bluuebunny/crossref_metadata_2025 huggingface dataset:
QUANTIFYING SHEAR EFFECTS ON A MODEL EMULSION SYSTEM
Authors: YURGEC M.J. , OSBORNE J. , STEFFE J.F. , DAUBERT C.R.
Published: August 2011

A model corn oil‐in‐water emulsion, stabilized by Tween 20 (0.2–0.6%), was subjected to homogenization conditions of time, number of homogenization cycles and pressure (100–800 bar), which corresponded to predetermined shear work and shear power intensity values. This project investigated the roles that shear work and intensity have on the development and destabilization of a sensitive emulsion system. Samples with the same shear work level produced an emulsion with any identical median particle size (MPS). Particle size data were modeled (MPS is a function of shear work and surfactant concentration). The data revealed a critical shear limit, where an increase in shear work no longer reduced the particle size that was directly related to surfactant concentration. A statistical model was adapted to determine the critical shear work value, resulting in the lowest MPS for each surfactant concentration tested.

PRACTICAL APPLICATIONS

Shear work and shear power intensity are rheological tools that can be used to design processing systems to yield optimum product quality. A process technologist can understand the shear limitations of a fluid system simply by understanding the affects that increasing levels of shear work and shear power intensity have on that system. By understanding the shear input that is occurring within a fluid system caused by various unit operations, a process technologist would be able to correlate this to the known shear limitations and make a determination if the process is too severe or not intense enough. Knowledge of this information would enable a process technologist to better select equipment, piping schematics and settings on devices that cause shear, which could lead to more optimum product quality and less product loss caused by over‐ or under‐shearing.
Efficacy of a New Accelerated Streptokinase Regime in Acute Myocardial Infarction: A Double Blind Randomized Clinical Trial
Authors: Ghaffari Samad , Kazemi Babak , Golzari Iraj Gorbani
Published: August 2011

Background: Studies of thrombolysis in acute ST‐elevation myocardial infarction (STEMI) have focused on differences in outcome between groups receiving various regimes. Expedited treatment may influence the efficacy of nonfibrin specific thrombolytic agents in restoring early patency of the infarct‐related artery (IRA), which is a major determinant of survival after ST‐elevation myocardial infarction (STEMI). Methods: We performed a randomized double blind clinical trial comparing an accelerated infusion (1.5 MU/20 min; group A, n = 200) with the conventional infusion (1.5 MU/60 min; group B, n = 100) of streptokinase (SK) in 300 patients with their first episode of acute STEMI. Demographics, clinical reperfusion rates, angiographic study findings, left ventricular ejection fraction (LVEF), in‐hospital morbidity and mortality and one year mortality were compared between two groups. Results: Mean age was 59 ± 12 years (79% male). There were no differences in baseline data between groups. Clinical, electrocardiographic and physiologic reperfusion indices revealed significant faster and higher reperfusion rates and better preserved LVEF at discharge in group A. Sixty‐three percent of patients in either group underwent invasive coronary angiography at a mean of 5 days with comparable findings. Atrial fibrillation, malignant ventricular arrhythmias in the second day, in‐hospital and late mortalities rates occurred more frequently in group B patients. In multivariate analysis, accelerated SK infusion was the only independent predictor of higher electrocardiographic reperfusion (OR = 3.2, CI: 1.93–5.3, P < 0.001). Conclusions: The accelerated SK infusion regimen of 1.5 MU in 20 min is safe and well tolerated with significantly faster and higher clinical reperfusion rates, more preserved LV systolic function, less atrial and ventricular sustained arrhythmias, and less in‐hospital and 1 year mortality rates in acute STEMI.
Modelling regional scale biofuel scenarios – a case study for India
Authors: Das Subhashree , Priess Joerg A. , Schweitzer Christian
Published: August 2011

Biofuel initiatives in India have gained momentum with the national biofuel policy targeting 20% blending of both petrol and diesel by 2017. Most of India's biofuel plans revolve around using sugarcane for bioethanol and jatropha for biodiesel production. This study, taking the southern Indian state of Karnataka as an example, aims at estimating the potential to achieve policy targets. The study spatially analyses land‐use change owing to biofuel expansion and its effects on food production. We used an integrated modelling framework to simulate land‐use change and bioenergy production under two scenarios – Industrial Economy (IE) and Agricultural Economy (AE). Results indicate that meeting the 20% blending target is a challenging goal to achieve under both scenarios. Bioethanol requirements can be nearly fulfilled (88% under IE and 93% under AE) because of sugarcane expansion. However, biodiesel demands cannot be fulfilled using only degraded lands as currently planned in India, but additional agricultural land (3–4% of the total cropland) will be required for jatropha‐based biodiesel production. Food production will not be directly impacted until 2025, because the largest source of additional land could be short‐ and long‐term fallows. We conclude that conservation oriented initiatives, such as water harvesting and energy conservation measures can increase productivities of biofuel crops and reduce fuel demands, respectively. State support and Clean Development Mechanism opportunities can enhance economic incentives for energy cropping. Therefore, a simultaneous and multipronged approach is needed to accommodate food and fuel demands in India.
Comparative interpretation of count, presence–absence and point methods for species distribution models
Authors: Aarts Geert , Fieberg John , Matthiopoulos Jason
Published: August 2011

1. The need to understand the processes shaping population distributions has resulted in a vast increase in the diversity of spatial wildlife data, leading to the development of many novel analytical techniques that are fit‐for‐purpose. One may aggregate location data into spatial units (e.g. grid cells) and model the resulting counts or presence–absences as a function of environmental covariates. Alternatively, the point data may be modelled directly, by combining the individual observations with a set of random or regular points reflecting habitat availability, a method known as a use‐availability design (or, alternatively a presence – pseudo‐absence or case–control design).

2. Although these spatial point, count and presence–absence methods are widely used, the ecological literature is not explicit about their connections and how their parameter estimates and predictions should be interpreted. The objective of this study is to recapitulate some recent statistical results and illustrate that under certain assumptions, each method can be motivated by the same underlying spatial inhomogeneous Poisson point process (IPP) model in which the intensity function is modelled as a log‐linear function of covariates.

3. The Poisson likelihood used for count data is a discrete approximation of the IPP likelihood. Similarly, the presence–absence design will approximate the IPP likelihood, but only when spatial units (i.e. pixels) are extremely small (Electric Journal of Statistics, 2010, 4, 1151–1201). For larger pixel sizes, presence–absence designs do not differentiate between one or multiple observations within each pixel, hence leading to information loss.

4. Logistic regression is often used to estimate the parameters of the IPP model using point data. Although the response variable is defined as 0 for the availability points, these zeros do not serve as true absences as is often assumed; rather, their role is to approximate the integral of the denominator in the IPP likelihood (The Annals of Applied Statistics, 2010, 4, 1383–1402). Because of this common misconception, the estimated exponential function of the linear predictor (i.e. the resource selection function) is often assumed to be proportional to occupancy. Like IPP and count models, this function is proportional to the expected density of observations.

5. Understanding these (dis‐)similarities between different species distribution modelling techniques should improve biological interpretation of spatial models and therefore advance ecological and methodological cross‐fertilization.
AN ADDITIVE METRIC FROM ALL THE PRINCIPAL COMPONENTS OF A PERFECT SCALE1
Authors: GUTTMAN LOUIS
Published: August 2011

A new type of metric is established for perfect scales that is different from the three previously known types of metrics. Given a perfect scale of m types of dichotomous items, each rank of persons is regarded as a point in an m‐dimensional space defined by the m non‐constant principal components. A non‐Euclidean distance function is defined for this space. It is proved that the resulting metric is additive: the non‐Euclidean distance between any two ranks i and k is the sum of the distances from i to j and from j to k whenever i ≤ j ≤ k. Treating the principal component space as non‐Euclidean may also be useful for the study of non‐scale structures and of quasi‐scales.
WEIGHTING RESPONSES TO ITEMS IN ATTITUDE SCALES
Authors: SLATER PATRICK
Published: August 2011

A metrical treatment of the problem of weighting responses to items in an attitude scale is described. The procedure proposed is developed from a method suggested by Guttman in 1941 and since discarded. A test for scalability is introduced. Procedures are described for carrying out the requisite iterations either with pencil and paper or with the Hollerith machine. Various methodological problems are also discussed.
THE DISTINCTION BETWEEN COMMON AND SPECIFIC VARIANCE IN FACTOR THEORY
Authors: Wrigley Charles
Published: August 2011

Abstract. The purpose of this paper is to indicate certain inadequacies in the current use of “communalities” in factor theory. There are considerable divergences in the way the term is defined; and several reasons for believing that, as ordinarily computed, the values become highly unstable when the number of tests or the size of the sample is increased. It is accordingly suggested that a better measure of the common factor variance might be furnished by substituting the square of the multiple correlation.
THE CONVERSION OF SCORES TO A UNIFORM SCALE
Authors: Howard M.
Published: August 2011

The original formula for rescaling estimates and test‐scores was derived from the three basic assumptions used by Galton and Pearson when deducing their formulae for the correlation coefficient; but it makes no allowance for differences in reliability and validity. However, the various modifications since suggested appear to rest on highly speculative arguments, and the improvements so obtained are seldom large enough to be statistically significant. On the basis of actual trials with tests and estimates of average validity, assessments of the predictive accuracy to be expected with the original formula have been computed. The accuracy diminishes progressively with the time‐interval involved, but remains high enough to justify its use for the practical purposes of the educationist.
PATTERN ANALYSIS1
Authors: Rimoldi H. J. A. , Grib T. F.
Published: August 2011

The purpose of the following article is to explain a technique for describing and comparing bivariate patterns in which a number of subjects respond to a number of items. A new scoring procedure is proposed for the responses based on a simple weighting principle, which leads to a convenient formula for comparing two or more patterns. The advantages of the method are discussed; and it is suggested that it may have useful applications in other fields.
FACTOR ANALYSIS, LATENT STRUCTURE ANALYSIS AND MENTAL TYPOLOGY
Authors: Miller Curtis R. , Eyman Richard K. , Dingman Harvey F.
Published: August 2011

The following paper deals with the classification of mentally retarded patients into groups or types, and is based on an analysis of data for over 700 cases. Two alternative methods have been used: first, latent structure analysis (a relatively new procedure suggested by Lazarsfeld) and factor analysis (a standard procedure for classifying persons as well as analysing tests or characteristics). It is found that the former yields a classification that agrees more closely with that proposed by earlier investigators in this field on the basis of subjective or intuitive judgement.
ASYMPTOTIC LEARNING IN PSYCHOPHYSICAL THEORIES1
Authors: Luce R. Duncan
Published: August 2011

The major types of models that have been proposed to account for the psychophysical data that are obtained when the stimulus differences are small are described briefly. Because it is clear that contingency variables, such as presentation schedules and payoffs, as well as the physical stimuli affect the response probabilities, recent models have included a trial dependent decision mechanism in addition to the (usually) static sensory one. Such models all appear to be special cases of two very general, but mathematically distinct, families of models, which are formulated in eqns. 1 and 5. Hypotheses about how the subject selects the response‐bias parameters of the decision process are examined. The assumption that they are chosen so as to maximize the expected payoff leads to incorrect predictions for special cases of both families. The alternative hypothesis studied is that the bias parameters are altered from trial to trial on the basis of information feedback according to one or another stochastic learning model. Primary attention is paid to the asymptotic expected values predicted for these parameters. Several such learning processes are described, their relations to static psychophysical models outlined, and their ability to explain data discussed.
FITTING A LINEAR TRACE DECAY MODEL TO TASTE COMPARISONS AND PREFERENCES1
Authors: Gregson R. A. M.
Published: August 2011

Taste assessment procedures are examples of human sensory and hedonic judgements which have not generally been analysed in dynamic psychophysical terms, though an extensive statistical literature has grown up to cover the use of such procedures. A taste comparison procedure, using mixtures of wines as stimuli and 168 non‐expert subjects as tasters, yielded data on five response measures which have been analysed using a linear trace decay model. The fit of the model is good and accounts for most of the observed variation in assessed differences which is associated with orders of tasting samples. Reasons for a poor fit in a minority of cases are discussed.
A REFORMULATION OF THE YERKES‐DODSON LAW
Authors: Broadbent D. E.
Published: August 2011

Since recent interest in ‘over‐arousal’ has revived the classic problem of deteriorating performance under high drives or incentives, and since some of the tests used to show this effect with human subjects can be analysed in terms of decision theory, an attempt is made to find a rule for decision which will show an inverted‐U relationship between efficiency and over‐all level of motivation. Such a principle is found, and proves to have the additional advantages of predicting frequency‐matching behaviour in guessing‐game situations, as well as departures from frequency‐matching as the level of motivation rises.
THE DIMENSIONS OF PERSONALITY AMONG CHILDREN OF SCHOOL AGE1
Authors: Hallworth H. J.
Published: August 2011

Researches on teachers' ratings of their pupils have indicated what appear to be two main dimensions of personality. Measurements of anxiety and of introversion obtained from questionnaires also suggest two dimensions, apparently similar in nature. Accordingly an attempt was made to relate the two sets of dimensions by using eight groups of secondary school pupils, each consisting of approximately 112 boys or girls in the first and fourth years of secondary modern and grammar schools. Ratings for personality, questionnaire scales, scores for tests of intelligence and attainment, and assessments of social conditions furnished 28 variables for fourth year pupils and 30 for first year pupils. A matrix of combined correlations was calculated for each of the eight groups. This was analysed by the method of principal components, and the axes were rotated in accordance with the Varimax criterion. Three factors were extracted which were comparable in each of the groups. The nature of the factors is discussed, and two possible interpretations are suggested.
DISCONTINUITIES AND LUMPINESS IN RECORDS OF EXTINCTION1
Authors: Slater Patrick , Yatkin A.
Published: August 2011

Records containing 2,154 inter‐response intervals (latencies) were obtained from 40 rats undergoing experimental extinction of a habit of pressing a bar to obtain food. The latencies do not generally tend to increase exponentially during the course of an experimental record, or follow any other smooth, continuous process of change. Gross discontinuities and lumpiness can be demonstrated; and these are the features that distinguish the records most clearly from random sequences of time intervals. The final event, extinction itself, appears as a significant discontinuity in every case but one. It can evidently occur without being induced by any continuous process; and perhaps the explanation of its occurrence should be sought by examining more closely the phenomena of discontinuities and lumpiness which contemporary theories overlook, and attempting to control them experimentally.
A SERVOANALYSIS OF SOME EFFECTS OF EFFORT ON RESPONSE RATE1
Authors: McFarland D. J.
Published: August 2011

The ability of pigeons to maintain a constant operant response rate, despite changes in the force required to operate the key‐mechanism, is discussed from a servoanalytic standpoint. It is shown that a first‐order linear feedback control system can account for the behaviour observed when a critical force requirement is not exceeded. Beyond the critical value the pigeons do not maintain the constant rate; and thus the control system is no longer linear. The existence of a limit to the applied force can account for this behaviour in this latter condition.
A NOTE ON SOME ALTERNATIVE MODELS FOR RESPONSE BIAS CHANGES DURING FORCED‐CHOICE DETECTION EXPERIMENTS1
Authors: Ronken Don A.
Published: August 2011

Several variants of a learning model for forced‐choice detection experiments (Atkinson and Kinchla, 1965) may be produced by making various reasonable assumptions regarding which events are effective in producing response bias changes. Atkinson and Kinchla assumed the bias changed according to a single parameter stochastic learning mechanism; such changes occurring only when no signal was detected. An alternative formulation uses two learning parameters and postulates that the bias changes on every trial, but at different rates according to whether or not the signal is detected. This two‐parameter model was applied to the data of Atkinson and Kinchla, and numerical estimates of the parameters were obtained which confirm the conjecture that the bias changes principally during non‐detection trials. In addition, the parameter estimates indicate that the relative effectiveness of information feedback is determined by its relative frequency of occurrence, an inference which was not possible from the single‐parameter model.
ROTATION TO A HYPOTHESIS OF CONSTANT FACTOR LOADINGS1
Authors: Sjöberg Lennart
Published: August 2011

A rotation method for the case of two dimensions is derived which maximizes the fit to a hypothesis of constant loadings in one factor in the least‐squares sense. An extension to cases of higher dimensionality is then presented together with an application of the procedure to the scaling of category judgements by the method of successive intervals.
ON THE INTERRELATED NATURE OF THE MULTIVARIATE STATISTICS USED IN DISCRIMINATORY ANALYSIS
Authors: Porebski Olgierd R.
Published: August 2011

This paper is concerned with discriminatory analysis involving two populations having equal a priori probabilities and a common covariance matrix and normal distribution. It is thus limited to a simple problem of discrimination to which a number of different solutions were proposed during the early period in the development of the subject. These well‐known results are presented here under one heading and in common notation. The paper begins with a discussion of some alternative logical ways of formulating the problem; then it shows the various statistical methods of deriving a discriminant function; finally, it exhibits the interrelated nature of the statistics which may be used in the test of significance. Each statistic is expressed as a scalar product of the same vector of differences between p pairs of means and a vector of discriminatory coefficients which varies only in length.
PRINCIPLES OF BEHAVIOURAL TAXONOMY AND THE MATHEMATICAL BASIS OF THE TAXONOME COMPUTER PROGRAM
Authors: Cattell Raymond B. , Coulter Malcolm A.
Published: August 2011

Types are modes in a multidimensional distribution, and can be found either by operating on a Q‐matrix of distances between individuals or by calculating densities in Cartesian sub‐spaces. Pursuing the former approach, reasons are given for preferring the family of rp ‘coefficients of likeness’ to Mahalanobis' D or other distance measures. A general formula is presented for rp, applicable to factors of any obliqueness and any assigned weight, permitting classification by what an individual docs as well as by what he is.

Classification procedures require recognition of the differences between types as homostats and as segregates. A homostat is a set of unusually similar people: a segregate is a series with above average similarities which thus has continuity, although there may be negligible resemblance between first and last members. A Boolean algorithm will objectively find homostats and sort them into phenomenal and nuclear clusters, and a further algorithm will operate on these to locate segregates. These steps have been combined in a computer program called Taxonome, two examples of the application of which are given. Search for types is a topographical descriptive procedure in which finding the ‘texture’ of a whole domain is as important as the location of individual types. Type analysis contributes to non‐linear prediction, to theories of type origin, and to higher order systematization and conceptualization.
TYPE I ERRORS AND THEIR DECISION BASIS
Authors: Rodger R. S.
Published: August 2011

It is proposed that an error‐rate 1 should be set for each statistical decision to be made. Methods for testing statistical hypotheses in the context of analysis of variance are reviewed and evaluated from the decision‐based error‐rate viewpoint. If decisions are the proper bases for the choice of an error‐rate, the available methods for testing any or all linear contrasts or linear functions of the means are unacceptable. Two new methods (R and D) are proposed for testing all contrasts or linear functions. One implication of the arguments given here is that, for most purposes, research workers have been using the wrong tables of F to test their statistical hypotheses.
A METHOD OF CLUSTER ANALYSIS
Authors: Constantinescu Paul
Published: August 2011

A mathematical method is proposed for clustering a set of elements with respect to a set of criteria. Input information is described in terms of a graph representing a distance function between the elements. Definitions are given for the concepts of a ‘tree’, and a ‘tree‐representation’. It is shown that clusters are particular kinds of subsets (level‐subsets) in a tree‐representation; and that a final pattern contains at least one non‐trivial tree, under specified conditions. An example of clustering is set out, and the computation of level‐subsets is described. The selection of clusters from a final pattern is briefly discussed.
A PROCEDURE FOR DETERMINING SLATER'S i AND ALL NEAREST ADJOINING ORDERS
Authors: Phillips J. P. N.
Published: August 2011

A new procedure is described for determining Slater's i and all nearest adjoining orders. The validity of the procedure is proved, and it is compared with Remage and Thompson's algorithm for the same purpose.
THE USE OF A NULL‐POINT METHOD TO STUDY THE ACQUISITION OK SIMPLE AND COMPLEX TRANSFORMATION SKILLS
Authors: Pask Gordon , Lewis B. N.
Published: August 2011

A null‐point experimental method for measuring human performance is described. This method can be used in studies of learning and in other situations where the effect of learning is appreciable, though irrelevant to the experimenter's objective. It provides a form of constancy of experimental conditions which is appropriate if the subject is conceived as an imperfect goal‐directed system. The method is exhibited in connexion with two experiments and a subsidiary study. One experiment involves the acquisition of a skill in which the human subject learns to apply a single transformation rule. For the other main experiment, the subject learns to deal alternately with two rules (so chosen that interference as well as positive transfer of training takes place). Further, in this case, the subject learns a concept which (in an operational sense) comprehends the pair of rules. The subsidiary experiment involves a modification of the original technique which may be useful in more detailed investigations of concept learning.
DISCRIMINATIVE BINARY PREDICTION WITH REINFORCED CUE IDENTIFICATION
Authors: Massaro Dominic W. , Moore John W.
Published: August 2011

Two tones, T1 and T2, differing in loudness, were employed as stimuli in a discriminative binary prediction task. Two responses, A1 and A2, predicting events E1 and E2 respectively, were available to the subjects. An A1 response was correct with probability π1 and π2 on T1 and T2 trials, respectively. The present study assessed the effects of the covariation of π2 and the similarity of T1 and T2 on P(A1|T1), the probability of an A1 response given a T1 trial. Subjects were also required to identify the trial type (loud or soft) and were given partial feedback of identification responding. Partial feedback was sufficient to eliminate the effects of cue similarity on discriminative event prediction and also improved identification of trial types. The reinforcement effects indicated that subjects learn to behave appropriately to identified cues rather than learn to make specific motor responses.
FACTOR ANALYSIS: THOMSON'S SAMPLING THEORY RECALLED
Authors: Maxwell A. E.
Published: August 2011

The advantages of basing the interpretation of mental factors on a model which is related to the possible physiological structure of the brain are re‐emphasized. The importance of the concept of determinacy of factors for those who claim that factors exist in some more or less permanent sense is pointed out, while the fact that good determinacy is seldom achieved is taken to counter‐indicate permanency. Examples are given to support the arguments, and it is shown that the value of factor analysis as a statistical aid is little affected when the notion of factors as entities is discarded.
SOME PROPERTIES OF QUADRATIC SIMILARITY JUDGEMENTS BETWEEN FOUR‐DIMENSIONAL STIMULI
Authors: Gregson R. A. M.
Published: August 2011

A model for quadratic similarity judgements developed previously (Gregson, 1969, 1970) is extended to deal with a form of bias, and to assess the information taken up by the parameters in the model. It is shown that judgements collapse, in terms of the model, into near randomness under restricted information conditions, but that this collapse is generally explicable in form, although it exhibits marked inter‐individual differences. Implications for similarity scaling models are noted.
SYSTEMS WITH RESPONSE‐DEPENDENT DEAD TIME
Authors: Hoopen M. Ten , Reuver H. A.
Published: August 2011

Conrad's (1951) data on the performance of a human operator who has to respond to a complex temporal sequence of stimuli (obtained by a parallel arrangement of two, three or four signal sources and each delivering periodic signals) are compared with the properties of three kinds of signal processing systems, each constituting special cases of a general concept. In model I a simple dead time is assumed, while in models II and III the dead time after each response is a linear function of the preceding inter‐response interval duration.

It is argued that the mean number of errors per unit of time, the criterion used so far, is a somewhat crude measure and that more decisive conclusions can be drawn when a more detailed description of the timing of the responses is available; for instance, in the form of the probability density function, or the joint probability density function of the response interval durations. The models may also find application in neuronal spike train analysis, and for problems in the field of operations research.
A NON‐PARAMETRIC MEASURE OF SIGNAL DISCRIMINABILITY
Authors: Altham Patricia M. E.
Published: August 2011

The estimation of a non‐parametric measure of signal discriminability is discussed and its behaviour investigated under the following conditions: (a) when the ‘trace’ distributions for the two signals being compared differ only by a shift parameter, Λ (b) when the probability density function of the trace is a monotone likelihood ratio; and (c) when the subject bases his response on a likelihood‐ratio rule, with a constant criterion. In this case the measure of discriminability is an increasing function of the shift, A. This monotonicity also holds for the two‐response experiment under rather more general conditions. Data from such an experiment are used as an example.
ANALYSIS OF COVARIANCE STRUCTURES AND EXPLORATORY FACTOR ANALYSIS
Authors: Mukherjee Bishwa Nath
Published: August 2011

After discussing the similarities and differences between covariance structural analysis and exploratory factor analysis, the relative superiority of the former is shown both for the generation, as well as for the testing of the hypothesis. Covariance structural analysis provides an objective axiomatic approach for the testing of structural hypotheses because, unlike exploratory factor analysis, it presupposes an explicit prior formulation of the hypothetical partitioning of data into factors. The two techniques are also compared in terms of scientific parsimony and the interpretation of results. It appears that though covariance structural analysis is more promising than exploratory factor analysis in theory building, a systematic joint use of both may lead to a more meaningful interpretation of intercorrelation data than can be reached by factor analysis alone.
STATISTICAL CONSIDERATIONS BASED ON AN INSTRUMENT FOR MEASURING ADVISER PERCEPTION
Authors: Kupper Lawrence L. , Hulka Barbara S. , Cassel John C.
Published: August 2011

An instrument is described for measuring the degree to which an adviser perceives' his advisees' attitudes. Its application requires each of n advisees to respond to a form consisting of c items. For each item, the adviser is instructed to respond as he thinks the particular advisee under consideration did. If Xij = jth advisee's response to the ith item, and if Yij = adviser's estimate of Xij, then θij = | Xij – Yij | is a reasonable measure of response discrepancy. Since the distribution of θij for a given patient response Xij = x depends on x, an ‘equitable’ comparison between two advisers must take into account differences in the distributions of advisee responses. A ‘standardized’ perception score is developed which reflects the fractional gain in perception from its worst possible value, conditional on the observed set of advisee responses. A method for testing the null hypothesis that two advisers are equally perceptive is given and a numerical example is included which illustrates the necessity for standardizing.
PROCEDURES FOR THE FACTOR ANALYTIC TREATMENT OF MEASURES OBTAINED ON DIFFERENT OCCASIONS
Authors: Hakstian A. Ralph
Published: August 2011

Five models are introduced for the factor analytic treatment of a set of measures obtained from the same sample of persons on two (and, in some cases, more) occasions. The models differ in terms of the assumptions made regarding the constancy of the factor score and factor pattern matrices on the two occasions. Least‐squares procedures are developed for the estimation of the (component) scores and patterns. The application of these procedures in common‐factor and image theoretical contexts is also discussed. Illustrative examples using some of the procedures are presented.
THE DEVELOPMENT OF A CLASS OF OBLIQUE FACTOR SOLUTIONS
Authors: Hakstian A. Ralph
Published: August 2011

Harris & Kaiser's (1964) class of oblique factor solutions, referred to as Case II, is reviewed and further developed. Certain features of the component matrices are explicated, and an iterative procedure is presented for their simultaneous solution. Illustrative examples are given, based on both this iterative procedure and other Case II formulations. Implications for practice and further research are discussed.
SIMPLIFIED FORMULAE FOR STANDARD ERRORS IN MAXIMUM‐LIKELIHOOD FACTOR ANALYSIS
Authors: Jennrich Robert I.
Published: August 2011

Standard errors for maximum‐likelihood estimates of factor loadings are expressed in terms of the inverse of an augmented information matrix. This formulation arises naturally by viewing the problem as one in constrained maximum‐likelihood estimation. The constraints correspond to the form of rotation used. Results are given for canonical rotation and analytic rotations in the orthomax family.
SOME APPLICATIONS OF GRAPH THEORY AND RELATED NON‐METRIC TECHNIQUES TO PROBLEMS OF APPROXIMATE SERIATION: THE CASE OF SYMMETRIC PROXIMITY MEASURES
Authors: Hubert Lawrence
Published: August 2011

This paper selectively reviews some of the recent developments in sequencing objects along a continuum that rely upon a symmetric proximity measure defined between the objects to be seriated. Most of the discussion is from a graph‐theoretical point of view and emphasizes the notion of a maximal spanning tree and related ‘crude’ seriation strategies that require only the ordinal information from the basic proximity values. In addition, correspondences with several hierarchical clustering techniques are presented as well as an extension to the newer circular‐arc models developed in mathematics. A number of substantive examples are given incorporating data sets available in the psychological literature that have been analysed previously with alternative methods.
A COMPARISON OF SINGLE SAMPLE AND CROSS‐VALIDATION METHODS FOR ESTIMATING THE MEAN SQUARED ERROR OF PREDICTION IN MULTIPLE LINEAR REGRESSION
Authors: Browne M. W.
Published: August 2011

Two procedures for estimating the mean squared error of prediction of an empirically determined linear prediction equation are examined. The method usually employed makes use of a second validation sample; another method makes use of the calibration sample alone. The mean squared error of estimation is derived for each of the two estimation procedures and a comparison made. A test is provided also for the hypothesis that use of a prespecified subset of predictors results in no increase in the expected mean squared error of prediction.
A CLASS OF GENERALIZED BAYES MINIMAX ESTIMATORS OF A MULTIPLE REGRESSION COEFFICIENT VECTOR
Authors: Lin Pi‐Erh , Bodo Erwin P.
Published: August 2011

Consider a multiple regression problem in which the dependent and (three or more) independent variables have a joint normal distribution with unknown mean vector and unknown covariance matrix. Relative to a loss function depending on the statistical design at hand, a family of minimax estimators is obtained for the regression coefficient vector. It is shown that the maximum‐likelihood estimator is dominated by the minimax estimators and hence inadmissible. A class of generalized Bayes estimators is obtained which may be expressed in terms of incomplete beta functions. With very mild conditions, the Bayes estimators are shown to be minimax.
A PROCEDURE FOR TESTING THE EQUALITY OF p CORRELATED VARIANCES
Authors: Levy Kenneth J.
Published: August 2011

Given an independent random sample from a p‐variate normal population, a procedure is proposed for testing the equality of the diagonal elements of the covariance matrix with no restrictive assumptions concerning its off‐diagonal elements. The procedure is simulated utilizing Monte Carlo techniques, and a method for post hoc probing is also suggested.
ON AN ALGORITHM OF SMITH AND PAYNE FOR DETERMINING SLATER'S i AND ALL NEAREST ADJOINING ORDERS
Authors: PHILLIPS Dr.J. P. N.
Published: August 2011

It is shown by an example that Smith and Payne's algorithm is invalid.
THE RANDOMIZED RESPONSE TECHNIQUE AND LARGE SAMPLE PAIRWISE COMPARISONS AMONG THE PARAMETERS OF k INDEPENDENT BINOMIAL POPULATIONS
Authors: Levy Kenneth J.
Published: August 2011

Methods are proposed for making all possible pairwise contrasts among the parameters of k independent binomial populations based upon information obtained by the randomized response technique. In addition, the results of a small Monte Carlo study are presented in support of the methods presently being proposed.
Evaluating priority effects in free recall
Authors: Hubert Lawrence J. , Levin Joel R.
Published: August 2011

A randomization model appropriate for evaluating priority effects in free recall (i.e. whether ‘new’ items are recalled prior to ‘old’ items) is discussed and related to well‐known non‐parametric significance tests. In particular, the bases for the measures that have been suggested in the psychological literature may be interpreted either in terms of Wilcoxon's rank sum statistic or through a specific entry in a 2 × 2 contingency table. The mean and variance formulas for a general correlational statistic are provided that specialize to the moments for the two measures already in common use.
A simple comprehensive model for the analysis of covariance structures
Authors: McDonald Roderick P.
Published: August 2011

A model is described which contains as special cases a large number of models for the analysis of covariance structures. Using rules for a calculus of functions of matrices given by McDonald & Swaminathan (1973), the first and second derivatives are given, for any loss function, with respect to the parameters of the hypothesis, thus enabling a variety of methods of fitting and testing it.
A binomial latent trait model for the study of Likert‐style attitude questionnaires
Authors: Andrich David
Published: August 2011

A binomial logistic latent trait model for attitude items constructed and scored in the Likert tradition is proposed. Unconditional maximum‐likelihood estimates for subject and item parameters are examined and the model is applied to both simulated and real data. Advantages for data analyses which accrue from having an explicit model for Likert questionnaires are considered with one particular feature being a ready disclosure as to whether or not the neutral category functions as is expected.
Embedding Bayes' theorem in general learning rules: Connections between idealized behaviour and empirical research on learning
Authors: Lad Frank
Published: August 2011

A response is made to the recent discussions critical of the Bayesian learning procedure on the basis of empirically observed deviations from its prescriptions. Bayes' theorem is embedded in a more general class of learning rules which allow for departure from the demands of idealized rational behaviour. Such departures are termed learning impediments or disabilities. Some particular forms and interpretations of impediment functions are presented. Consequences of learning disabilities for the likelihood principle, stable estimation and admissible decision‐making are explored. Examples of surprising learning behaviours and decision strategies are generated. Deeper understanding of Bayesian learning and its characteristics results.
Two‐stage sampling to set sample size for post hoc tests in ANOVA with decision‐based error rates
Authors: Rodger R. S.
Published: August 2011

In the usual fixed‐effects ANOVA, if sample size N is to be calculated to set the power β for detecting some alternative to a null hypothesis, that alternative must be expressed in the units of the unknown variance σ2. The fact that the unknown σ2 may vary widely from experiment to experiment, makes comparability between them difficult. Stein (1945) invented a two‐stage sampling procedure which circumvents this difficulty and allows alternatives to nulls to be expressed entirely in numerical units. This paper reports tables of parameters D[Eβ]; v1 v2 required for two‐stage sampling with Rodger's (1967, 1974) method of post hoc tests. If v1 mutually orthogonal contrasts across the true means μ, each has the numerical value √k2 Σjchj2, then a sample size N1 can be calculated (using preliminary data, k2 and D[Eβ]; v1 v2) to ensure that the expected null contrast rejection rate will be at least Eβ in an appropriately chosen decision set. A worked example illustrates the method and shows how the risk of unpractically large N1 may be controlled.
The likelihood ratio test for the equality of correlation matrices
Authors: Browne M. W.
Published: August 2011

An algorithm for obtaining the likelihood ratio test statistic for testing the equality of correlation matrices is provided. The number of unknowns involved in the iterative process is reduced by means of nested minimization. Asymptotic properties of a pooled correlation matrix provided by the procedure are found to be similar to those of single correlation matrices. An illustrative example is given.
The simultaneous estimation of factor loadings and scores
Authors: McDonald Roderick P.
Published: August 2011

A well‐known problem in the estimation of factor loadings and scores in the fixed factors model is circumvented, and the estimates are shown to be the same as in the random factors model. It is shown that the fixed factors model readily generalizes to cases involving prescribed non‐linear regressions.
Achievement tests and latent structure models
Authors: Wilcox Rand R.
Published: August 2011

In the past, several latent structure models have been proposed for handling problems associated with measuring the achievement of examinees. Typically, however, these models describe a specific examinee in terms of an item domain or they describe a few items in terms of a population of examinees. In this paper, a model is proposed which allows a population of examinees to be described in terms of an item domain. As is illustrated, the model yields a new formula score which allows guessing to vary over the population of examinees.
Interdependent data and human conservatism
Authors: Goldstein Michael
Published: August 2011

Navon (1978) has considered the way in which apparent conservatism in human data processing maybe partly attributed to a perceived lack of independence between the data items. We consider this question for Bernoulli data, and identify those dependencies which lead to apparently conservative behaviour and those dependencies which will lead to apparent overestimation of posterior probabilities.
Multiple comparisons for variance heterogeneity
Authors: Games Paul A. , Keselman H. J. , Clinch Jennifer J.
Published: August 2011

Pairwise comparisons were computed on six procedures which convert tests of spread into tests for mean equality using the usual Student's t statistic and a Welch t statistic which obtains an error term from the variance and sample sizes involved in the comparison. The Tukey multiple comparison critical value was used to assess significance. The obtained Type I error and power data indicate that: (a) neither form of t is uniformly preferable; (b) both forms generally result in a more powerful test when sample sizes are equal; and (c) only the Brown & Forsythe absolute deviations from the median and Box‐Scheffé methods yield probabilities of a Type I error at the approximate nominal a level for all non‐normal leptokurtic populations. The applicability of the various forms of the t statistic to non‐pairwise comparisons and other multiple comparisons critical values is indicated.
Functional relations in multidimensional scaling
Authors: Lee Sik‐Yum , Bentler P. M.
Published: August 2011

Theory testing with multidimensional scaling models requires the ability to specify models with functional relations among parameters, to estimate the parameters of such models, and to compare the resulting models to models without functional constraints. The non‐linear optimization theory relevant to general multidimensional scaling models with functional relations is developed via first‐order necessary conditions. A Gauss‐Newton based algorithm is developed to implement the theory. The specific case of constraints to yield a circular configuration in the linear Euclidian distance model is studied in detail, and it is applied to some classical colour data.
The likelihood of the Borda effect in small decision‐making committees
Authors: Colman Andrew M.
Published: August 2011

Simple plurality voting allows the surprising possibility that a majority of a committee or an electorate may prefer one of the defeated alternatives to the plurality winner. Relatively little attention has been devoted to this paradox (which is distinct from Condorcet's ‘paradox of voting’) since the 18th century. With seven‐person committees choosing among three alternatives, the theoretical probability of its occurrence is shown to be 0.126 in a completely uniform culture in which all preference rankings are equally likely. The observed relative frequency was, however, found to be 0.020 when 70 university students who were randomly assigned to 10 seven‐person groups ranked 20 triplets of randomly chosen girls' names, and this was significantly lower (P < 0.001) than the theoretical probability in a completely uniform culture.
Probability expressions for simple social decision scheme models
Authors: Gillett Raphael
Published: August 2011

Five simple models of the implicit social process whereby a group combines individual preferences into a collective decision are investigated: plurality, majority, proportionality, equiprobability and highest expected value. For each model, an expression is developed which provides the probability that a group selects a given alternative, as a function of (i) group size, (ii) number of alternatives and (iii) the set of probabilities governing the likelihood with which a group member advocates each alternative. Predictions yielded by the probability expressions are used as the basis for a comparison of the models.
Variable selection techniques in discriminant analysis: II. Allocation
Authors: McKay R. J. , Campbell N. A.
Published: August 2011

The literature dealing with the selection of variables for allocation procedures is examined. Two types of technique are discussed, namely, those which use group separation as the criterion for variable selection and those which more appropriately employ error rates in allocation.
Arrow's theorem and examination assessment
Authors: Vassiloglou M. , French S.
Published: August 2011

Usually in examinations an overall assessment of a candidate's performance is made by means of a weighted sum of the marks attained on the various components. However, recently it has been suggested that the combination should be based on the candidate's rankings on the components alone, and not on the actual marks. This paper discusses whether such an approach can lead to a fair and consistent system of assessment.
Annotated bibliography of three‐mode factor analysis
Authors: Kroonenberg Pieter M.
Published: August 2011

Published and unpublished theoretical and applied papers on three‐mode principal component analysis and factor analysis have been annotated. In addition, the applications have been classified according to subject matter, data type, language and the theoretical papers have been classified according to problem, model, method or computer program treated.