bluuebunny/crossref_metadata_2025 huggingface dataset:
A METHOD FOR INVESTIGATING CHILDREN'S UNDERSTANDING OF CERTAIN LOGICAL CONNECTIVES USED IN BINARY PROPOSITIONAL THINKING
Authors: Peel E. A.
Published: August 2011

A theoretical frame of reference and an experimental method are described for investigating children's understanding of such logical connectives as If … then in certain binary propositions. A game is played with coloured beads and counters between experimenter and child which both obviates the need to use ‘naturally’ connected binary propositions and at the same time prevents the rejection of the propositions on account of their arbitrariness. The games consist essentially of a bead draw by the experimenter followed by a responding draw of a counter by the child, according to the instructions for each game.

The frequencies of different conjunctions of bead and counter draws (pq, where p and q are different kinds of beads and counters respectively) are obtained and converted to proportions. These proportions are compared with those expected theoretically according to the definitions of the main binary propositions.
NON‐PARAMETRIC TREND TESTS FOR LEARNING DATA
Authors: Jonckheere A. R. , Bower Gordon H.
Published: August 2011

Many current stochastic models of learning imply stationarity of portions of individual response sequences. Non‐parametric tests are presented for detecting overall group trend and homogeneity of individual trends in a sample of protocols. The protocols may differ in length and consist of any responses that take ordered values, such as errors and successes, ratings, or response latencies. The power of the test for overall group trend is discussed in relation to both linear and logistic alternatives.
A NOTE ON A GENERATING ASSUMPTION IN McGEE'S MULTIDIMENSIONAL ANALYSIS OF ‘ELASTIC’ DISTANCES
Authors: Gregson R. A. M. , Russell P. N.
Published: August 2011

Evidence is offered that multidimensional similarity judgements do not behave in a way demanded for an elastic distance model advanced by McGee. Problems concerning the properties of similarity data which can be included in scaling models are indicated.
A RETEST OF THE RESPONSE‐BIAS EXPLANATION OF THE WORD‐FREQUENCY EFFECT
Authors: Morton John
Published: August 2011

This paper investigates whether the relation between the frequency of occurrence of a word and its sensory threshold can properly be ascribed to response bias. Seven models for the recognition process are tested against data of Brown & Rubenstein (1961). The models are of two kinds: probabilistic single‐threshold models and information‐processing models. It is concluded that the data can only be accounted for within the former class of models by assuming a differential effect of the stimulus as well as response bias. For the class of information‐processing models, the data require the assumptions that there is equal sensitivity for words of all frequencies and a lower criterion for more common words. The relation between the two acceptable models makes it apparent that the notions of ‘stimulus effect’ and ‘response effect’ are by no means as clear as has previously been thought.
SIMULATING PERCEIVED SIMILARITIES BETWEEN TASTE MIXTURES HAVING MUTUALLY INTERACTING COMPONENTS
Authors: Gregson R. A. M.
Published: August 2011

Empirical findings about the perceived interaction of the components of qualitatively complex taste stimuli are reviewed and summarized. The revision of multidimensional scaling equations to incorporate a simulation of a mutually inhibitory or facilitatory interaction between components is discussed. Data from a previously published study on the perception of similarity among taste mixtures are re‐analysed for illustrative purposes and a description of them is shown to be less adequate when provision is made for one form of interaction than when this is omitted. A reclassification of stimulus‐response paradigms for studying taste mixture perception is outlined; and it is suggested that the interaction of taste components may be an artifact of the response measures used.
SLOW LEARNING
Authors: Norman M. Frank
Published: August 2011

Learning will be slow if the quantity that represents the state of learning changes by small steps or with small probability on each experimental trial. Approximations to the distribution of this quantity for both types of slow learning are obtained. These approximations are applicable to a wide variety of models.
THE STUDY OF HOSTILITY IN THE TEMPERAMENTS OF SPOUSES: DEFINITIONS AND METHODS
Authors: Hope K.
Published: August 2011

The nature of aggression or hostility is discussed, and the possible relations between hostility in the personalities of husbands and hostility in the personalities of wives are conceptualized under the heads: (a) Similarity in quantity of aggression; (b) Similarity in pattern of aggression; (c) Oppositeness or complementarity in quantity of aggression; (d) Oppositeness or complementarity in pattern of aggression; and (e) Systematic relations between similar or dissimilar (but not necessarily opposite) patterns of aggression. The first four possibilities are explored by imposing a model on questionnaire data obtained from alcoholics and their wives. The fifth possibility, which is the first to be dealt with, is investigated with the aid of a technique which follows the pattern of the data without imposing a model on them.

The analysis demonstrates that exclusive reliance on correlational methods, however complex, may obscure the essential features of a psychological situation. It also shows how the special characteristics of temperamental qualities may be accommodated by the construction of an appropriate model.
THE NORMAL SCORES TEST FOR THE c‐SAMPLE PROBLEM
Authors: McSweeney Maryellen , Penfield Douglas
Published: August 2011

Two forms of a c‐sample normal scores test are presented as alternatives to the Kruskal–Wallis test (KW). The normal scores test statistics and multiple comparison procedures are illustrated for large samples requiring a correction for tied observations. Theoretical and empirical evidence is cited in support of using the normal scores test in preference to a rank test such as the KW. The normal scores test is asymptotically more efficient than the KW for samples from common non‐normal populations (e.g. uniform and exponential) and is less sensitive to non‐normality and unequal variances than is either the F‐test or the KW test.
EXPERIMENTATION BY COMPUTER: SOME PRELIMINARY STEPS
Authors: Wolfendale G.
Published: August 2011

A computer system is described which carries out on‐line experiments involving m‐independent variables and one dependent variable. Using a search procedure that applies hillclimbing techniques, the system selectively places points in regions that demand them for reliable description. Some results of its performance are given in Section 3. The experimentation system leaves information in store and this is used by a model‐assessment procedure in order to achieve the optimum predictive efficiency for each of the functional models under consideration.

This study is part of a research project aimed at producing computer‐controlled experimentation which will not only assess functional models, but also generate them, assess and generate discrete or ‘structural’ models, and design and carry out experiments whose results will be essential for discrimination between models. The work is also intended as a contribution to the problem of computer program semantics.
SERIAL DEPENDENCY IN THE METHOD OF LIMITS
Authors: Speight L. R.
Published: August 2011

Empirical investigations suggest that dependency between successive responses in psychophysical experiments may not be uncommon. This paper puts forward a simple Markov model of response dependency. The constant method is briefly reviewed in the light of this model, and is shown to result in unbiased estimates of the psychophysical function. The method of limits is examined in more detail. Estimates of psychophysical function parameters obtained by this method, whether by averaging stopping‐point values or by conducting a probit analysis on the derived data, are shown to be a function of the inter‐stimulus interval chosen, the stopping criterion selected, and the degree of response dependency. However, bias is very small when stopping‐point averages are employed, provided that the inter‐stimulus interval is fairly large compared with the slope of the psychophysical function, and that use is made of a simple correction formula.
ESTIMATION AND TESTING OF SIMPLEX MODELS
Authors: Jöreskog Karl G.
Published: August 2011

Various statistical models for simplex structures are formulated in terms of the well‐known Wiener and Markov stochastic processes. A distinction is made between a perfect simplex and a quasi‐simplex. For each model the problems of identification and estimation of the parameters and that of testing the goodness of fit of the model are considered. All models may be estimated by a general method for covariance structures developed by Jöreskog (1970), but in some cases simpler methods may be used, in which case these are presented.
THE STATISTICAL DESCRIPTION OF POLARIZATION PHENOMENA IN SOCIETY†
Authors: Weidlich W.
Published: August 2011

Statistical models based on probability laws, and originally used for the description of the dynamic development of an ensemble of interacting spins, are reformulated in order to study the structure of social groups of individuals mutually influencing each other with respect to their decision behaviour. After a description of the general features of these models, and relating them to the polarization phenomena in society, a quantitative model is developed which can be compared with the decision behaviour of social groups.
INFORMATION CURVES AND EFFICIENCY OF THREE LOGISTIC TEST MODELS
Authors: Hambleton Ronald K. , Traub Ross E.
Published: August 2011

Our purpose was to determine the efficiency of the estimates of ability provided by the one‐parameter logistic model as compared to the estimates provided by the more general two‐ and three‐parameter models. Several tests were simulated with item parameters meeting the assumptions of either the two‐ or three‐parameter model. For each test, the information provided by ability estimates appropriate to the one‐, two‐ and three‐parameter models was compared at several ability levels. The results indicate that it is particularly important, when guessing affects test scores, to use the scoring system of the three‐parameter model for estimating the ability of low‐ability examinees.
MULTIVARIATE STATISTICAL INFERENCE UNDER MARGINAL STRUCTURE
Authors: Gleser Leon Jay , Olkin Ingram
Published: August 2011

Suppose that we are utilizing k different psychological tests, each having one subtest in common. Of particular concern is the hypothesis that these tests are parallel with respect to their means and/or covariances. A complete hierarchy of hypotheses for this situation has been developed. For example, Hm've is the hypothesis that the tests are parallel only with respect to the means of the common test, but with respect to the covariances of both tests. (The prime indicates equality for the common test only.) This hypothesis might be tested against Hvc, the hypothesis of parallelism with respect to the covariances. Other hypotheses considered are Hmvc, Hm'vc, Hm'vc and Hvc. Maximum‐likelihood estimators under the various models (and under the assumption of normally distributed test scores) have been obtained, as well as the related likelihood‐ratio statistics. Approximate distributions of the likelihood‐ratio statistics are worked out, so that the tests can be applied, and an example of their use is provided.
TESTS OF ASSOCIATION IN TERMS OF MATRIX ALGEBRA
Authors: Maxwell A. E.
Published: August 2011

Initially it is shown how the calculations involved in tests of association on contingency tables can be expressed in terms of matrix algebra. Several advantages which follow from doing so are then described and illustrated. The problem of estimating correlation coefficients between attributes which have truncated distributions is considered, and the paper concludes by comparing the results from two different populations.
ORTHOGONAL TRANSFORMATION TO HYPOTHESIZED FACTORS OF DIFFERENT ORDERS
Authors: Fee Francis
Published: August 2011

Two procedures are described for transforming an arbitrary factor matrix to accord with a target matrix which may imply higher order factors transposed to the first‐order realm. The first procedure derives a solution whose major product moment is identical with that of the arbitrary while the second procedure produces a solution which includes specific factors and reproduces the complete correlation matrix.
ANALYSIS OF EMPIRICAL DATA USING TWO LOGISTIC LATENT TRAIT MODELS
Authors: Hambleton Ronald K. , Traub Ross E.
Published: August 2011

Although Birnbaum's logistic models have been known since 1957, there have been few applications to empirical data reported in the literature. In this study, the one‐ and two‐parameter logistic models were compared with respect to their capacity to predict the distribution of statistics for estimating ability. The results of this study suggest that the two‐parameter model will provide greatest improvement over the one‐parameter model when applied to data from short tests where the variability of the discrimination parameters is substantial. Whether the gains are worth the increased cost of solving for the parameters of the more complex model is a question which requires investigation.
CANONICAL ANALYSIS IN SEVERAL POPULATIONS WITH PREDICTOR WEIGHTS CONSTRAINED ACROSS POPULATIONS
Authors: Frederiksen Carl H.
Published: August 2011

An extension of canonical analysis to several populations is considered in which, at each stage in the analysis, one set of canonical weights is constrained to be equivalent across the several populations. Estimation and hypothesis testing are discussed with respect to the first‐stage canonical variates, and an iterative procedure for obtaining an approximate solution for higher‐stage canonical variates is presented.
DETECTION OF CORRELATED ERRORS IN LONGITUDINAL DATA
Authors: Sörbom Dag
Published: August 2011

A study of change in ability between two occasions may employ a number of tests believed to measure the ability in question. Either the same battery of tests is used on both occasions, or equivalent forms are used. For a variety of reasons, correlations may exist between certain errors remaining after eliminating variance due to true scores, and hence the classical factor analysis model is not applicable. A procedure for detecting correlations between errors is discussed. A search strategy is proposed since, even if the number of observed variables is small, the number of possible models is very large. A computer program is described, which produces maximum‐likelihood estimates for the parameters in a factor analytic model in which the error variables may be correlated.
A NEW APPROACH TO THE CHARACTERIZATION OF SEQUENTIAL STRUCTURE IN MULTI‐TRIAL FREE RECALL USING HIERARCHICAL GROUPING ANALYSIS
Authors: Monk Andrew F.
Published: August 2011

Previous approaches to the assessment of subjective organization in multi‐trial free recall (MTFR) have depended upon the identification of sequential structure which is stable over two successive recall trials. While these techniques give adequate estimates of the degree of subjective organization they are incapable of revealing its content for two reasons. Firstly, the resultant characterizations contain considerable redundancy; and, secondly, they are highly susceptible to the operation of chance factors. The approach described in the present paper, hierarchical grouping analysis (HGA), appears to meet these criticisms. The possibilities extended by using HGA are demonstrated in an analysis of some experimental data which examines the relationship between semantic inter‐item associations and recall structure. Finally, the possibility of applying HGA in other domains is discussed.
A MONTE CARLO STUDY OF SOME ASYMMETRIC ASSOCIATION MEASURES
Authors: Särndal Carl Erik
Published: August 2011

Comparatively little research has been reported on the nature of the distributions of existing association measures. In this paper, a Monte Carlo study of the distributions of 12 asymmetric association measures is reported. The derived distributions, and in particular their basic properties such as mean, variance, skewness and closeness to normal shape, provide valuable guides as to the expected performance of each of the association measures, at a given level of theoretical association in the underlying population.
HARKING BACK TO ‘HARK‐BACK’: A PROOF OF A CONJECTURE OF GREEN & JACKSON
Authors: Clowes J. S. , Leach C.
Published: August 2011

A proof is offered of Green & Jackson's (1976) conjecture concerning the maximum value that their measure of hark‐back for search patterns can attain. Some of the properties of the measure are discussed.
On Bayesian formula scores for random guessing in multiple choice tests
Authors: Molenaar W.
Published: August 2011

Van der Ven (1974) identified defects of the classical formula score used to estimate the probability of chance success and the number of items on a multiple choice test for which the examinee truly knows the answer. He derived an estimator based upon the assumption of a uniform prior distribution for the number of known items. The present paper investigates properties of this estimator and compares it with the classical formula. More general models are presented of which the uniform prior is a special case. Further, it is shown that estimators of the prior distribution may be derived from the distribution of the total number of correct answers for a group of examinees. The fit of the models for some observed data is discussed.
Quasi‐F ratios for an unusual experimental design
Authors: Games Paul A.
Published: August 2011

An experimental design is described in which random subjects are nested under one fixed factor; random raters are nested under another fixed factor; and both sets are crossed. The expected mean squares under this unusual structure are reported, as are the quasi‐F ratios needed to test the interaction and the main effects of the fixed factors. Quasi‐ Fs are also reported for testing of simple effects, if needed.
Applications of combinatorial programming to data analysis: Seriation using asymmetric proximity measures
Authors: Baker Frank B. , Hubert Lawrence J.
Published: August 2011

Based on a given asymmetric proximity function, a two‐stage computational heuristic for sequencing a set of objects along a continuum is presented and illustrated with the type of example common in the paired‐comparison literature. The first stage, defined by the pairwise interchange of objects, is intended to generate reasonably good orderings from randomly chosen initial starts; the second stage can be considered to be a refinement phase and depends on a general condition for an optimal solution suggested by Younger involving the interchange of consecutively placed groups of objects. An extension of the heuristic is also described that allows the selection and sequencing of a subset of all the possible objects.
Tests are perfectly reliable
Authors: Lumsden J.
Published: August 2011

All test items are perfectly reliable. The unreliability of test scores results solely from person fluctuations. The theory implies that: (1) test length effects are a sampling phenomenon; (2) person reliabilities can be compared from person characteristic curves; (3) all ICC for a unidimensional test have the same slope; (4) ICC are not necessarily invariant from one group to another; and (5) reliabilities of groups can be compared from ICC.

A reliability coefficient of the theory is defined as the proportion of variance in obtained scores attributable to variance in average attribute level for subjects. Lower bounds for the classical reliability coefficient are also lower bounds for the new coefficient. Statistics calculated from this coefficient have no useful application.
Tests and contrasts for comparing change parameters for a multiple sample McNemar data model
Authors: Marascuilo Leonard A. , Serlin Ronald C.
Published: August 2011

The McNemar test of dichotomous change is extended to the case in which a researcher has two or more independent groups that are to be compared for identical change. Planned and post hoc comparison methods using contrasts for testing identity of change parameters are presented. The proposed procedures are illustrated for an attitude change study and are compared to other tests designed to examine no change across two or more groups. The methods illustrated permit a direct identification of significant pairwise differences, while the competing procedures are shown to terminate in an omnibus test of statistical significance.
Representation and uniqueness of the Bradley–Terry–Luce model for pair comparisons
Authors: Colonius Hans
Published: August 2011

The set of all formally equivalent Bradley–Terry–Luce models for pair comparison and uniqueness of their corresponding scales are characterized.
Modelling recall order in free recall experiments
Authors: Robertson Chris
Published: August 2011

A general Markov model for the order of recall of words in free recall experiments is described. This model is an extension to Cowan's (1966) original model. A restricted version of the general model which uses only categorical information is fitted to data and various hypotheses about the model parameters are tested. Finally modifications to the model are discussed.
Constrained latent class models: Theory and applications
Authors: Formann Anton K.
Published: August 2011

Three types of restricted latent class models for binary data are discussed: models assuming equalities of certain latent parameters, linearly constrained latent class analysis, and linear logistic latent class analysis. The basic equations of the latter model state the decomposition of the log odds of the item latent probabilities and of the class sizes into weighted sums of basic parameters representing the effects of predictor variables which are hypothesized to be relevant indicators for the original parameters. The maximum likelihood equations for these effect parameters and a criterion for their local identifiability are given. Further, statistical tests for goodness of fit are sketched, and the practical application of linear logistic latent class analysis is demonstrated by several examples. They comprise some known scaling models as well as a simple model with located classes and items, a model which relates item difficulty to item structure, and a model for measuring latent changes. Finally, the generalization of linear logistic latent class analysis to polytomous manifest variables is outlined.
A linear model for estimating the size of a closed population
Authors: Bonett Douglas G. , Woodward J. Arthur , Bentler P. M.
Published: August 2011

A linear model for estimating the size of a closed population is developed that will accommodate both dependent samples and heterogeneity of capture in multiple recapture sampling studies. Model parameters are estimated under exact and stochastic linear constraints and a Wald statistic is defined for evaluating constraints on model parameters and subpopulation sizes. Applications to survey research and experimental psychology are discussed.
Statistical analysis of discrete relational data
Authors: Wasserman Stanley , Iacobucci Dawn
Published: August 2011

Social interaction data record the intensity of the relationship, or frequency of interaction, between two individual actors. Recent methods for analysing such data have treated these relational variables as continuous. A more appropriate method, described here, views these dyadic interactions as variables in multidimensional discrete cross‐classified arrays, thus permitting analysis by log‐linear models.

These methods extend previous approaches to social interaction data, which were limited to binary relations, by focusing on discrete‐valued relations. Dyadic interactions, measured for a single discrete relational variable, are modelled stochastically using tendencies towards expansiveness (actor‐effects), popularity (partner‐effects) and reciprocity. Actor‐characteristic variables may be used to group actors into a substantive partition, thus simplifying the analysis and subsequent interpretations.
An evaluation of parametric and non‐parametric tests on modified and non‐modified data
Authors: Rasmussen Jeffrey Lee
Published: August 2011

A number of studies have questioned the robustness of the parametric F ratio to assumption violation and have recommended alternative procedures. These procedures differ in terms of whether they are parametric or non‐parametric, and whether they involve data modification or not. The present study compares Type I error rates and power of these approaches when they are calculated on data from a common mixed normal distribution. The tests investigated are F (parametric test, without data modification), Fm (parametric test, with data modification), Approximate randomization test (non‐parametric test, without data modification), and Mann–Whitney U (non‐parametric test, with data modification). Contrary to a previous study, the approximate randomization approach did not show good power characteristics. The Fm test and the Mann–Whitney U did show good power, with the former outperforming the latter.
Robustness of normal theory methods in the analysis of linear latent variate models
Authors: Browne M. W. , Shapiro A.
Published: August 2011

The structure of the covariance matrix of sample covariances under the class of linear latent variate models is derived using properties of cumulants. This is employed to provide a general framework for robustness of statistical inference in the analysis of covariance structures arising from linear latent variate models. Conditions for normal theory estimators and test statistics to retain each of their usual asymptotic properties under non‐normality of latent variates are given. Factor analysis, LISREL and other models are discussed as examples.
The correction of correlation coefficients for restriction of range when restriction results from the truncation of a normally distributed variable
Authors: Dobson Paul
Published: August 2011

A method is presented which allows correlation coefficients to be corrected for restriction of range when only the proportion of the population selected is known. The method assumes that the population distribution is normal and that selection has resulted in single truncation. A table is given which provides the ratio of the population and sample standard deviations, the truncation point, and the ordinate in N(0, 1), corresponding to the proportion of the population selected. Correlations can be corrected for the effects of direct or indirect selection by substitution of tabled values in traditional correction formulae. Further, the population mean or standard deviation can be estimated if the censored sample mean or standard deviation is known.
The robustness of the t test of the correlation coefficient and the need for simulation studies
Authors: van den Brink Wulfert P.
Published: August 2011

The t test of the Pearson product moment correlation coefficient for the null hypothesis that the population correlation, ρ, is zero, is very robust to violations of normality as long as the variables are independent. This conclusion is based on the results of simulation studies. But to reach this general conclusion, no simulation studies arc needed. It is a consequence of the virtual coincidence of the permutation distribution of r with the normal‐theory distribution. This implies that the test is also robust in most of the cases not examined by simulation studies, as long as the variables are independent. Only some predictable and extreme situations can give problems. Simulation studies should be directed to these situations to gain further insight in the robustness of the t test. This has not been done and much effort is misdirected on the simulation studies. When the variables are non‐independent it might be expected that the test is non‐robust. Also in this case simulation studies are useful to gain insight in the robustness of the test.
Synthesizing standardized mean‐change measures
Authors: Becker Betsy Jane
Published: August 2011

A new approach is presented for the meta‐analysis of data from pre‐test‐post‐test designs. With this approach, data from studies using different designs may be compared directly and studies without control groups need not be omitted. The approach is based on a ‘standardized mean‐change’ measure, computed for each sample within a study, and involves analysis of the standardized mean changes and differences in the standardized mean changes. Analyses are illustrated using results of studies of the effectiveness of mental practice on motor‐skill development.
A partial correlation test for the Goodman‐Kruskal λ on a dichotomy
Authors: Suich Ronald C. , Turek Richard J.
Published: August 2011

Goodman & Kruskal (1954) introduced a measure λ of predictive association when predicting the category of a variable A from a category of a variable B. The measure λ is such that 0≤λ≤1 with a zero value meaning no predictive gain, while λ=1 indicates a perfect predictive association between A and B. Turek & Suich (1983) developed an exact test of H0:λ = 0 versus H1:λ>0 where the variable A is dichotomous. This test is analogous to a test for the significance of the correlation coefficient. This paper analyses the partial λ coefficient in order to answer the question of whether knowledge of a third (fourth, fifth, etc.) classification results in a significant increase in ability to predict the dichotomous variable A. This test, developed for qualitative categorical variables, is analogous to the test for partial correlation coefficients for quantitative variables.
Data transformation, Type I error rate and power
Authors: Rasmussen Jeffrey Lee
Published: August 2011

Research has shown that when an appropriate data transformation is known a priori, then it can lead to a substantial increase in power of analysis of variance while maintaining an appropriate Type I error rate. It was unknown, however, whether data transformation selected on sample characteristics would yield accurate Type I error rates and increased power. The present Monte Carlo study demonstrates that correct data transformation values could be selected on samples as small as four per group, that legitimate approaches do not inflate the nominal significance levels and that power could be increased by sample‐based transformations.
Balanced versus unbalanced designs for linear structural relations in two‐level data
Authors: McDonald Roderick P. , Goldstein Harvey
Published: August 2011

A general two‐level model for multivariate data is described and illustrated by specializations to a common factor model and a path model with latent variables. The problem of estimation is treated, and in the special case of a balanced sampling design, a likelihood‐based discrepancy function and a test of goodness of fit are obtained in terms of some simple sufficient statistics.
Decision conflicts: Within‐trial resampling in Richardson's method of triads
Authors: Ennis Daniel M. , Mullen Kenneth , Frijters Jan E. R. , Tindall J.
Published: August 2011

A unidimensional model is derived which can provide the probability that the same two stimuli will be perceived to be most alike and most different in Richardson's method of triads under the assumption that resampling occurs within a trial. This probability is shown to depend on the extent to which the stimulus distributions overlap and their relative locations on a unidimensional continuum. Recommendations on how to estimate this probability experimentally are given.
Constrained latent class models: Some further applications†
Authors: Formann Anton K.
Published: August 2011

Two types of restricted latent class models are known: linearly constrained latent class analysis (LCA), especially models assuming equalities of certain latent parameters, and linear logistic LCA. The present paper shows some new fields for their application, namely, one application of the first model type to non‐monotone dichotomous items and three applications of linear logistic LCA: 1. A model for paired comparisons comparable to that by Bradley and Terry, but providing for a heterogeneous sample composed of subsamples with different scaling values for the objects. 2. A model for repeated measurements on one and the same item, whereby changes over time can be represented by class‐specific change parameters. 3. Two variants of a simple scaling model showing that the unconditional as well as the conditional maximum‐likelihood representation of the Rasch model are special cases of LCA.
Factor structure in groups selected on observed scores
Authors: Muthén Bengt O.
Published: August 2011

A new method is proposed for estimating factor means and factor covariances in a group of individuals selected on their observed scores. The selection variable is, for example, the total score on an admissions test. Given a factor model for the test items based on the group of test takers, we may be interested in the factor structure for those in the top quartile. The differences in factor means and covariances between this selected group and the full group gives useful information both on successful test performance and on test validity. The new method draws on the classic Pearson‐Lawley selection formulas. It avoids the fallacy of factor analysis on the selected group, which would lead to incorrect estimates. The new method is applied to a simple factor structure model for the GMAT test. Although the majority of the GMAT items test verbal skills, it is found that a quantitative factor shows the greatest change in moving from average to top quartile test takers.
Parametric and non‐parametric analysis of groups by trials design under variance‐covariance inhomogeneity
Authors: Rasmussen Jeffrey Lee
Published: August 2011

The parametric groups by trials analysis of variance F ratio is a widely used statistical test. When the variancc‐covariance assumption of the test is not met, researchers are commonly advised to use an epsilon‐corrected F ratio. A non‐parametric alternative has also been recommended when this assumption is not tenable. The present study compares the Type I error rate and power of the conventional F ratio, the epsilon‐corrected F ratio, and a non‐parametric statistic under various degrees of violation of the variance‐covariance assumption. The results indicate that only under gross violation of the assumption does the non‐parametric test show superior power to the parametric test. Additionally the results indicate that the power of the non‐parametric test is also affected by violation of the variance‐covariance assumption. In general the epsilon‐corrected F ratio is recommended under the conditions investigated.
Estimation and application of latent variable models in categorical data analysis
Authors: Leung S. O.
Published: August 2011

Bartholomew (1980, 1984a) has laid down a foundation for factor analysis based on latent variable models. Shea (1984, 1985) has provided computer programs for estimating one‐factor latent variable models when responses are binary or polytomous variables. However, the programs have limitations on number of variables and the sample size, which limits their applicability, especially when variables are polytomous. However, the more important limitation is that it is not possible to use two‐factor models when one‐factor models are not adequate.

Here, we have gone further and successfully obtained maximum likelihood estimates for both the one‐factor and two‐factor latent variable models for binary and polytomous variables. The new algorithm is much faster because of careful and efficient programming. More importantly, generalization to high latent domensions is straightforward. Formal hypothesis testing is very difficult when variables are very large in number. However, we have shown in our examples that some interesting graphical interpretations can be made.
Attributable risk and relative improvement over chance: A note on Copas & Loeber (1990)
Authors: Nijsse M.
Published: August 2011

Copas & Loeber's (1990) measure of association for 2times2 tables, relative improvement over chance (RIOC), is shown to be identical to Levin's measure of attributable risk. It is demonstrated that both measures are equal to the difference between the true positive rate and the false negative rate, standardized for the ratio of base rate and selection ratio. Also, it is shown that Copas & Loeber's formula for the variance of RIOC in large samples is identical to the formula for the variance of attributable risk in cross‐sectional research as developed by Walter (1976). Relationships between RIOC and some existing measures of association are mentioned. By using Copas & Loeber's numerical example, it is concluded that they rightly make a distinction between large and small samples.
A generalization of the Rescorla‐Wagner model of conditioning and learning
Authors: Chiang Ching‐Yuan
Published: August 2011

We consider a generalization of the Rescorla‐Wagner model of conditioning and learning such that the associative strength of a stimulus compound is a linear combination of the associative strengths of the stimulus components. The difference equations defined by the generalization are solved, and some properties of the solutions and their implications are discussed.
Hierarchical relations between methods for simultaneous component analysis and a technique for rotation to a simple simultaneous structure
Authors: Kiers Henk A. L. , ten Berge Jos M. F.
Published: August 2011

The present paper discusses several methods for (simultaneous) component analysis of scores of two or more groups of individuals on the same variables. Some existing methods are discussed, and a new method (SCA‐S) is developed for simultaneous component analysis in such a way that for each set essentially the same component structure is found (SCA‐S). This method is compared to alternative methods for analysing such data which employ the same component weights matrix (SCA‐W) or the same pattern matrix (SCA‐P) across data sets. Among these methods, SCA‐W always explains the highest amount of variance, SCA‐S the lowest, and SCA‐P takes the position in between. These explained variances can be compared to the amount of variance explained by separate PCAs. Implications of such fit differences are discussed. In addition, it is shown how, for cases where SCA‐S does not fit well, one can use SCA‐W (and SCA‐P) to find out if and how correlational structures differ. Finally, some attention is paid to facilitating the interpretation of an SCA‐S solution. Like the other SCA methods, SCA‐S has rotational freedom. This rotational freedom is exploited in a specially designed simple structure rotation technique for SCA‐S. This technique is illustrated on an empirical data set.
Estimating recency and familiarity using trace strength
Authors: McLaren I. P. L.
Published: August 2011

One problem with trace strength models of recognition is that they typically confound the recency of a stimulus with its frequency of occurrence (familiarity). This paper proposes a trace strength model that allows computation of relatively independent measures of recency and familiarity. It closes with some speculations on the possible roles of context and interference in this type of system.
A better beta model of navigation
Authors: McLaren I. P. L.
Published: August 2011

Zipser's (1986) formulation of the beta model for navigation suffers from two major drawbacks; it requires a minimum of three landmarks, and that each landmark's position relative to the current position be accurately estimated. This paper extends the beta model by demonstrating that it can apply in the two landmark case, and also when one of the two landmarks is too distant for its coordinates to be estimated with any accuracy. This enables the model to meet some of the criteria for a successful account of navigation in the rat and the gerbil.
ANOVA: The practical importance of heteroscedastic methods, using trimmed means versus means, and designing simulation studies
Authors: Wilcox Rand R.
Published: August 2011

This paper addresses three issues related to the analysis of variance: the practical importance of heteroscedastic methods, replacing means with some other measure of location, with an emphasis on trimmed means, and the problem of how to design meaningful simulation studies. A reasonable argument is that if the variances of J independent groups are unequal, surely the means are unequal, in which case there is no worry about a Type I error. Assuming this is true, the temptation is to use the conventional F test, but this is a highly undesirable approach for several reasons described in the paper. Another practical concern is whether substantial gains in power can be achieved by switching from means to some other measure of location. It is already known that certain resistant measures of location have substantial advantages over the means when distributions are non‐normal. This paper describes a few new results related to trimmed means. Finally, when simulations are used to study the properties of a particular testing procedure, how should they be designed? In particular, which distributions should be used, and how should our choice be influenced by experience with non‐simulated data from actual studies? Also, which characteristics of a particular testing procedure need to be studied and reported? A few suggestions are made in the hope of improving upon current practice.
Who discovered Spearman's rank correlation?
Authors: Lovie A. D.
Published: August 2011

Spearman's Rank Correlation coefficient rho is the one nonparametric measure of association to feature in most modern courses, textbooks and computer packages in elementary statistics. This paper covers the tortuous route to the present position over the period 1904 to the early 1950s, casting considerable doubt on the way as to the easy identification of any one person (including Spearman) with the coefficient.
Maximum likelihood estimation for unbalanced multilevel covariance structure models via the EM algorithm
Authors: Raudenbush Stephen W.
Published: August 2011

Recent investigations have revealed that widely available software can be adapted to provide maximum likelihood (ML) estimates for a general class of multilevel covariance structure models if the data are balanced (e.g. equal numbers of students in each of many schools). When the data are unbalanced, finding ML estimates is more challenging. However, by viewing the ‘complete data’ as balanced, one can calculate ML estimates for unbalanced data by constructing a comparatively simple EM algorithm. Computation using standard single‐level structural equation software performs the ‘M step’, and an auxiliary program computes the E‐step. Simple computational formulas for this E‐step are provided in the case of two‐level data, and recent experience with its implementation discussed. Asymptotic standard errors are found by computing the observed‐data information matrix at convergence.
A hyperbolic cosine latent trait model for unfolding polytomous responses: Reconciling Thurstone and Likert methodologies
Authors: Andrich David
Published: August 2011

In the 1920s, Thurstone articulated a theory for the measurement of social variables that involved two distinct steps: first constructing and operationalizing a linear continuum by locating statements according to their affective values; second measuring persons. The first step involved the pair‐comparison design and the cumulative response mechanism, the second step involved the direct‐response design (of the form Agree or Disagree) and the unfolding response mechanism. In the 1930s, Likert proposed a procedure that obviated the need for the first step and apparently permitted measuring persons from their responses to statements that were similar to those used by Thurstone, but which required a response that indicated degrees of intensity of the form Strongly Agree, Agree, Undecided, Disagree or Strongly Disagree. Furthermore, and in contrast to Thurstone, he implicitly used the cumulative mechanism, scoring the successive categories with successive integers and simply summing them to obtain a measurement for each person. The two procedures were considered to be distinct and alternative, and in general, this is still the perception with a number of matters still not reconciled between the two procedures.

By resolving the Disagree response in the unfolding mechanism into its two constituent components, this paper presents an unfolding model for direct responses from first principles, and then generalises it to provide an unfolding model for polytomous responses of the Likert style. This model permits an understanding of those matters still not reconciled between the Thurstone and Likert approaches: First, Likert's success in using Thurstone‐like statements with the cumulative mechanism rather than the unfolding mechanism; second, the gap found between two clusters of locations when statements from a Likert‐style questionnaire are scaled using the Thurstone procedure; and third, the consistent problem with the middle category of Undecided in Likert‐style response formats.
Spectroscopic Observation of Dual Catalytic Sites During Oxidation of CO on a Au/TiO
2
Catalyst
Authors: Green Isabel Xiaoye , Tang Wenjie , Neurock Matthew , Yates John T.
Published: August 2011

The low-temperature oxidation of carbon monoxide proceeds initially with oxygen molecules that bridge titanium and gold sites.
Fukushima Begins 30-Year Odyssey in Radiation Health
Authors: Normile Dennis
Published: August 2011

Japanese researchers are about to launch one of the most ambitious epidemiological studies ever attempted on the effects of low-dose radiation.
Memory T-Cell Immune Response in Healthy Young Adults Vaccinated with Live Attenuated Influenza A (H5N2) Vaccine
Authors: Chirkova T. V. , Naykhin A. N. , Petukhova G. D. , Korenkov D. A. , Donina S. A. , Mironov A. N. , Rudenko L. G.
Published: August 2011

Cellular immune responses of both CD4 and CD8 memory/effector T cells were evaluated in healthy young adults who received two doses of live attenuated influenza A (H5N2) vaccine. The vaccine was developed by reassortment of nonpathogenic avian A/Duck/Potsdam/1402-6/68 (H5N2) and cold-adapted A/Leningrad/134/17/57 (H2N2) viruses. T-cell responses were measured by standard methods of intracellular cytokine staining of gamma interferon (IFN-γ)-producing cells and a novel T-cell recognition of antigen-presenting cells by protein capture (TRAP) assay based on the trogocytosis phenomenon, namely, plasma membrane exchange between interacting immune cells. TRAP enables the detection of activated trogocytosis-positive T cells after virus stimulation. We showed that two doses of live attenuated influenza A (H5N2) vaccine promoted both CD4 and CD8 T-memory-cell responses in peripheral blood of healthy young subjects in the clinical study. Significant differences in geometric mean titers (GMTs) of influenza A (H5N2)-specific IFN-γ+cells were observed at day 42 following the second vaccination, while peak levels of trogocytosis+T cells were detected earlier, on the 21st day after the second vaccination. The inverse correlation of baseline levels compared to postvaccine fold changes in GMTs of influenza-specific CD4 and CD8 T cells demonstrated that baseline levels of these specific cells could be considered a predictive factor of vaccine immunogenicity.