bluuebunny/crossref_metadata_2025 huggingface dataset:
On Tests for Correlated Proportions in the Presence of Incomplete Data
Authors: Gokhale D. V. , Sirtonik B. W.
Published: January 2006

This paper proposes test statistics based on the likelihood ratio principle for testing equality of proportions in correlated data with additional incomplete samples. Powers of these tests are compared through Monte Carlo simulation with those of tests proposed recently by Ekbohm (based on an unbiased estimator) and Campbell (based on a Pearson-Chi-squared type statistic). Even though tests based on the maximum likelihood principle are theoretically expected to be superior to others, at least asymptotically, results from our simulations show that the gain in power could only be slight.
A Reformulation of the General Euclidean Model for the External Analysis of Preference Data
Authors: Davison Mark L.
Published: January 2006

This paper discusses least squares methods for fitting a reformulation of the general Euclidean model for the external analysis of preference data. The reformulated subject weights refer to a common set of reference vectors for all subjects and hence are comparable across subjects. If the rotation of the stimulus space is fixed, the subject weight estimates in the model are uniquely determined. Weight estimates can be guaranteed nonnegative. While the reformulation is a metric model for single stimulus data, the paper briefly discusses extensions to nonmetric, pairwise, and logistic models. The reformulated model is less general than Carroll's earlier formulation.
Sample Size Determinations for the Two Rater Kappa Statistic
Authors: Flack V. F. , Afifi A. A. , Lachenbruch P. A. , Schouten H. J. A.
Published: January 2006

This paper gives a method for determining a sample size that will achieve a prespecified bound on confidence interval width for the interrater agreement measure, κ. The same results can be used when a prespecified power is desired for testing hypotheses about the value of kappa. An example from the literature is used to illustrate the methods proposed here.
Bug Distribution and Statistical Pattern Classification
Authors: Tatsuoka Kikumi K. , Tatsuoka Maurice M.
Published: January 2006

A model (called the rule space model) which permits measuring cognitive skill acquisition, diagnosing cognitive errors, detecting the weaknesses and strengths of knowledge possessed by individuals was introduced earlier. This study further discusses the theoretical foundation of the model by introducing “bug distribution” and hypothesis testing (Bayes' decision rules for minimum errors) for classifying subjects into their most plausible latent state of knowledge. The model is illustrated with the domain of fraction arithmetic and compared with the results obtained from a conventional artificial intelligence approach.
The Statistical Analysis of General Processing Tree Models with the EM Algorithm
Authors: Hu Xiangen , Batchelder William H.
Published: January 2006

Multinomial processing tree models assume that an observed behavior category can arise from one or more processing sequences represented as branches in a tree. These models form a subclass of parametric, multinomial models, and they provide a substantively motivated alternative to loglinear models. We consider the usual case where branch probabilities are products of nonnegative integer powers in the parameters, 0≤θs≤1, and their complements, 1 - θs. A version of the EM algorithm is constructed that has very strong properties. First, the E-step and the M-step are both analytic and computationally easy; therefore, a fast PC program can be constructed for obtaining MLEs for large numbers of parameters. Second, a closed form expression for the observed Fisher information matrix is obtained for the entire class. Third, it is proved that the algorithm necessarily converges to a local maximum, and this is a stronger result than for the exponential family as a whole. Fourth, we show how the algorithm can handle quite general hypothesis tests concerning restrictions on the model parameters. Fifth, we extend the algorithm to handle the Read and Cressie power divergence family of goodness-of-fit statistics. The paper includes an example to illustrate some of these results.
A Modification of Feldt's Test of the Equality of Two Dependent Alpha Coefficients
Authors: Alsawalmeh Yousef M. , Feldt Leonard S.
Published: January 2006

The available statistical tests of the equality of nonindependent alpha reliability coefficients require that the product of the number of test parts times the number of subjects be quite large—1000 or more. A modification of one of these tests is derived which avoids this limitation. Monte Carlo studies indicate that the modified test effectively controls the Type I error rate with as few as 2 or 3 test parts and 50 subjects. This means the modified test can be safely employed in comparisons between interrater reliabilities.
Optimal Sequential Designs for On-line Item Estimation
Authors: Jones Douglas H. , Jin Zhiying
Published: January 2006

Replenishing item pools for on-line ability testing requires innovative and efficient data collection designs. By generating local D-optimal designs for selecting individual examinees, and consistently estimating item parameters in the presence of error in the design points, sequential procedures are efficient for on-line item calibration. The estimating error in the on-line ability values is accounted for with an item parameter estimate studied by Stefanski and Carroll. Locally D-optimal n-point designs are derived using the branch-and-bound algorithm of Welch. In simulations, the overall sequential designs appear to be considerably more efficient than random seeding of items.
Some Neglected Problems in IRT
Authors: Fischer Gerhard H.
Published: January 2006

The paper addresses three neglected questions from IRT. In section 1, the properties of the “measurement” of ability or trait parameters and item difficulty parameters in the Rasch model are discussed. It is shown that the solution to this problem is rather complex and depends both on general assumptions about properties of the item response functions and on assumptions about the available item universe. Section 2 deals with the measurement of individual change or “modifiability” based on a Rasch test. A conditional likelihood approach is presented that yields (a) an ML estimator of modifiability for given item parameters, (b) allows one to test hypotheses about change by means of a Clopper-Pearson confidence interval for the modifiability parameter, or (c) to estimate modifiability jointly with the item parameters. Uniqueness results for all three methods are also presented. In section 3, the Mantel-Haenszel method for detecting DIF is discussed under a novel perspective: What is the most general framework within which the Mantel-Haenszel method correctly detects DIF of a studied item? The answer is that this is a 2PL model where, however, all discrimination parameters are known and the studied item has the same discrimination in both populations. Since these requirements would hardly be satisfied in practical applications, the case of constant discrimination parameters, that is, the Rasch model, is the only realistic framework. A simple Pearson x2 test for DIF of one studied item is proposed as an alternative to the Mantel-Haenszel test; moreover, this test is generalized to the case of two items simultaneously studied for DIF.
The Approximation of Two-Mode Proximity Matrices by Sums of Order-Constrained Matrices
Authors: Hubert Lawrence , Arabie Phipps
Published: January 2006

A least-squares strategy is proposed for representing a two-mode proximity matrix as an approximate sum of a small number of matrices that satisfy certain simple order constraints on their entries. The primary class of constraints considered define Q-forms (or anti-Q-forms) for a two-mode matrix, where after suitable and separate row and column reorderings, the entries within each row and within each column are nondecreasing (or nonincreasing) to a maximum (or minimum) and thereafter nonincreasing (or nondecreasing). Several other types of order constraints are also mentioned to show how alternative structures can be considered using the same computational strategy.
An Efficient Algorithm for Joint Correspondence Analysis
Authors: Boik Robert J.
Published: January 2006

Joint correspondence analysis is a technique for constructing reduced-dimensional representations of pairwise relationships among categorical variables. The technique was proposed by Greenacre as an alternative to multiple correspondence analysis. Joint correspondence analysis differs from multiple correspondence analysis in that it focuses solely on between-variable relationships. Greenacre described one alternating least-squares algorithm for conducting joint correspondence analysis. Another alternating least-squares algorithm is described in this article. The algorithm is guaranteed to converge, and does so in fewer iterations than does the algorithm proposed by Greenacre. A modification of the algorithm for handling Heywood cases is described. The algorithm is illustrated on two data sets.
Latent Change in Recurrent Choice Data
Authors: Böckenholt Ulf , Langeheine Rolf
Published: January 2006

This paper introduces dynamic latent-class models for the analysis and interpretation of stability and change in recurrent choice data. These latent-class models provide a nonparametric representation of individual taste differences. Changes in preferences are modeled by allowing for individual-level transitions from one latent class to another over time. The most general model facilitates a saturated representation of class membership changes. Several special cases are presented to obtain a parsimonious description of latent change mechanisms. An easy to implement EM algorithm is derived for parameter estimation. The approach is illustrated by a detailed analysis of a purchase incidence data set.
Application of Model-Selection Criteria to Some Problems in Multivariate Analysis
Authors: Sclove Stanley L.
Published: January 2006

A review of model-selection criteria is presented, with a view toward showing their similarities. It is suggested that some problems treated by sequences of hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Consideration is given to application of model-selection criteria to some problems of multivariate analysis, especially the clustering of variables, factor analysis and, more generally, describing a complex of variables.
A Similarity-Based Smoothing Approach to Nondimensional Item Analysis
Authors: Ramsay J. O.
Published: January 2006

The probability that an examinee chooses a particular option within an item is estimated by averaging over the responses to that item of examinees with similar response patterns for the whole test. The approach does not presume any latent variable structure or any dimensionality. But simulated and actual data analyses are presented to show that when the responses are determined by a latent ability variable, this similarity-based smoothing procedure can reveal the dimensionality of ability very satisfactorily.
A General Linear Model for Estimating Effect Size in the Presence of Publication Bias
Authors: Vevea Jack L. , Hedges Larry V.
Published: January 2006

When the process of publication favors studies with small p-values, and hence large effect estimates, combined estimates from many studies may be biased. This paper describes a model for estimation of effect size when there is selection based on one-tailed p-values. The model employs the method of maximum likelihood in the context of a mixed (fixed and random) effects general linear model for effect sizes. It offers a test for the presence of publication bias, and corrected estimates of the parameters of the linear model for effect magnitude. The model is illustrated using a well-known data set on the benefits of psychotherapy.
Testing the Assumptions Underlying Tetrachoric Correlations
Authors: Muthén Bengt , Hofacker Charles
Published: January 2006

A method is proposed for empirically testing the appropriateness of using tetrachoric correlations for a set of dichotomous variables. Trivariate marginal information is used to get a set of one-degree of freedom chi-square tests of the underlying normality. It is argued that such tests should preferrably preceed further modeling of tetrachorics, for example, modeling by factor analysis. The assumptions are tested in some real and simulated data.
Explicit Candecomp/Parafac Solutions for a Contrived 2 × 2 × 2 Array of Rank Three
Authors: ten Berge Jos M. F. , Kiers Henk A. L. , de Leeuw Jan
Published: January 2006

Kruskal, Harshman and Lundy have contrived a special 2 × 2 × 2 array to examine formal properties of degenerate Candecomp/Parafac solutions. It is shown that for this array the Candecomp/Parafac loss has an infimum of 1. In addition, the array will be used to challenge the tradition of fitting Indscal and related models by means of the Candecomp/Parafac process.
The Irrelevance of Distributional Assumptions on Reaction Times in Multidimensional Scaling of Same/Different Judgment Tasks
Authors: Storms Gert , Delbeke Luc
Published: January 2006

Takane and Sergent developed a model (MAXRT) for scaling same/different judgments and response times (RTs) simultaneously. The model assumes that RTs are distributed lognormally. Our experiment showed that the RT distribution of the judgments might be task dependent. It is shown that lognormal RTs provide a far better fit than exponential, normal, and Pareto distributed RTs (with the same means and variances), but that the final parameter estimates from the data set with lognormal RTs hardly differ from the alternatively distributed RTs. Finally, despite the robustness of the distributional assumption of the RTs with respect to the parameter estimates, it is shown that RTs have an informational value that is not contained in the same/different judgments alone.
Further Remarks on Nondichotomization of Graded Responses
Authors: Andrich David
Published: January 2006

In addition to addressing the points raised in Roskam (1995) as a rejoinder to Andrich (1995), these further remarks on the nondichotomization of graded responses attempt to clarify the difference in perspective between the two articles that gives rise to the different appreciation of what appear to be the same details. Therefore, these remarks take the following form: first, a brief comment is made on the development of the argument and perspective against routine dichotomization of graded responses (which is often seen as no more than commonsense); second, some points raised in the rejoinder are reexamined and clarified from this perspective; third, the perspective is consolidated with examples to show the way in which nondichotomization of graded responses is consistent with intuition. Roskam (1995) and Andrich (1995) are referred to, respectively, as the rejoinder and the paper.
EM and Beyond
Authors: Rubin Donald B.
Published: January 2006

The basic theme of the EM algorithm, to repeatedly use complete-data methods to solve incomplete data problems, is also a theme of several more recent statistical techniques. These techniques—multiple imputation, data augmentation, stochastic relaxation, and sampling importance resampling—combine simulation techniques with complete-data methods to attack problems that are difficult or impossible for EM.
Some Relationships between the Information Function of IRT and the Signal/Noise Ratio and Reliability Coefficient of Classical Test Theory
Authors: Nicewander W. Alan
Published: January 2006

It is shown that IRTs information function for an item is functionally related to “local” versions of classical test theories' signal/noise ratio and reliability coefficient.
Testing Whether Independent Treatment Groups have Equal Medians
Authors: Wilcox Rand R.
Published: January 2006

The paper suggests new methods for comparing the medians corresponding to independent treatment groups. The procedures are based on the Harrell-Davis estimator in conjunction with a slight modification and extension of the bootstrap calibration technique suggested by Loh. Alternatives to the Harrell-Davis estimator are briefly discussed. For the special case of two treatment groups, the proposed procedure always had more power than the Fligner-Rust solution, as well as the procedure examined by Wilcox and Charlin. Included is an illustration, using real data, that comparing medians, rather than means, can yield a substantially different conclusion as to whether two distributions differ in terms of some measure of central location.
Constructing the Exact Significance Level for a Person Fit Statistic
Authors: Liou Michelle , Chang Chih-Hsin
Published: January 2006

This paper uses an extension of the network algorithm originally introduced by Mehta and Patel to construct exact tail probabilities for testing the general hypothesis that item responses are distributed according to the Rasch model. By assuming that item difficulties are known, the algorithm is applicable to the statistical tests either given the maximum likelihood ability estimate or conditioned on the total score. A simulation study indicates that the network algorithm is an efficient tool for computing the significance level of a person fit statistic based on test lengths of 30 items or less.
Influence in Canonical Correlation Analysis
Authors: Romanazzi Mario
Published: January 2006

The perturbation theory of the generalized eigenproblem is used to derive influence functions of each squared canonical correlation coefficient and the corresponding canonical vector pair. Three sample versions of these functions are described and some properties are noted. As particular applications, the influence function of the squared multiple correlation coefficient and influence functions of eigenvalues and eigenvectors in correspondence analysis are obtained. Three numerical examples are briefly discussed.
Comparing the Variances of Dependent Groups
Authors: Wilcox Rand R.
Published: January 2006

Recently several new attempts have been made to find a robust method for comparing the variances of J dependent random variables. However, empirical studies have shown that all of these procedures can give unsatisfactory results. This paper examines several new procedures that are derived heuristically. One of these procedures was found to perform better than all of the robust procedures studied here, and so it is recommended for general use.
Conditional Covariance Structure of Generalized Compensatory Multidimensional Items
Authors: Zhang Jinming , Stout William
Published: January 2006

Some nonparametric dimensionality assessment procedures, such as DIMTEST and DETECT, use nonparametric estimates of item pair conditional covariances given an appropriately chosen subtest score as their basic building blocks. Such conditional covariances given some subtest score can be regarded as an approximation to the conditional covariances given an appropriately chosen unidimensional latent composite, where the composite is oriented in the multidimensional test space direction in which the subtest score measures best. In this paper, the structure and properties of such item pair conditional covariances given a unidimensional latent composite are thoroughly investigated, assuming a semiparametric IRT modeling framework called a generalized compensatory model. It is shown that such conditional covariances are highly informative about the multidimensionality structure of a test. The theory developed here is very useful in establishing properties of dimensionality assessment procedures, current and yet to be developed, that are based upon estimating such conditional covariances.

In particular, the new theory is used to justify the DIMTEST procedure. Because of the importance of conditional covariance estimation, a new bias reducing approach is presented. A byproduct of likely independent importance beyond the study of conditional covariances is a rigorous score information based definition of an item's and a score's direction of best measurement in the multidimensional test space.
Finite Mixtures in Confirmatory Factor-Analysis Models
Authors: Yung Yiu-Fai
Published: January 2006

In this paper, various types of finite mixtures of confirmatory factor-analysis models are proposed for handling data heterogeneity. Under the proposed mixture approach, observations are assumed to be drawn from mixtures of distinct confirmatory factor-analysis models. But each observation does not need to be identified to a particular model prior to model fitting. Several classes of mixture models are proposed. These models differ by their unique representations of data heterogeneity. Three different sampling schemes for these mixture models are distinguished. A mixed type of the these three sampling schemes is considered throughout this article. The proposed mixture approach reduces to regular multiple-group confirmatory factor-analysis under a restrictive sampling scheme, in which the structural equation model for each observation is assumed to be known. By assuming a mixture of multivariate normals for the data, maximum likelihood estimation using the EM (Expectation-Maximization) algorithm and the AS (Approximate-Scoring) method are developed, respectively. Some mixture models were fitted to a real data set for illustrating the application of the theory. Although the EM algorithm and the AS method gave similar sets of parameter estimates, the AS method was found computationally more efficient than the EM algorithm. Some comments on applying the mixture approach to structural equation modeling are made.
On Holland's Dutch Identity Conjecture
Authors: Zhang Jinming , Stout William
Published: January 2006

The manifest probabilities of observed examinee response patterns resulting from marginalization with respect to the latent ability distribution produce the marginal likelihood function in item response theory. Under the conditions that the posterior distribution of examinee ability given some test response pattern is normal and the item logit functions are linear, Holland (1990a) gives a quadratic form for the log-manifest probabilities by using the Dutch Identity. Further, Holland conjectures that this special quadratic form is a limiting one for all “smooth” unidimensional item response models as test length tends to infinity. The purpose of this paper is to give three counterexamples to demonstrate that Holland's Dutch Identity conjecture does not hold in general. The counterexamples suggest that only under strong assumptions can it be true that the limits of log-manifest probabilities are quadratic. Three propositions giving sets of such strong conditions are given.
Generating Items During Testing: Psychometric Issues and Models
Authors: Embretson Susan E.
Published: January 2006

On-line item generation is becoming increasingly feasible for many cognitive tests. Item generation seemingly conflicts with the well established principle of measuring persons from items with known psychometric properties. This paper examines psychometric principles and models required for measurement from on-line item generation. Three psychometric issues are elaborated for item generation. First, design principles to generate items are considered. A cognitive design system approach is elaborated and then illustrated with an application to a test of abstract reasoning. Second, psychometric models for calibrating generating principles, rather than specific items, are required. Existing item response theory (IRT) models are reviewed and a new IRT model that includes the impact on item discrimination, as well as difficulty, is developed. Third, the impact of item parameter uncertainty on person estimates is considered. Results from both fixed content and adaptive testing are presented.
A Simple Multivariate Probabilistic Model for Preferential and Triadic Choices
Authors: Mullen Kenneth , Ennis Daniel M.
Published: January 2006

Multidimensional probabilistic models of behavior following similarity and choice judgements have proven to be useful in representing multidimensional percepts in Euclidean and non-Euclidean spaces. With few exceptions, these models are generally computationally intense because they often require numerical work with multiple integrals. This paper focuses attention on a particularly general triad and preferential choice model previously requiring the numerical evaluation of a 2n-fold integral, where n is the number of elements in the vectors representing the psychological magnitudes. Transforming this model to an indefinite quadratic form leads to a single integral. The significance of this form to multidimensional scaling and computational efficiency is discussed.
Maximizing the Coefficient of Generalizability under the Constraint of Limited Resources
Authors: Sanders P. F. , Theunissen T. J. J. M. , Baas S. M.
Published: January 2006

A procedure for maximizing the coefficient of generalizability under the constraint of limited resources is presented. The procedure uses optimization techniques that offer an investigator or test constructor the possibility of employing practical constraints. The procedure is illustrated for the two-facet random-model crossed design.
Multiclus: A New Method for Simultaneously Performing Multidimensional Scaling and Cluster Analysis
Authors: DeSarbo Wayne S. , Howard Daniel J. , Jedidi Kamel
Published: January 2006

This paper develops a maximum likelihood based method for simultaneously performing multidimensional scaling and cluster analysis on two-way dominance or profile data. This MULTICLUS procedure utilizes mixtures of multivariate conditional normal distributions to estimate a joint space of stimulus coordinates and K vectors, one for each cluster or group, in a T-dimensional space. The conditional mixture, maximum likelihood method is introduced together with an E-M algorithm for parameter estimation. A Monte Carlo analysis is presented to investigate the performance of the algorithm as a number of data, parameter, and error factors are experimentally manipulated. Finally, a consumer psychology application is discussed involving consumer expertise/experience with microcomputers.
Rasch-Representable Reaction Time Distributions
Authors: Vorberg Dirk , Schwarz Wolfgang
Published: January 2006

This article investigates properties of a representation based on the Rasch test model for reaction times (RT) that was proposed by Micko. Necessary and sufficient conditions for a set of RT distributions to be Rasch-representable are derived. It is shown that independent serial and independent parallel processing models cannot be reconciled with the representation. However, random extreme models compatible with the Reasch-representation exist that assume RT is determined by the longest or he shortest processing time of a random number of independent paraloel channels. Nonparametric properties of Rasch-representable distributions are derived that can be used for testing the model and for estimating its parameters. Conditions are presented for Rasch-representable distributions to form a scale family. Finally, Rasch-represent-able distributions are characterized interms of their hazard functions.
Model Modification
Authors: Sörbom Dag
Published: January 2006

An analysis of empirical data often leads to a rejection of a hypothesized model, even if the researcher has spent considerable efforts in including all available information in the formulation of the model. Thus, the researcher must reformulate the model in some way, but in most instances there is, at least theoretically, an overwhelming number of possible actions that could be taken. In this paper a “modification index” will be discussed which should serve as a guide in the search for a “better” model. In statistical terms, the index measures how much we will be able to reduce the discrepancy between model and data, as defined by a general fit function, when one parameter is added or freed or when one equality constraint is relaxed. The modification index discussed in this paper is an improvement of the one incorporated in the LISREL V computer program in that it takes into account changes in all the parameters of the model when one particular parameter is freed.
An Alternating Least Squares Algorithm for Fitting the Two- and Three-Way Dedicom Model and the Idioscal Model
Authors: Kiers Henk A. L.
Published: January 2006

The DEDICOM model is a model for representing asymmetric relations among a set of objects by means of a set of coordinates for the objects on a limited number of dimensions. The present paper offers an alternating least squares algorithm for fitting the DEDICOM model. The model can be generalized to represent any number of sets of relations among the same set of objects. An algorithm for fitting this three-way DEDICOM model is provided as well. Based on the algorithm for the three-way DEDICOM model an algorithm is developed for fitting the IDIOSCAL model in the least squares sense.
Separability of Item and Person Parameters in Response Time Models
Authors: Van Breukelen Gerard J. P.
Published: January 2006

This paper discusses two forms of separability of item and person parameters in the context of response time (RT) models. The first is “separate sufficiency”: the existence of sufficient statistics for the item (person) parameters that do not depend on the person (item) parameters. The second is “ranking independence”: the likelihood of the item (person) ranking with respect to RTs does not depend on the person (item) parameters. For each form a theorem stating sufficient conditions, is proved. The two forms of separability are shown to include several (special cases of) models from psychometric and biometric literature. Ranking independence imposes no restrictions on the general distribution form, but on its parametrization. An estimation procedure based upon ranks and pseudolikelihood theory is discussed, as well as the relation of ranking independence to the concept of double monotonicity.
A Maximum Likelihood Method for Latent Class Regression Involving a Censored Dependent Variable
Authors: Jedidi Kamel , Ramaswamy Venkatram , Desarbo Wayne S.
Published: January 2006

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.
Estimating Latent Distributions in Recurrent Choice Data
Authors: Böckenholt Ulf
Published: January 2006

This paper introduces a flexible class of stochastic mixture models for the analysis and interpretation of individual differences in recurrent choice and other types of count data. These choice models are derived by specifying elements of the choice process at the individual level. Probability distributions are introduced to describe variations in the choice process among individuals and to obtain a representation of the aggregate choice behavior. Due to the explicit consideration of random effect sources, the choice models are parsimonious and readily interpretable. An easy to implement EM algorithm is presented for parameter estimation. Two applications illustrate the proposed approach.
On the Base-Free Measure of Change Proposed by Tucker, Damarin and Messick
Authors: Bond Lloyd
Published: January 2006

Tucker, Damarin and Messick proposed a “base-free” measure of change which involves the computation of residual scores that are uncorrelated with true scores on the pretest. The present note discusses this change measure and demonstrates that, because of an incorrect derivation by the authors, properties they attribute to α (the coefficient for the regression of true scores from the second testing on true scores from the first testing) are, in fact, properties of b, the ordinary regression coefficient. A correct derivation of the initial position—change correlation in terms of α is obtained, and Tucker et al.'s discussion of the “law of initial values” is reconsidered.
Latent Curve Analysis
Authors: Meredith William , Tisak John
Published: January 2006

As a method for representing development, latent trait theory is presented in terms of a statistical model containing individual parameters and a structure on both the first and second moments of the random variables reflecting growth. Maximum likelihood parameter estimates and associated asymptotic tests follow directly. These procedures may be viewed as an alternative to standard repeated measures ANOVA and to first-order auto-regressive methods. As formulated, the model encompasses cohort sequential designs and allow for period or practice effects. A numerical illustration using data initially collected by Nesselroade and Baltes is presented.
Inferential Procedures for Multifaceted Coefficients of Generalizability
Authors: Schroeder Marsha L. , Ralph Hakstian A.
Published: January 2006

A two-facet measurement model with broad application in the behavioral sciences is identified, and its coefficient of generalizability (CG) is examined. A normalizing transformation is proposed, and an asymptotic variance expression is derived. Three other multifaceted measurement models and CGs are identified, and variance expressions are presented. Next, an empirical investigation of the procedures follows, and it is shown that, in most cases, Type I error control in inferential applications is precise, and that the estimates are relatively efficient compared with the correlation coefficient. Implications for further research and for practice are noted. In an Appendix, four additional models, CGs, and variance expressions are presented.
Easy Bayes Estimation for Rasch-Type Models
Authors: Jannarone Robert J. , Yu Kai F. , Laughlin James E.
Published: January 2006

A Bayes estimation procedure is introduced that allows the nature and strength of prior beliefs to be easily specified and modal posterior estimates to be obtained as easily as maximum likelihood estimates. The procedure is based on constructing posterior distributions that are formally identical to likelihoods, but are based on sampled data as well as artificial data reflecting prior information. Improvements in performance of modal Bayes procedures relative to maximum likelihood estimation are illustrated for Rasch-type models. Improvements range from modest to dramatic, depending on the model and the number of items being considered.
Applying the Principles of Specific Objectivity and of Generalizability to the Measurement of Change
Authors: Fischer Gerhard H.
Published: January 2006

A formal framework for measuring change in sets of dichotomous data is developed and implications of the principle of specific objectivity of results within this framework are investigated. Building upon the concept of specific objectivity as introduced by G. Rasch, three equivalent formal definitions of that postulate are given, and it is shown that they lead to latent additivity of the parametric structure. If, in addition, the observations are assumed to be locally independent realizations of Bernoulli variables, a family of models follows necessarily which are isomorphic to a logistic model with additive parameters, determining an interval scale for latent trait measurement and a ratio scale for quantifying change. Adding the further assumption of generalizability over subsets of items from a given universe yields a logistic model which allows a multidimensional description of individual differences and a quantitative assessment of treatment effects; as a special case, a unidimensional parameterization is introduced also and a unidimensional latent trait model for change is derived. As a side result, the relationship between specific objectivity and additive conjoint measurement is clarified.
An Extension of the Partial Credit Model with an Application to the Measurement of Change
Authors: Fischer Gerhard H. , Ponocny Ivo
Published: January 2006

The partial credit model is considered under the assumption of a certain linear decomposition of the item × category parameters δih into “basic parameters” αj. This model is referred to as the “linear partial credit model”. A conditional maximum likelihood algorithm for estimation of the αj is presented, based on (a) recurrences for the combinatorial functions involved, and (b) using a “quasi-Newton” approach, the so-called Broyden-Fletcher-Goldfarb-Shanno (BFGS) method; (a) guarantees numerically stable results, (b) avoids the direct computation of the Hesse matrix, yet produces a sequence of certain positive definite matrices Bk, k = 1, 2, ..., converging to the asymptotic variance-covariance matrix of the \documentclass[12pt]{minimal}
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\end{document}. The practicality of these numerical methods is demonstrated both by means of simulations and of an empirical application to the measurement of treatment effects in patients with psychosomatic disorders.
Some Clarifications of the TUCKALS2 Algorithm Applied to the IDIOSCAL Problem
Authors: ten Berge Jos M. F. , Bekker Paul A. , Kiers Henk A. L.
Published: January 2006

Kroonenberg and de Leeuw have suggested fitting the IDIOSCAL model by the TUCKALS2 algorithm for three-way components analysis. In theory, this is problematic because TUCKALS2 produces two possibly different coordinate matrices, that are useless for IDIOSCAL unless they are equal. Kroonenberg has claimed that, when IDIOSCAL is fitted by TUCKALS2, the resulting coordinate matrices will be identical. In the present paper, this claim is proven valid when the data matrices are semidefinite. However, counterexamples for indefinite matrices are also constructed, by examining the global minimum in the case where the data matrices have the same eigenvectors. Similar counterexamples have been considered by ten Berge and Kiers in the related context of CANDECOMP/PARAFAC to fit the INDSCAL model.
An Inequality between the Weighted Average and the Rowwise Correlation Coefficient for Proximity Matrices
Authors: Krijnen Wim P.
Published: January 2006

De Vries (1993) discusses Pearson's product-moment correlation, Spearman's rank correlation, and Kendall's rank-correlation coefficient for assessing the association between the rows of two proximity matrices. For each of these he introduces a weighted average variant and a rowwise variant. In this note it is shown that for all three types, the absolute value of the first variant is greater than or equal to the absolute value of the second.
Glycerol kinase deficiency presenting with hypodipsia, osmotic diuresis and severe hypernatraemia
Authors: Mak T. W. L. , Wong L. M. , Wong S. N. , Tse K. , Lai J. P. S.
Published: January 2006

A Chinese boy with glycerol kinase deficiency is reported. His presentation with severe hypernatraemia secondary to hypodipsia and glycerol‐induced osmotic diuresis is unusual and not previously described in the literature.
Decreased plasma concentration of von Willebrand factor antigen (VWF:Ag) in patients with glycogen storage disease type Ia
Authors: MÜHlhausen C. , Schneppenheim R. , Budde U. , Merkel M. , Muschol N. , Ullrich K. , Santer R.
Published: January 2006

Despite highly increased blood lipids, patients with glycogen storage disease type Ia (GSD Ia) do not develop premature vascular complications. Since this could be due to changes of coagulation factors, coagulation tests (including von Willebrand factor (VWF) antigen (VWF:Ag) ELISA, VWF:collagen binding activity (VWF:CB) and VWF multimer analysis) were performed in 10 GSD Ia patients, single cases of other GSD types, and in both healthy and hyperlipidaemic controls. In 60% of GSD Ia patients we found abnormal results, with a decrease of VWF:Ag and multimer analysis showing reduced intensity of individual oligomers in the presence of all multimers with a normal triplet structure. We interpret these findings as an aquired ‘von Willebrand syndrome type I’ in GSD Ia. The underlying metabolic mechanism and a potential role in the protection from vascular complication still needs to be evaluated.
S‐Adenosylhomocysteine hydrolase deficiency: A second patient, the younger brother of the index patient, and outcomes during therapy
Authors: Barić I. , Ćuk M. , Fumić K. , Vugrek O. , Allen R. H. , Glenn B. , Maradin M. , Pažanin L. , Pogribny I. , Radoš M. , Sarnavka V. , Schulze A. , Stabler S. , Wagner C. , Zeisel S. H. , Mudd S. H.
Published: January 2006

S‐Adenosylhomocysteine (AdoHcy) hydrolase deficiency has been proven in a human only once, in a recently described Croatian boy. Here we report the clinical course and biochemical abnormalities of the younger brother of this proband. This younger brother has the same two mutations in the gene encoding AdoHcy hydrolase, and has been monitored since birth. We report, as well, outcomes during therapy for both patients. The information obtained suggests that the disease starts in utero and is characterized primarily by neuromuscular symptomatology (hypotonia, sluggishness, psychomotor delay, absent tendon reflexes, delayed myelination). The laboratory abnormalities are markedly increased creatine kinase and elevated aminotransferases, as well as specific amino acid aberrations that pinpoint the aetiology. The latter include, most importantly, markedly elevated plasma AdoHcy. Plasma S‐adenosylmethionine (AdoMet) is also elevated, as is methionine (although the hypermethioninaemia may be absent or nonsignificant in the first weeks of life). The disease seems to be at least to some extent treatable, as shown by improved myelination and psychomotor development during dietary methionine restriction and supplementation with creatine and phosphatidylcholine.
Mucopolysaccharidosis I: α‐L‐Iduronidase mutations in three Tunisian families
Authors: Laradi S. , Tukel T. , Erazo M. , Shabbeer J. , Chkioua L. , Khedhiri S. , Ferchichi S. , Chaabouni M. , Miled A. , Desnick R. J.
Published: January 2006

Mucopolysaccharidosis type I (MPS I) is a lysosomal storage disease resulting from the defective activity of the enzyme α‐L‐iduronidase (IDUA). The disease has severe and milder phenotypic subtypes. The IDUA mutations in five MPS I patients from three unrelated families from central and southern Tunisia were determined by amplifying and sequencing each of the IDUA exons and intron–exon junctions. Two novel IDUA mutations, c.1805delTinsGAACA in exon 13 and I270S in exon 7, and two previously reported mutations, P533R and R628X, were detected. The two patients in family 1 who had the Hurler phenotype were homoallelic for the novel deletion‐insertion mutation. The patient in family 2 who also had the Hurler phenotype was heteroallelic for the novel missense mutation I270S and the previously reported nonsense mutation R628X. The two patients in family 3 who had the Hurler–Scheie phenotype were homoallelic for P533R. In addition, six known IDUA polymorphisms were identified. These are the first Tunisian MPS I patients to be genotyped. The identification of these mutations and their genotype–phenotype correlations should facilitate prenatal diagnosis and counselling for MPS I in Tunisia, where a very high rate of consanguinity exists.
Pressurisation of raw skim milk and of a dispersion of phosphocaseinate at 9 °C or 20 °C: effects on the distribution of minerals and proteins between colloidal and soluble phases
Authors: Regnault Stéphanie , Dumay Eliane , Cheftel Jean Claude
Published: January 2006

The effects of high pressure treatments (100–300 MPa; 15 min; 9 °C or 20 °C) on the distribution of minerals and proteins of raw skim milk (RSM) and of a dispersion of industrial phosphocaseinate (PC) were studied after separation of the micellar and soluble phases by ultracentrifugation (UCF). Whatever the temperature of high pressure treatments, the pressure-induced dissociation of the casein micelles was accompanied by calcium (Ca), phosphorus (P) and casein release from the micelles. The released Ca and P were or became bound to soluble proteins since progressive increases in Ca and P concentrations were observed in the UCF supernatants of RSM and of the PC dispersion but not in the ultrafiltrates from these UCF supernatants (free of soluble proteins). Simultaneously, αS1-, αS2-, β- and κ-caseins were progressively released from the micelles, as seen by electrophoretic analysis. The pressure-induced solubilisation of αS1- and αS2-caseins, essentially located in the core of the micelles, suggests that high pressure destabilised micelles including their internal structure.
Seroepidemiology of hepatitis A and hepatitis B virus in Luxembourg
Authors: MOSSONG J. , PUTZ L. , PATINY S. , SCHNEIDER F.
Published: January 2006

A prospective seroepidemiological survey was carried out in Luxembourg in 2000–2001 to determine the antibody status of the Luxembourg population against hepatitis A virus (HAV) and hepatitis B virus (HBV). One of the objectives of this survey was to assess the impact of the hepatitis B vaccination programme, which started in May 1996 and included a catch-up campaign for all adolescents aged 12–15 years. Venous blood from 2679 individuals was screened for the presence of antibodies to HAV antigen and antibodies to hepatitis B surface antigen (anti-HBs) using an enzyme immunoassay. Samples positive for anti-HBs were tested for antibody to hepatitis B core antigen (anti-HBc) using a chemiluminiscent microparticle immunoassay to distinguish between individuals with past exposure to vaccine or natural infection. The estimated age-standardized anti-HAV seroprevalence was 42·0% [95% confidence interval (CI) 39·8–44·1] in the population >4 years of age. Seroprevalence was age-dependent and highest in adult immigrants from Portugal and the former Yugoslavia. The age-standardized prevalence of anti-HBs and anti-HBc was estimated at 19·7% (95% CI 18·1–21·3) and 3·16% (95% CI 2·2–4·1) respectively. Anti-HBs seroprevalence exceeding 50% was found in the cohorts targeted by the routine hepatitis B vaccination programme, which started in 1996. Our study illustrates that most young people in Luxembourg are susceptible to HAV infection and that the hepatitis B vaccination programme is having a substantial impact on population immunity in children and teenagers.