bluuebunny/crossref_metadata_2025 huggingface dataset:
An Extended Threshold Model for Analyzing Ordered Categorical Data
Authors: Quednau H. D.
Published: May 2007

This paper presents an extended threshold model for analyzing ordered categorical data. The model admits interactions between the position of the thresholds and the levels of the effective factors. These interactions are described according to the approach of Milliken and Graybill (1970). Especially important for practical application is the special assumption that there is a linear relation between interactions and thresholds, and that the slopes of the concerning regression lines may be different for samples. This means that the latent variables are distributed according to the same type of distributions, but may have different expectations and variances.

Underlying this submodel, the estimation of parameters and the testing of hypotheses according to the maximum likelihood method is described. The procedure is illustrated by a numerical example, and an outline is given about a cluster analysis using model parameters.
Bayesian Approach to Proportional Odds Models for Survival Analysis
Authors: Tan W. Y.
Published: May 2007

In this paper Bayesian approach is adopted to develop inferences about parameters in proportional odds models. Bayesian posterior intervals for coefficients in proportional odds models are derived by using approximation given in Pregibon (1981). The results are illustrated by using the lung cancer survival data reported by Prentice (1973).
Comparing Vectors of Adjusted Means when Covariance Matrices are Unequal
Authors: Misra R. K.
Published: May 2007

The ability to distinguish between stocks of fish is of vital importance in fisheries management programs. Morphometric measurements are commonly employed to separate biological populations. Unique role of multivariate analysis of covariance in separating fish stocks has been recognized recently. However, fish populations frequently differ in their covariance matrices and sometimes also in vectors of slope (on the covariate) coefficients. In this article the following are presented: (a) a procedure for comparing adjusted (for variations in body sizes of specimens) mean vectors of populations with unequal covariance matrices and slopes, and (b) a study to distinguish between beaked redfishes based on the analysis of a real data set by this procedure. This will also serve as a numerical example.
The Monofactorial Model for Recurrence Risks with Generalized Penetrance
Authors: Khamis H. J.
Published: May 2007

Recurrence risks are derived explicitly in terms of gene frequencies and penetrance coefficients for the general case in which all genotypes have incomplete penetrance. Maximum likelihood estimation of recurrence risks is achieved through the use of the semi‐symmetric intraclass contingency table. The resulting formulas and estimation procedure can be useful for the analysis of population and family data, and in genetic counselling.
Ultimate Size of the Drug Addict Population
Authors: Dayananda P. W. A.
Published: May 2007

A model presented in a previous paper by Billard et al. (1985) on the spread of drug addiction in a closed population is further examined as a random walk process. The addiction process depends on the initial conditions and the parameters of the process. This paper considers the ultimate size of the drug addict population which is shown to satisfy a recurrence relation. A general expression for the distribution of the ultimate size of the number of drug addicts is derived; its expected size also presented. For given initial conditions and the values of the parameters, numerical values of the expected size of the ultimate number of addict population are presented and they are compared with the corresponding values for the deterministic model.
On a probability Model for Classifying the Unknown Causes of Death Due to Two Competing Risks into Assignable Causes
Authors: Biswas Suddhendu , Noor Hamed Saad
Published: May 2007

A probability model to classify the otherwise unclassified causes of death due to two competing risks R1 and R2 has been evolved in this paper. A simple model based on Poisson inputs has been illustrated by numerical illustrations. Further generalization of the model with more than two competing risks is straightforward for the given model.
A Note on the Two‐Compartment Model in Pharmacokinetics
Authors: Masuyama M.
Published: May 2007

The almost‐one parameter hypothesis is applied to the two‐compartment model in pharmacokinetics. If the model is represented by a difference equation, then its coefficients are highly correlated, as was expected from the hypothesis.
Goodness‐of‐Fit Testing for the Logistic Regression Model when the Estimated Probabilities are Small
Authors: Hosmer D. W. , Lemeshow S. , Klar J.
Published: May 2007

The distribution of the Hosmer‐Lemeshow chi‐square type goodness‐of‐fit tests (Čg, Ȟg) for the logistic regression model are examined via simulations designed to examine their behavior when most of the estimated probabilities are small or are expected to fall in a few deciles. The results of the simulations show statistic Čg should be used when the two outcome groups (y = 0, 1) are not well separated, Δ≤2, where Δ2 is the Mahalanobis distance. Statistic Ȟg should be used when Δ ≥ 8. Either statistic may be used when 2 ≦ Δ ≦ 8. All tests should be used with caution when the proportion in the sample with y = 1 is less than 0.1.
Modification of the Minimum Logit Chi‐Squared Estimator in Simple Linear Logistic Regression
Authors: Hosmane B.
Published: May 2007

A new modification of Berkson's minimum logit chi‐squared estimator in simple linear logistic regression is suggested in order to achieve reduction of first order bias of the estimator as well as in the model. Furthermore, unlike estimators currently available, our procedure is quite simple to apply in practice and is valid even in the presence of zero frequencies in the table.
Unbiased Estimation of Relative Risk Using a Binomial with a Negative Binomial Plan
Authors: Roberts Ch.
Published: May 2007

The use of the binomial distribution for the numerator and the negative binomial for the denominator in prospective studies leads to an unbiased estimate of relative risk and an unbiased estimate for combining experiments. Optimal sample sizes for groups are calculated and confidence intervals for the relative risk are presented. The efficiency of plans are evaluated by comparing variances and coefficients of variation.
On Edge Corrections for the Point‐Event Analogue of the Clark‐Evans Statistic
Authors: Doguwa S. I. , Upton G. J. G.
Published: May 2007

Edge corrections are reported for the mean and variance of the average distance between a sampling point and the nearest event point in a spatial point pattern, for the case of a regular grid of sampling points. Using these corrections the point‐event analogue of the Clark‐Evans statistic is found to be a powerful detector of departures from randomness in the clustered direction.
A Discrete Charlier Series Distribution
Authors: Ong S. H.
Published: May 2007

A discrete distribution involving Charlier polynomial is considered. This distribution can be regarded as the counterpart of the non‐central negative binomial distribution (Ong and Lee, 1979). Application to data‐fitting is illustrated.
A Technique for the Analysis of Unbalanced Data
Authors: Singe Kuan P. , Singh Umed
Published: May 2007

The regression methods with dummy variables have been shown to be effective in preventing confusion in the analysis of linear models. In particular, this model simplifies interpretation of parameters and clarifies hypothesis statements. All existing methods have been shown as special cases of the general linear hypothesis in regression setting.

Three regression on dummy variables methods are examined critically to bring out the salient features of each method. The choice of a method should be based on the way definitions of the parameters are desired. The linear models are considered in a regression model setting. This has been done by defining appropriate dummy variables in a regression model which often is desirable, if not mandatory, when dealing with unbalanced data involving two or more factors.
Estimation by Maximum Entropy Subject to Second‐Order Conditions
Authors: Lefkovitch L. P.
Published: May 2007

If the variance,V=V(μ, ϑ) is some known function of the mean, μ = μ(β), where ϑ and β may include unknown parameters, then given empirical data, this paper describes how to estimate the unknown parameters by choosing them to satisfy the variance/mean relationship, and simultaneously to require that the sampling probability distribution has maximum entropy. Bounds for the estimated values of the unknown parameters can be obtained by a further application of the maximum entropy principle. The power variance function,V(μ)=λμϑis discussed, including some special cases of λ and ϑ. The procedure is briefly compared with quasi‐ likelihood, and illustrated by some numerical examples.
A Logic Programming and Expert Statistical Systems Approach for Tissue Characterization in Magnetic Resonance Imaging
Authors: Levy G. C. , Dudewicz E. J. , Harner T. J. , Dudewicz Edward J. , Wehrli F. W. , Breger R.
Published: May 2007

The main research goal has been to evaluate significant factors affecting the in vivo magnetic resonance imaging (MRI) parameters T, T, T2, and 1H density. This approach differs significantly from other such projects in that the experimental data analysis is being performed while concurrently developing automated, computer‐aided analysis software for such MRI tissue parameters.

In the experimental portion of the project, statistical analyses, and a heuristic minimum/maximum discriminant analysis algorithm have been explored. Both methods have been used to classify tissue types from 1.5 Tesla transaxial MR images of the human brain.

The developing program, written in the logic programming language Prolog, is similar in a number of ways to many existing expert systems now in use for other medical applications; inclusion of the underlying statistical data base and advanced statistical analyses is the main differentiating feature of the current approach.

First results indicate promising classification accuracy of various brain tissues such as gray and white matter, as well as differentiation of different types of gray matter and white matter (e.g.: caudate‐nucleus vs. thalamus, both representatives of gray matter; and, cortical white matter vs. internal capsule as representative of white matter). Taking all four tissue types together, the percentage of correct classifications ranges from 73 to 87%.
Statistical Inference for a Gibbs Point Process of Mutually Non‐Intersecting Discs
Authors: Stoyan D. , Stoyan D.
Published: May 2007

For a Gibbs point process of mutually non‐intersecting discs a parameter estimation method is suggested. It is applied to a pattern of positions of beadlet anemones, for which, until now, no appropriate Gibbs process model has been found.
Nonparametric Two‐Sample Tests for General Clinical Data
Authors: Hilgers R. A.
Published: May 2007

Starting from the discussion of a practical example a unifying concept for the derivation of meaningfully interpretable nonparametric tests for the two‐sample case is developed which may well be adapted for other designs, too.

This methodology covers other well‐known procedures, e.g. Fisher's exact test, the Wilcoxon‐Mann‐Whitney and Gehan's tests, and may furthermore be extended to all situations sharing the same fundamental structural property of the sample space, namely its strict order induced by the substantial problem under study.

The resulting test procedure is discussed for a randomization argument, exact and approximate, as well as for the general specific test problem. A numerical example is provided.
VariousX2‐Tests of Homogeneity: Some Comments
Authors: Elandt‐Johnson Regina C.
Published: May 2007

Methodological issues in the analysis of incidence rates or prevalence proportions for count data, presented in a form of a sequence of 2×2 tables, corresponding to levels (strata) of a specified variable (risk factor)X, are discussed. Suppose λ1iand λ2iare the incidence rates of an eventDin the ith stratum for populations 1 and 2, respectively. Thehomogeneity(null) hypothesis is formulated in the form:H0:λ1i=λ2ifor alli(i= 1, 2, …,I). ThreeX2‐tests forH0and their theoretical bases are discussed:XTotal2which is sensitive to alternativesHA:λ1i± λ2ifor at least somei;XComb2which is sensitive to alternativesHA: λ1iλ2i2or< λ2ibutnot bothfor alli; andXDiff2which is sensitive to alternativesHA:λ1i>λ2i3for someiand λ1i′< λ2i′for somei′ (i≠i′). These statistics satisfy the relationXTotal2=XComb2+XDiff2. Also,X′2‐statistic for pooled data is calculated, which in conjunction withXComb2can serve for detecting confounding. Although most of these techniques are known, they are rather scattered in the literature, and not always considered jointly, as it is emphasized in the present paper. It is hoped that these comments will be helpful to biostatisticians as well as to epidemiologists and medical researchers in the analysis of mortality and morbidity data. For illustration, two examples with large sets of epidemiological data are given.
The Wald Statistic in Proportional Hazards Hypothesis Testing
Authors: Bangdiwala Shrikant I.
Published: May 2007

In survivorship modelling using the proportional hazards model of Cox (1972, Journal of the Royal Statistical Society, Series B, 34, 187–220), it is often desired to test a subset of the vector of unknown regression parameters β in the expression for the hazard rate at timet. The likelihood ratio test statistic is well behaved in most situations but may be expensive to calculate. The Wald (1943, Transactions of the American Mathematical Society 54, 426–482) test statistic is easier to calculate, but has some drawbacks. In testing a single parameter in a binomial logit model, Hauck and Donner (1977, Journal of the American Statistical Association 72, 851–853) show that the Wald statistic decreases to zero the further the parameter estimate is from the null and that the asymptotic power of the test decreases to the significance level. The Wald statistic is extensively used in statistical software packages for survivorship modelling and it is therefore important to understand its behavior. The present work examines empirically the behavior of the Wald statistic under various departures from the null hypothesis and under the presence of Type I censoring and covariates in the model. It is shown via examples that the Wald statistic's behavior is not as aberrant as found for the logistic model. For the single parameter case, the asymptotic non‐null distribution of the Wald statistic is examined.
On Testing Equality of Means of Correlated Variates with Missing Data on One Response
Authors: Bhoj Dinesh S.
Published: May 2007

A statistic is proposed for testing the hypothesis of equality of the means of a bivariate normal distribution with unknown common variance and correlation coefficient when observations are missing on one of the variates. The distribution of the statistic is approximated by a normal distribution under the null hypothesis. The empirical powers of the statistic are computed and compared with those of the conventional paired t and the other known statistics. The power comparisons support the use of the proposed test.
On Comparing Correlated Means in the Presence of Incomplete Data
Authors: Bhoj Dinesh S.
Published: May 2007

Two statistics are proposed for testing the hypothesis of equality of the means of a bivariate normal distribution with unknown common variance and correlation coefficient when observations are missing on both variates. One of the statistics reduces to the one proposed by Bhoj (1978, 1984) when the unpaired observations on the variates are equal. The distributions of the statistics are approximated by well known distributions under the null hypothesis. The empirical powers of the tests are computed and compared with those of some known statistics. The comparison supports the use of one of the statistics proposed in this paper.
On Model‐Choice in Discrimination with Categorical Variables
Authors: Wernecke K.‐D. , Haerting J. , Kalb G. , Stuerzebecher E.
Published: May 2007

An algorithm for model selection in discrimination with categorical variables is presented. It is based on four models applied hierarchically and linked with a build‐up procedure of feature‐selection. The choice of models and features is ensured by a consequent cross‐validation. Results of an application in medical diagnostics are described.
Comparing Power Behaviours for Some Goodness‐of‐Fit Test Statistics in Sparse Multinomials
Authors: Lawal H. B.
Published: May 2007

This paper is concerned with the power behaviour of four goodness‐of‐fit test statistics in sparse multinomials withkcells. Most previous work has been concerned only with both Pearson'sX2and the likelihood ratio test statistics. We consider in this study, two additional test statistics, namely, the Cressie‐Read test statistic –I(2/3) and the modified Freeman‐Tukey test (FT) statistic. Becausek≥ 10 in this study, a Monte Carlo procedure based on 1000 simulated samples is used to estimate the powers for the four test statistics. Alternatives on various line segments are employed. Results suggest that none of the test statistics completely dominate the other and that the choice of which test to use depends on the nature of the alternative hypothesis. These results are consistent with those obtained by West and Kempthorne (1972), although, the Pearson's χ2test statistic may be preferred because of its closer approximation to the χ2distribution in terms of the attained α levels.
Comparing Stochastically Restricted Linear Estimators in a Regression Model
Authors: Liski Erkki P.
Published: May 2007

Conditions for superiority of the minimum dispersion estimator over another with respect to the covariance matrix are derived when the vector parameter of a regression model is subject to competing stochastic restrictions. The restrictions may also consist both of a deterministic part and a stochastic part.
F‐tests for Hypotheses with Block Matrices and Under Conditions of Orthogonality in the General Multivariate Gauss‐Markoff Model
Authors: Oktaba Wiktor
Published: May 2007

The multivariate general Gauss‐Markoff (MGM) model (U, XB, ∑⊗σ2V) when the matrices V ≥ 0 and ∑ > 0 are known and the scalar σ2 > 0 is unknown, is considered. The present paper is a continuation of two earlier works (Oktaba, 1988a, b). If XB = X1Σ + X2Δ, then the F‐test for verification the hypothesis WΣA = 0 is presented. Moreover, under conditions of orthogonality the decomposition of the matrix SA (ŁBCA)′L−(ŁBCA) into the sum of s = r(L) matrices is given, where ŁBCA is the estimator of the parametric estimable functions ŁBCA, Cov (ŁBCA) = A′ ∑⊗σ2L = ŁC4Ł′, B̌ = (X′T−X)−X′T−U, C4 = (X′T−X)−M, where M = M′ is any arbitrary matrix such that R(X) ⊂ R(T), T=V+XMX′; T− is any c‐inverse. R(A) is the linear space generated by the colums of A. Then under additional assumption on normality of U the statistics F for testing ŁBA = 0 is deduced.

Under conditions of normality of U and decomposition of SA, the statistics F1, …, Fs for the hypotheses ji BA = 0 (i = 1,…, s) are established.
Cost‐Efficient Density Estimation Based on Nearest Individual Distances in a Natural Forest
Authors: Prayag V. R. , Gore A. P.
Published: May 2007

One useful method of estimating tree density is based on point to individual distances. Estimators are available for data on i‐th nearest individual distances, i = 1, 2, 3,…, etc. This paper provides a method of deciding the optimal value of i in the sense of providing the maximum likelihood estimator of density with minimum mean square error subject to given outlay. The result derived for a Poisson forest is extended to an aggregated forest.
On the Additive and Multiplicative Models of Relative Risk
Authors: Kodell Ralph L. , Gaylor D. W.
Published: May 2007

Two popular models of absence of synergism in epidemiologic cohort studies are analyzed and compared. It is shown that the statistical concept of the union of independent events that traditionally has given rise to the “additive” model of relative risk can also generate the “multiplicative” model of relative risk. In fact, the same set of approximating conditions can be used to generate both models, which suggests a lack of identifiability under the traditional approach. An alternate approach is proposed in this paper. The new approach does not require the assumption that background risk factors are independent from causal agents of interest. The concept of “dose additivity” is discussed.
Nearest Neighbours: Estimators for Heterogeneity
Authors: Van Linde A. Der
Published: May 2007

Papadakis' method is shown to be an example of an estimation procedure for a heterogeneity function localized in a reproducing kernel Hilbert space. Within this framework some current models for the evaluation of field trials are discussed.
Selection of Populations: An Overview and Some Recent Results
Authors: Van Laan P. Der , Vebdooren L. R.
Published: May 2007

In practice the problem of comparing several treatments can often be formulated as which treatment can be considered best. Selection procedures have been designed specifically to answer questions like this one. In many situations selection procedures are more realistic than the usual testing procedures. In this paper an introduction and an overview of selection of populations will be given with special reference to Normal, Binomial, Poisson and Multinomial populations. In the field of agricultural applications these distributions play an important role.

Bechhofer's and Gupta's approach are presented side by side for a number of problems. After that the relatively new procedures of Somerville are discussed. Finally, some recent results are presented.
Stabilization Coefficient of Random Variable
Authors: Liu Chui‐Yu , Zheng Zhang‐Yuan
Published: May 2007

Coefficient of variation, standard deviation divided by mean, has some essential defects. Its density, expectation and variance are too complex to make the statistical inference for such a coefficient. The definition of stabilization coefficient is just the reciprocal of variation coefficient, mean divided by standard deviation. Such a coefficient has a simple expectation and a simple variance, and is an asymptotically unbiased estimator and a consistent estimator of its true value. Furthermore, coefficient of stabilization has an asymptotic normality. Due to its statistical advantages, coefficient of stabilization is easy to be tested statistically. In some applied fields, usually, there is an increasing standard deviation accompanying an increasing mean. Coefficient of stabilization can be practically used for some comparison studies in such fields. Illustrations about comparing microorganism strains are given in this paper. The robustness of stabilization coefficient is satisfactory.
On Some Application of Non‐Homogeneous Semi‐Markov Processes
Authors: Wajda W.
Published: May 2007

In this paper a non‐homogeneous semi‐Markov process is applied to a study of the behaviour of a cell after irradiation. The definition and main properties of the non‐homogeneous semi‐Markov process are reminded. Moreover one assumes that the cell may stay in one of four states namely, normal state, damaged state 1, damaged state 2, state of death, which are defined. Using the results of the theory of non‐homogeneous semi‐Markov processes and Markov renewal theory the characteristics of interest pertaining to the cell behaviour are studied.
On Second Order Neighbourhood Analysis of Mapped Point Patterns
Authors: Doguwa Sani I.
Published: May 2007

Getis and Franklin (1987), introduced a technique based on second order methods, called second order neighbourhood method, which is used to quantify clustering at various spatial scales. Variants of this method are introduced for testing whether a spatial point pattern is consistent with the hypothesis of a Poisson process. These variants are applied to point location data for a sample of Ponderosa pine (Pinus ponderosa) trees.
Asymptotic Interval Estimation of Some Cause‐Specific Mortality Risk Measures in Epidemiologic Studies
Authors: Rao B. Raja , Marsh Gary M. , Winwood Joan
Published: May 2007

The present paper describes the algebraic and statistical relationships between the population‐based mortality risk measures, the Standardized Mortality Ratio (SMR) and the Standardized Risk Ratio (SRR), and their respective proportional mortality‐based counterparts, the internally and externally Standardized Proportional Mortality Ratios (SPMR, SePMR). The paper shows, how under some reasonable assumptions, asymptotically precise inferences about population‐based risk measures can be made from studies of proportional mortality. Through application of the asymptotic multivariate normal approximation to the multinomial distribution, shortest confidence intervals for the relative SMR (RSMR) involving the corresponding SPMR are constructed for any cause of death. This same technique is also used to construct asymptotic prediction intervals about the cause‐specific SePMR which, with high probability, contains the corresponding relative SRR (RSRR).

The utility of the proportional mortality measures SPMR and SePMR as estimators of the corresponding cause‐specific risks RSMR and RSRR in occupational epidemiologic research is empirically evaluated using data from two recent occupational cohort studies.

Asymptotic Bonferroni type simultaneous inferential techniques are also developed for these measures which facilitate the assessment of overall risk in the presence of several competing factors.
A Note on the Application of Martingales in a Problem of Non‐Communicable Epidemics
Authors: Biswas S. , Noor Hamed Saad
Published: May 2007

The present paper is a Martingale approach to some non‐communicable epidemic problem (e.g. cervical cancer). It is assumed the progress of the disease from pre‐cancerous lesions to several grades of dysplasia and ultimately leading to carcinomia in situ and invasive cancer follows by consecutive hittings; and the regression (or the backward movement) from these states to ultimately non cancerous state; may be analogous to consecutive healings. Each hitting and healing thus considered to be a birth and death respectively in the density dependent linear birth and death process. Given that a patient is in some states of dysplasia the problem lies in finding the proportion of patients coming back to noncancerous state and the expected time for the same. Martingales constructed on a linear birth and death process have been employed to answer the problems.
A Response‐Additive Model for Analyzing Mixtures of Two Chemicals in the Salmonella Reversion Assay
Authors: Chen James J. , Heflich Robert H. , Hass Bruce S.
Published: May 2007

A statistical model is proposed for analyzing the mutagenic responses produced by mixtures of two chemicals in the Salmonella reversion assay. This model is based on the simplex‐lattice design for mixtures with the total concentration fixed. The dose‐response relationship is expressed as a function of both the proportions of the two chemicals and the total concentration of the chemicals in the mixture. If the joint action of two chemicals can be predicted by response‐additivity, then the response of the mixture at the total concentrationTcan be represented by the weighted average of the responses produced by the individual chemicals at the same concentrationTwith the weights for individual responses being equal to the proportions of the chemicals in the mixture. Two non‐additive models, synergism and antagonism, are discussed. An example is illustrated by analyzing the joint mutagenic effects of 1‐nitrobenzo(a)pyrene (1‐NBP), and 3‐NBP in the Salmonella reversion assay.
General Statistical Issues in the Analysis of Pedigree Data
Authors: Wilson Susan R.
Published: May 2007

When analysing pedigree data, it is just as important to detect deficiencies in the fitting and application of the current model as to be able to specify the model, estimate its parameters and test appropriate hypotheses. Some of the statistical issues that arise in the fitting and application of genetic models to pedigree data are discussed in this paper. A particular set of data and a non‐controversial characteristic have been chosen to highlight these issues.
A Nonparametric Test for Ordered Alternatives in Two‐Way Layouts with Censored Data
Authors: Magel Rhonda C.
Published: May 2007

A nonparametric test is presented to test for ordered alternatives of the treatment effects when the data follow a two‐way layout. The observations are subject to arbitrary right censorship. The test is similar to the one developed by Hettmansperger and Norton (1987) for uncensored observations.
A Comparison of Methods to Deteet Adulteration in Natural Products Under a Restricted Alternative
Authors: Katz B. P. , Brown M. B.
Published: May 2007

Multivariate statistical tests used to assess purity of natural food products, such as fruit juices, do not assume prior knowledge about the most likely causes of adulteration. We describe a likelihood ratio test that has a directional alternate hypothesis so that prior knowlege about the most likely method of adulteration can be utilized. Critical regions for this statistic are based on a nonparametric tolerance interval, which makes it insensitive to an assumption of multivariate normality.

This new test is compared to two tests currently used for identifying adulterated samples. It is shown that the new test will have increased power relative to the other tests in the direction of the predicted adulteration.
Spatial Data Analysis of Regional Counts
Authors: Cressie Noel , Read Timothy R. C.
Published: May 2007

Counts data from spatially continguous regions offer a challenge to the statistician both from the data analytic and the statistical modeling point of view. Important applications include epidemiological studies (e. g., cancer mortality over the counties of the USA) and Census surveys (e. g., undercount over the Census blocks of an urban area). It has long been recognized by time‐series analysts that data close together in time usually exhibit higher dependence than those far apart. Time‐series data analysis relies on methods of data transformation, detrending, and autocorrelation plotting. It is our intention in this article to generalize this approach to a spatial setting. To do this we consider a small spatial data set of 100 observations. Through the use of a square‐root transformation, a weighted median polish and a variogram analysis of the median‐polish residuals, we represent the transformed data as a trend plus stationary error. Thus we show how standard data‐analytic techniques can be modified both to mitigate and to exploit the spatial relationships.
The Effect of Parameters Change of a Semi‐Markov Model on Interval Transition Probabilities
Authors: Jain R. K.
Published: May 2007

This paper examines the changes in parameters of a Semi‐Markov model and its impact on interval transition probabilities. Computational techniques are used to illustrate that the model is sensitive enough to depict changes in the interval transition probabilities if the paramters of the model are modified.
Some Improved Regression Estimators of Heritability
Authors: Verma Davendra , Jain J. P.
Published: May 2007

Three new improved regression estimators of heritability viz. modified range restricted estimator, minimum quadratic loss estimator and minimax linear restricted estimator are proposed. In addition, these estimators are illustrated and compared numerically with the existing restricted estimator based on linear stochastic constraint.
On the Behaviour of Fligner‐Wolfe‐Trend Test “Control versus k Treatments” with Application in Toxicology
Authors: Hothobn Ludwig
Published: May 2007

The behaviour of Fligner‐Wolfe‐trend test “control versus k treatments” was characterized by simulation. Sample size estimation took place via non‐central t‐distribution. Some results on asymptotic efficiency were shown and compared with simulation results for small sample sizes. A test version for umbrella alternatives was given and characterized by simulation.
The Analysis of Sensory Data by Generalized Linear Model
Authors: Randall J. H.
Published: May 2007

The use of generalized linear model theory in formulating and testing hypotheses which may arise in the analysis of ordinal scale organoleptic data is illustrated.
Approximate Moments of the Adès Distribution
Authors: Holgate Philip
Published: May 2007

Laplace's method of approximating to integrals is used to obtain asymptotic expressions for the central moments, and the moments about zero, of the Adès distribution. A correction term for the power law relationship between the variance and the mean is derived.
A New Statistical Method for Mixed Variates Analysis in Epidemiological Research
Authors: Wortha H.‐P.
Published: May 2007

Epidemiologically oriented research often may not do without observational or only partially controlled studies. In many such situations both qualitative characteristics and quantitative ones are observed. In literature there are different methods of handling such problems. The paper presents a method for analyzing dependencies resp. associations between random variates of any kind. The model concerned fullfills the whole field between analysis of variance, analysis of covariance and contingency table analysis. The method is named MIVA or mixed variates analysis, bases on the class of Conditional Gaussian Distributions of the exponential family and results in a unique system of mixed and unmixed measures of association–of pairwise, partial, multiple and global type. These measures are easy to be estimated and tested on significant deviation from zero. They may be used describing or analyzing dependence structures in many epidemiological studies but also in other fields.
A Stochastic Model for Coupled Enzyme System
Authors: Sen Pali
Published: May 2007

The molecular biology of transformed cancer cells singles out key enzymes as sensitive targets of anti‐cancer drugs. Here we use one substrate–one intermediate–one final product model for a coupled enzyme system. The transfer rates for the mechanism are taken as continuous but subject to random fluctuations. Explicit formulae for the first moments of the distribution of the process are obtained. These formulae allow us to take into account not only the variability between the subjects, but also the variability of the process for a single subject. The present results allow us also to build the prediction interval for a particular time period given the observations for some preceding moments.
Some Mathematical Properties of Cumulative Damage Models Regarding Their Application in Cancer Epidemiology
Authors: Becker Nikolaus , Rittgen Werner
Published: May 2007

In an earlier paper, cumulative damage models (CD models) were proposed for modelling the epidemiological aspects of carcinogenesis. In the present paper, further, mainly mathematical support is given for the adequacy of this approach. In the first place, this concerns the aspect that the cumulative damage process is a compound Poisson process. Secondly, it will be demonstrated that the CD models can be considered as a formal generalization of certain well‐known special carcinogenesis models. A more intensive investigation of these models themselves makes it evident that, on account of their mathematical qualities, they will possibly place very efficient new measures at the disposal of epidemiology. A diffusion approximation, however, does, after first experiments, not appear to make the handling of the models any easier but, on the contrary, to lead to a loss of certain pleasant qualities.
Indian Biotech Bazaar: A swot analysis
Authors: Kumar Abhishek
Published: May 2007

Biotechnology is a life science‐based technique especially used in agriculture, medicine and food sciences. It is generally defined as the manipulation in organisms to generate products for the welfare of the world. Biotechnology combines disciplines such as genetics, biochemistry, microbiology, and cell biology along with information technology, chemical engineering, robotics etc. It includes basic industries such as food processing, tissue culture, plant development and other sophisticated ones such as recombinant therapeutics and diagnostics. Biotechnology, globally recognized as a rapidly emerging and far‐reaching technology, is aptly described as the “technology of hope” for its promise of food, health and environmental sustainability. In India, biotechnology employs more than 10 000 people and generates roughly US$ 500 million in revenue annually. The biotechnology market has increased its sales from Rs. 50 billion in 1997 to Rs.70 billion in 2000, and is expected to cross Rs. 240 billion by the year 2010. In India, the human health biotech products account for 60% of the total market; agribiotech and veterinary 25%, medical devices, contract research and development (R&D), reagents and supplies constitute the remaining 15% Moreover, to facilitate foreign investment, capital and government policies are being revised. Other important industries include industrial enzyme manufacture, bioinformatics, and medical devices. Biotechnology has had limited appeal so far on our capital markets, and we have less then a dozen biotech companies listed on the public markets.
Amphetamine effects on brain protein structure and oxidative stress as revealed by FTIR microspectroscopy
Authors: Rodríguez‐Casado A. , Alvarez I. , Toledano A. , de Miguel E. , Carmona P.
Published: May 2007

Amphetamines are psychostimulants abused by man, that eventually leads to drug dependence. Amphetamine administration to rodents has been shown to provoke significant neurotoxicity involving dopaminergic nerve terminal degeneration. However, little information related to the effect of amphetamines on reactive oxygen species (ROS) production and neurotoxicity in brain is currently available. Herein we report the biochemical alterations of lipids and proteins in brain sections from amphetamine‐treated rodents using infrared microspectroscopy, immunohistochemistry, and immunoblotting. The spectroscopic changes reveal for the first time the formation of β‐sheet‐rich proteins in the cortex, but no significant protein alterations are visible in hippocampus region where hydroperoxide concentration is found to be lower relative to cortex. These result suggest that ROS generated by amphetamine‐mediated oxidative stress induce formation β‐sheet‐rich proteins which can be of amyloid β‐like character. © 2007 Wiley Periodicals, Inc. Biopolymers 86: 437–446, 2007.

This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com
Molecular Assemblies from Imidazolyl‐Containing Haloalkenes and Haloalkynes: Competition between Halogen and Hydrogen Bonding
Authors: Bouchmella Karim , Boury Bruno , Dutremez Sylvain G. , van der Lee Arie
Published: May 2007

The structural characterization of molecular assemblies constructed from imidazolyl‐containing haloalkenes and haloalkynes is reported. 1‐(3‐Iodopropargyl)imidazole (2) and 1‐(2,3,3‐triiodoallyl)imidazole (5) were synthesized from 1‐propargylimidazole (1). In the solid state, these wholly organic modules self‐assemble through N⋅⋅⋅I halogen‐bonding interactions, thus giving rise to polymeric chains. The N⋅⋅⋅I interaction observed in 2 (d(N⋅⋅⋅I)=2.717 Å, ∢C(sp)‐I⋅⋅⋅N=175.8°) is quite strong relative to previously reported data. The N⋅⋅⋅I interaction in 5 (d(N⋅⋅⋅I)=2.901 Å, ∢C(sp2)‐I⋅⋅⋅N=173.6°) is weaker, in accordance with the order C(sp)‐X←base>C(sp2)‐X←base. Compound 5 was found to give a 1:1 cocrystal 4 with morpholinium iodide (6). In the X‐ray crystal studies of 4, N⋅⋅⋅I halogen‐bonding interactions similar to those observed in 5 were shown not to be present, as the arrangement of the molecules is governed by two interwoven hydrogen‐bonding networks. The first network involves N‐H⋅⋅⋅O interactions between nearby morpholinium cations, and the second network is based on N‐H⋅⋅⋅N hydrogen bonding between morpholinium cations and imidazolyl groups. Both hydrogen‐bonding schemes are charge‐assisted. Halogen bonding is not completely wiped out, however, as the triiodoalkene fragment forms a halogen bond with an iodide anion in its vicinity (d(I⋅⋅⋅I)=3.470 Å, ∢C(sp2)‐I⋅⋅⋅I=170.7°). X‐ray crystal studies of 6 show a completely different arrangement from that observed in 4, namely, N‐H⋅⋅⋅O interactions are not present. In crystalline 6, morpholinium cations are interconnected through C‐H⋅⋅⋅O bridges (d(H⋅⋅⋅O)=2.521 and 2.676 Å), and the NH2+ groups interact with nearby iodide anions (d(H⋅⋅⋅I)=2.633 and 2.698 Å).
Eutectic‐Based Ionic Liquids with Metal‐Containing Anions and Cations
Authors: Abbott Andrew P. , Barron John C. , Ryder Karl S. , Wilson David
Published: May 2007

Eutectic mixtures of zinc chloride and donor molecules such as urea and acetamide are described and it is proposed that these constitute a new class of ionic liquids. FAB‐MS analysis shows that the liquids are made up of metal‐containing anions and cations in which the donor is coordinated to the cation. Data on the viscosity, conductivity, density, phase behaviour and surface tension are presented and these are shown to be significantly different to other related ionic liquids that incorporate quaternary ammonium salts. The conductivity and viscosity are comparable with other ionic liquids and the data fit well to the Hole theory model recently proposed.
π–π Stacking versus Steric Effects in Stereoselectivity Control: Highly Diastereoselective Synthesis of syn‐1,2‐Diarylpropylamines
Authors: García Ruano José L. , Alemán José , Alonso Inés , Parra Alejandro , Marcos Vanesa , Aguirre José
Published: May 2007

N‐Arylarylideneamines react with sulfinylbenzyl carbanions derived from 2‐(p‐tolylsulfinyl)toluenes (S)‐1 and (S)‐2, affording epimeric mixtures at C1 of 1,2‐diarylethyl‐ and 1,2‐diarylpropylamine derivatives. The sulfinyl group completely controls the configuration at C2 in the reactions of (S)‐2. The configuration at C1 depends on the electron density of the ring adjacent to the iminic carbon atom which is modulated by π–π stacking interactions with the ring joined to the carbanionic centre. The stereoselectivity was controlled by modifying the acceptor character of the arylideneamine ring with appropriate substituents, the formation of the highly selective (R) configuration at C1 being made possible by electron‐donating groups. N‐(2,4,6‐Trimethoxyphenyl)arylideneamines have been shown to be suitable starting materials for the preparation of (R)‐1,2‐diarylethyl‐ and (1R,2S)‐1,2‐diarylpropylamines (syn epimers) in a highly stereoselective manner.
Single‐Triggered AB6 Self‐Immolative Dendritic Amplifiers
Authors: Shamis Marina , Shabat Doron
Published: May 2007

Self‐immolative dendrimers are a unique class of molecules that are able to disassemble upon undergoing a specific triggering reaction through domino‐like fragmentations. We have designed and synthesized a novel AB6 self‐immolative dendritic adaptor that amplifies a single cleavage event into the release of six reporter units. The disassembly mechanism is based on a specifically triggered cleavage event followed by elimination of a cyclic urea derivative and six consecutive quinone methide eliminations. The system was disassembled under both organic and aqueous conditions by either chemical or enzymatic triggering. Various reporter molecules and triggering groups were introduced onto the dendritic adaptor to obtaining sensor molecules with enhanced properties for diagnostics and imaging.
Cover Picture: Organogels of 8‐Quinolinol/Metal(II)–Chelate Derivatives That Show Electron‐ and Light‐Emitting Properties (Chem. Eur. J. 15/2007)
Authors: Shirakawa Michihiro , Fujita Norifumi , Tani Takahiro , Kaneko Kenji , Ojima Masayoshi , Fujii Akihiko , Ozaki Masanori , Shinkai Seiji
Published: May 2007

Newly designed coordination gelators have been produced. In their Full Paper on page 4155 ff., S. Shinkai et al. describe how 8‐quinolinol complexes show interesting phosphorescence and field emission properties when they are integrated along the low‐molecular‐weight gel fibers.
Magnetic resonance imaging on an NMR spectrometer. An experiment for the physical chemistry laboratory
Authors: Steinmetz Wayne E. , Maher Cyrus R.
Published: May 2007

We converted a conventional Fourier‐transform NMR spectrometer into an MRI imager by installing a triple‐axis gradient probe and medical imaging software. This arrangement permits imaging of materials that fit into a 5‐mm NMR tube to a resolution of 0.05 mm or better. The experiment introduces the student to the physical principles underlying MRI such as gradients, spin echoes, multidimensional spectroscopy, and relaxation. Students employ a multi‐slice‐multi‐echo (MSME) method to image a biological specimen and measure the transverse relaxation time, T2, of water in selected regions of interest. © 2007 Wiley Periodicals, Inc. Concepts Magn Reson Part A 30A: 133–139, 2007
GABA distribution in lamprey is phylogenetically conserved
Authors: Robertson Brita , Auclair François , Ménard Ariane , Grillner Sten , Dubuc Réjean
Published: May 2007

The localization of γ‐aminobutyric acid (GABA) has been well described in most classes of vertebrates but not in adult lampreys. The question if the GABA distribution is similar throughout the vertebrate subphylum is therefore still to be addressed. We here investigate two lamprey species, the sea lamprey,Petromyzon marinus, and the river lamprey,Lampetra fluviatilis, and compare the GABA pattern with that of other vertebrates. The present immunohistochemical study provides an anatomical basis for the general distribution and precise localization of GABAergic neurons in the adult lamprey forebrain and brainstem. GABA‐immunoreactive cells were organized in a virtually identical manner in the two species. They were found throughout the brain, with the following regions being of particular interest: the granular cell layer of the olfactory bulb, the nucleus of the anterior commissure, the septum, the lateral and medial pallia, the striatum, the nucleus of the postoptic commissure, the thalamus, the hypothalamus, and pretectal areas, the optic tectum, the torus semicircularis, the mesencephalic tegmentum, restricted regions of the rhombencephalic tegmentum, the octavolateral area, and the dorsal column nucleus. The GABA distribution found in cyclostomes is very similar to that of other classes of vertebrates, including mammals. Since the lamprey diverged from the main vertebrate line around 450 million years ago, this implies that already at that time the basic vertebrate plan for the GABA innervation in different parts of the brain had been developed. J. Comp. Neurol. 503:47–63, 2007. © 2007 Wiley‐Liss, Inc.