between component increases. The probability intervals are shown to be shorter on average than a comparable confidence interval based upon the within classes sum of squares, and to be robust against nonnormality in the class means.
The search for submarine pingos in the Beaufort Sea: An unusual application of the binomial distribution
Authors: Johnson B. R. 
Published: June 2006

AbstractAlmost all statistical estimation problems involving the binomial distribution occur with the number of independent Bernoulli trials, n, being a known parameter and the probability of success, p, being unknown. Applications in which n is unknown and p is known are extremely rare. One such application to a real problem in the physical sciences is the subject of this note.
Monte Carlo studies of some adaptive robust procedures for location
Authors: Forst Frederick R. , Ali Mir Masoom 
Published: June 2006

AbstractOne linear and two nonlinear adaptive robust procedures have been developed in which preliminary statistics, based on tail lengths, attempt to identify distributions from which the samples arise so that a suitable robust estimator based on trimmed means can be used to estimate the location parameter. The efficiencies of the estimators based on the three proposed adaptive robust procedures have been obtained using Monte Carlo methods involving eight distributions and these efficiencies are compared with the efficiencies of nineteen other robust estimators.
The multitype branching random walk, I
Authors: Gail Ivanoff B. 
Published: June 2006

AbstractThe limiting behaviour of the multitype branching random walk is studied. A limit theorem is proven for the supercritical process. Steady‐state distributions are shown to exist for the subcritical process with immigration, and for the critical transient process beginning with Poisson random fields. An analogue of the exponential limit law is proven for the critical process whose migration process is Brownian motion in two dimensions.
On the asymptotic null distribution of the F‐statistic for testing a partial null hypothesis in a randomized PBIB design with m associate classes under the Neyman model
Authors: Ogawa Junjiro , Ikeda Sadao 
Published: June 2006

AbstractIn the paper [11], the authors have shown that the familiar central F‐distribution can be considered as an asymptotically approximate distribution, in a heuristic sense, of the null distribution of the F‐statistic for testing a partial null hypothesis in a randomized PBIB design with m associate classes under the Neyman model. This result is the most general among those given in previous related papers [6, 7, 8, 9, 11]. The term “asymptotically approximate distribution” has been used, however, in a rather heuristic and unsophisticated way and the rigorous formulation of the notion of asymptotically approximate distribution has not yet been attempted. The purposes of the present article are to give a satisfactory formulation of the asymptotically approximate distribution based on Ikeda's theory of the asymptotic equivalence of probability distributions [2, 5] and to show that the familiar centrals F‐distribution is “an asymptotically approximate distribution”, in the sense just defined, of the F‐statistic for testing a partial null hypothesis in the analysis of a PBIB design with m associate classes, even under the Neyman model when it is randomized. The tedious calculations of the previous paper [11] are eliminated and the rather rigid uniformity conditions are weakened in the present article. The present work throws some light on the asymptotic nature of the power function of the F‐statistic under consideration; this will be presented in a forthcoming paper based on [4].
Evaluation of misclassification errors
Authors: Srivastava M. S. 
Published: June 2006

AbstractIn this paper the problem of classifying an individual into one of two multivariate normal populations with common covariance matrix is considered. An attempt is made to provide some idea about the errors of misclassification for the Welch‐Anderson statistic. It is shown that in most cases the usual asymptotic expression (the one when all the parameters are known) is an underestimate of the actual error committed. In Part II, an alternative classification procedure, known as a step‐down procedure, is proposed. In this the errors of misclassification are easily computable.
A simplified statistical estimation procedure for regional econometric models
Authors: Karasek Mirek 
Published: June 2006

AbstractThis paper is concerned with some computational aspects of Fisher's simultaneous‐equation estimator in its modified version [15] and with the alternative of using this computational scheme as the first stage of the two‐stage instrumental variables (2 SIV) estimator [1, p. 11]. The main disadvantage of the above estimation process arises out of the repeated investigation of a given set of instruments to determine how significantly some of their combinations contribute to R̄2. A short‐cut procedure that eliminates this computational inconvenience is suggested in this paper. The new method treats the problem within the framework of operations research, i.e., by isolating the optimum combination through the shortest way possible. The resulting step‐wise algorithm leads to the optimum combination of the given instrumental variables in, at most, n steps, where n is the number of instruments. The results of the application of this procedure to the estimation of the Ontario Econometric Model [9] are discussed, tested and compared with other methods of estimation.
A characterization of the pareto distribution
Authors: Ahsanullah M. , Kabir A. B. M. Lutful 
Published: June 2006

AbstractSuppose that in a random sample of size n from a population with probability density function f(x), the order statistics are X(1) <x(2) <…<x(n). It is proved that a necessary and sufficient condition for f (x) to be a Pareto density function is that the statistics X(r) and X(s)/X(r) ≤ r < s ≤ n) are independent.
Robust M‐estimators of multivariate location and scatter in the presence of asymmetry
Authors: Wiens D. P. , Zheng Z. 
Published: June 2006

AbstractRobust estimation of location vectors and scatter matrices is studied under the assumption that the unknown error distribution is spherically symmetric in a central region and completely unknown in the tail region. A precise formulation of the model is given, an analysis of the identifiable parameters in the model is presented, and consistent initial estimators of the identifiable parameters are constructed. Consistent and asymptotically normal M‐estimators are constructed (solved iteratively beginning with the initial estimates) based on “influence functions” which vanish outside specified compact sets. Finally M‐estimators which are asymptotically minimax (in the sense of Huber) are derived.
Some finite sample properties of generalized ridge regression estimators
Authors: Kadiyala Krishna 
Published: June 2006

AbstractIn this paper we study the mean square error properties of the generalized ridge estimator. We obtain the exact and the approximate bias and the mean square error of the operational generalized ridge estimator in terms of G( ) functions. We show, among other things, that the operational generalized ridge estimator does not dominate the ordinary least squares estimator up to a certain order of approximation. Finally, we note that the iterative procedures to obtain coverging ridge estimators should be used with caution.
On the poisson approximation to the multinomial distribution
Authors: McDonald David R. 
Published: June 2006

AbstractLet Xi be the number of outcomes in class Ci, i = 0,…,k, during n independent possibly non‐identical trials. If class C0 has high probability we show {Xi}ki=1 can be approximated by {Yi}ki=1 a sequence of independent Poisson random variables with ℰXi=ℰYi. A bound on the error is given. The result is an extension of Hodges and LeCam's (1960) Poisson‐binomial approximation. Applications to goodness of fit and to the sign test are given.
Case study in data analysis, no. 2
Authors: Gentleman Jane F. , Whitmore G. A. 
Published: June 2006

AbstractIn November 1979, the derailment of a train passing through Mississauga, Ontario, caused the explosion of tank cars containing liquid propane and the leakage of chlorine through a hole in another tank car, Officials evacuated more than 200,000 people from the area, but firemen stayed, exposing themselves to noxious fumes from the explosions and fires. When the crisis was over, health officials administered health tests and questionnaires to the affected men and to a control group of unaffected firefighters. Health information was gathered again one and two years later. In this study, two independent sets of analysts examine the health data to determine whether exposure to hazardous chemicals at the derailment site had any lasting effects on the lung function of the Mississauga firefighters.
Improved shrinkage estimators for the mean vector of a scale mixture of normals with unknown variance
Authors: Bravo Gina , Macgibbon Brenda 
Published: June 2006

AbstractThe problem of estimating the mean θ of a not necessarily normalp‐variate (p> 3) distribution with unknown covariance matrix of the form σ2A (Aa known diagonal matrix) on the basis ofni> 2 observations on each coordinateXt(1 <i < p) is considered. It is argued that the class of scale (or variance) mixtures of normal distributions is a reasonable class to study. Assuming the loss function is quadratic, a large class of improved shrinkage estimators is developed in the case of a balanced design. We generalize results of Berger and Strawderman for one observation in the known‐variance case. This methodology also permits the development of a new class of minimax shrinkage estimators of the mean of a p‐variate normal distribution for an unbalanced design. Numerical calculations show that the improvements in risk can be substantial.
A note on L1 consistent estimation
Authors: Yatracos Yannis G. 
Published: June 2006

AbstractLet (𝒳, 𝒜) be a space with a σ‐field, M = {Ps; s o} a family of probability measures on A, Θ arbitrary, X1,…,Xn independently and identically distributed P random variables. Metrize Θ with the L1 distance between measures, and assume identifiability. Minimum‐distance estimators are constructed that relate rates of convergence with Vapnik‐Cervonenkis exponents when M is “regular”. An alternative construction of estimates is offered via Kolmogorov's chain argument.
Exact confidence regions for species assignment based on DNA markers
Authors: Almudevar Anthony 
Published: June 2006

AbstractAssignment of individuals to correct species or population of origin based on a comparison of allele profiles has in recent years become more accurate due to improvements in DNA marker technology. A method of assessing the error in such assignment problems is présentés. The method is based on the exact hypergeometric distributions of contingency tables conditioned on marginal totals. The result is a confidence region of fixed confidence level. This confidence level is calculable exactly in principle, and estimable very accurately by simulation, without knowledge of the true population allele frequencies. Various properties of these techniques are examined through application to several examples of actual DNA marker data and through simulation studies. Methods which may reduce computation time are discussed and illustrated.
k‐sample rank tests using pair‐specific scoring functions
Authors: Archambault W. A. T. , Mack G. A. , Wolfe D. A. 
Published: June 2006

AbstractIn this paper we consider generalizations of the distribution‐free one‐way ANOVA test procedures studied by Puri (1965), such generalizations allowing for possibly different scoring functions for different pairs of samples. The asymptotic distributions of the test statistics are derived and formulas for the asymptotic relative efficiencies of these tests with respect to a parametric competitor are obtained. Applications of these procedures to settings of ordered and umbrella alternatives are presented and potential advantages of this pair‐specific scoring scheme are discussed.
A note on a strong renewal theorem
Authors: Mohan N. R. 
Published: June 2006

AbstractLet {Sn, n≥ 1} be a sequence of partial sums of independent and identically distributed non‐negative random variables with a common distribution functionF.LetFbelong to the domain of attraction of a stable law with exponent α, 0 < α < 1. Suppose H(t) = ϵ N(t), t ⩾ 0, whereN(t)=max(n : Sn≥ t). Under some additional assumptions onF, the difference betweenH(t)and its asymptotic value as t → ∞ is estimated.
On principles and arguments to likelihood
Authors: Evans Michael J. , Fraser Donald A. S. , Monette Georges 
Published: June 2006

AbstractBirnbaum (1962a) argued that the conditionality principle (C) and the sufficiency principle (S) implied the likelihood principle (L); he then argued (Birnbaum 1972) that C and a mathematical equivalence principle M implied L. Evans, Fraser, and Monette (1985a) gave reference details, and this paper gives proof that C alone implies L. The level of support by the profession for L is sharply less than that for S or even for C; thus the paradoxical nature of these results. In this regard, we elaborate on the Monette example (Fraser, Monette, and Ng 1984), which provides a strong case against L. We also examine closely the various proofs linking the principles and find that S and C can each be used operationally to suppress information otherwise deemed relevant. From another viewpoint this says that S and C can each be used in contexts that directly conflict with the original examples and motivations supporting them; the principles can thus be viewed as inappropriately used, or more strongly, as invalid. In either case, the result that C and S imply L or that C implies L can be regarded as noneffective in the context of discriminating applications. A resolution of the apparent anomalies can be obtained by allowing the statistical model to include ingredients additional to those usually present (particularly for subsequent use with conditionality), or alternatively by restricting the application of the principles to contexts where the conflicts would seem not to arise.
A family of admissible minimax estimators of the mean of a multivariate, normal distribution
Authors: Li Tze Fen , Bhoj Dinesh S. 
Published: June 2006

AbstractLetXhas ap‐dimensional normal distribution with mean vector θ and identity covariance matrixI. In a compound decision problem consisting of squared‐error estimation of θ, Strawderman (1971) placed a Beta (α, 1) prior distribution on a normal class of priors to produce a family of Bayes minimax estimators. We propose an incomplete Gamma(α, β) prior distribution on the same normal class of priors to produce a larger family of Bayes minimax estimators. We present the results of a Monte Carlo study to demonstrate the reduced risk of our estimators in comparison with the Strawderman estimators when θ is away from the zero vector.
Mixture models in survival analysis: Are they worth the risk?
Authors: Farewell Vernon T. 
Published: June 2006

AbstractThere has been a recurring interest in models for survival data which hypothesize subpopulations of individuals highly susceptible to some type of adverse event. Other individuals are assumed to be at much less risk. Most commonly, in clinical trials, these models attempt to estimate the fraction of patients cured of disease. The use of such models is examined, and the likelihood function is advocated as an informative inference tool.
Bayesian incorporation of repeated measurements in logistic discrimination
Authors: Andrews D. F. , Brant R. , Percy M. E. 
Published: June 2006

AbstractA common problem in medical statistics is the discrimination between two groups on the basis of diagnostic information. Information on patient characteristics is used to classify individuals into one of two groups: diseased or disease‐free. This classification is often with respect to a particular disease. This discrimination has two probabilistic components: (1) the discrimination is not without error, and (2) in many cases the a priori chance of disease can be estimated. Logistic models (Cox 1970; Anderson 1972) provide methods for incorporating both of these components. The a posteriori probability of disease may be estimated for a patient on the basis of both current measurement of patient characteristics and prior information. The parameters of the logistic model may be estimated on the basis of a calibration trial. In practice, not one but several sets of measurements of one characteristic of the patient may be made on a questionable case. These measurements typically are correlated; they are far from independent. How should these correlated measurements be used? This paper presents a method for incorporating several sets of measurements in the classification of a case.
Statistical inference for some Volterra population processes in a random environment
Authors: Guttorp Peter , Kulperger Reg 
Published: June 2006

AbstractWe study the problem of maximum‐likelihood estimation in some random‐environment population models, defined through nonlinear ltǒ stochastic differential equations. It is shown that a criticality parameter can be estimated consistently. The asymptotic behavior of the estimators is analyzed, and a goodness‐of‐fit test is proposed.
Empirical and rank processes of observations and residuals
Authors: Shorack Galen R. 
Published: June 2006

AbstractEmpirical and rank processes of a sample are shown to converge under weak conditions. These results are then extended to analogous empirical and rank processes formed from the residuals of a linear model. Representations of the limiting processes are obtained by means of a special construction. The technicalities are honed to require few regularity conditions.