ESTIMATING CONTENT-ACQUIESCENCE CORRELATION BY COVARIANCE STRUCTURE ANALYSIS

A topic of continuing interest in the measurement area is response acquiescence. A recent study has demonstrated the feasibiliy of studying acquiescence or, more importantly, content/acquiescence correlation in the MMPI. Utilizing the components of variance approach, this study found that the variance due to acquiescence in scores on the Pt and Hg scales was small relative to content variance, but that the correlation between acquiescence and content may be substantial for the Pt scale. The present paper describes a general statistical procedure for investigating content variance, variance due to non-content characteristics of items, and the covariances of content and various item characteristics. The data from a previous paper are reanalyzed, using alternative covariance structure models. Maximum likelihood procedures which allow for a statistical test for parameters of interest are used. The results point to the significance of the content- acquiescence correlation in the Pt scale, but not in the Hy scale. The previous findings are verified statistically, and procedures which hold promise for other investigation into the properties of behavioral tests are described.     

Further evidence for Coren and Hakstian's "Methodological implications of interaural correlation: count heads not ears" and an alternative correction formula.

Coren and Hakstian (1990) identified a serious methodological problem that arises in auditory research because of interaural correlation. When measures from both ears of the subjects are pooled together in an experimental design that assumes independence of measures, there can be spuriously high apparent statistical significance. The present paper provides further evidence in support of Coren and Hakstian's argument and also derives a formula that effectively corrects inflated test statistics resulting from interaural correlation. This formula is a special case of a more general one that applies in many other experimental contexts in which nonindependence of measures is a problem. We found that statistical tests based on our formula have somewhat greater power to detect differences than the kind of correction method advocated by Coren and Hakstian.     

Further evidence for Coren and Hakstian’s “Methodological implications of interaural correlation: Count heads not ears” and an alternative correction formula

Coren and Hakstian (1990) identified a serious methodological problem that arises in auditory research because of interaural correlation. When measures from both ears of the subjects are pooled together in an experimental design that assumes independence of measures, there can be spuriously high apparent statistical significance. The present paper provides further evidence in support of Coren and Hakstian’s argument and also derives a formula that effectively corrects inflated test statistics resulting from interaural correlation. This formula is a special case of a more general one that applies in many other experimental contexts in which nonindependence of measures is a problem. We found that statistical tests based on our formula have somewhat greater power to detect differences than the kind of correction method advocated by Coren and Hakstian.     

The use of extreme groups to test for the presence of a relationship

Experimenters in psychology frequently investigate the relationship between two variables by selecting extreme groups on the first measure and comparing their mean scores on the second. This paper considers the efficacy of this procedure from the criterion of the power of the statistical tests. Optimal cutting points for the extreme groups are defined, and the power of the difference approach is compared to that of significance tests for the productmoment correlation coefficient.     

A new rank correlation coefficient with application to the consensus ranking problem

The consensus ranking problem has received much attention in the statistical literature. Given m rankings of n objects the objective is to determine a consensus ranking. The input rankings may contain ties, be incomplete, and may be weighted. Two solution concepts are discussed, the first maximizing the average weighted rank correlation of the solution ranking with the input rankings and the second minimizing the average weighted Kemeny–Snell distance. A new rank correlation coefficient called τ_x is presented which is shown to be the unique rank correlation coefficient which is equivalent to the Kemeny‐Snell distance metric. The new rank correlation coefficient is closely related to Kendall's tau but differs from it in the way ties are handled. It will be demonstrated that Kendall's τ_b is flawed as a measure of agreement between weak orderings and should no longer be used as a rank correlation coefficient. The use of τ_x in the consensus ranking problem provides a more mathematically tractable solution than the Kemeny–Snell distance metric because all the ranking information can be summarized in a single matrix. The methods described in this paper allow analysts to accommodate the fully general consensus ranking problem with weights, ties, and partial inputs. Copyright © 2002 John Wiley & Sons, Ltd.     

Measuring text similarity based on structure and word embedding

The problem of finding the similarity between natural language sentences is crucial for many applications in Natural Language Processing (NLP). An accurate calculation of similarity between sentences is highly needed. Many approaches depend on word-to-word similarity to measure sentence similarity. This paper proposes a new approach to improve the accuracy of the sentence similarity calculation. The proposed approach combines different similarity measures in the calculation of sentence similarity. In addition to traditional word-to-word similarity measure, the proposed approach exploits sentence semantic structure. Discourse representation structure (DRS) which is a semantic representation for natural sentences is generated and used to calculated structure similarity. Furthermore, word order similarity is measured to consider the order of words in sentences. Experiments show that exploiting structural information achieves good results. Moreover, the proposed method outperforms the current approaches on a standard benchmark dataset achieving 0.8813 Pearson correlation with human similarity.     

Random dynamics and the research programme of classical mechanics

The modern mathematical theory of dynamical systems proposes a new model of mechanical motion. In this model the deterministic unstable systems can behave in a statistical manner. Both kinds of motion are inseparably connected, they depend on the point of view and researcher's approach to the system. This mathematical fact solves in a new way the old problem of statistical laws in the world which is essentially deterministic. The classical opposition: deterministic‐statistical, disappears in random dynamics. The main thesis of the paper is that the new theory of motion is a revolution in the research programme of classical mechanics. It is the revolution brought about by the development of mathematics.     

共同方法偏差的统计检验与控制方法

共同方法偏差是心理学研究中一个越来越被关注的课题,但国内心理学界对其的介绍、研究还比较少,导致研究中对共同方法偏差的控制还有所欠缺。共同方法偏差的控制方法分为程序控制和统计控制,该文介绍了共同方法偏差的多种统计控制法,如因素分析法、偏相关法、潜在的误差变量控制法、结构方程模型法等,分析了其各自的优缺点,并提出了如何选择采用这些方法的建议.     

Optimal sample sizes for the design of reliability studies: Power consideration

Intraclass correlation coefficients are used extensively to measure the reliability or degree of resemblance among group members in multilevel research. This study concerns the problem of the necessary sample size to ensure adequate statistical power for hypothesis tests concerning the intraclass correlation coefficient in the one-way random-effects model. In view of the incomplete and problematic numerical results in the literature, the approximate sample size formula constructed from Fisher’s transformation is reevaluated and compared with an exact approach across a wide range of model configurations. These comprehensive examinations showed that the Fisher transformation method is appropriate only under limited circumstances, and therefore it is not recommended as a general method in practice. For advance design planning of reliability studies, the exact sample size procedures are fully described and illustrated for various allocation and cost schemes. Corresponding computer programs are also developed to implement the suggested algorithms.     

Statistical approaches to language acquisition and the self-organizing consciousness: a reversal of perspective

Recent years have seen the upsurge of a new approach to language that moves away from the rule-based conventional framework. In this approach, mostly supported by the success of connectionist models, children learn language by exploiting the distributional properties of the input. It is argued in this paper that, in the same way as conforming to rules does not imply the existence of mental rules, conforming to statistical regularities does not imply that statistical computations are performed mentally. Sensitivity to statistical regularities can alternatively be conceived of as a by-product of the recurrent interplay between the properties of the current conscious content and the properties of the linguistic and extralinguistic environment. The validity of including the content of conscious experiences in an otherwise standard dynamical approach rooted in the notion of self-organization is discussed.     

How the 2SLS/IV estimator can handle equality constraints in structural equation models: A system‐of‐equations approach

Parameters in structural equation models are typically estimated using the maximum likelihood (ML) approach. Bollen (1996) proposed an alternative non‐iterative, equation‐by‐equation estimator that uses instrumental variables. Although this two‐stage least squares/instrumental variables (2SLS/IV) estimator has good statistical properties, one problem with its application is that parameter equality constraints cannot be imposed. This paper presents a mathematical solution to this problem that is based on an extension of the 2SLS/IV approach to a system of equations. We present an example in which our approach was used to examine strong longitudinal measurement invariance. We also investigated the new approach in a simulation study that compared it with ML in the examination of the equality of two latent regression coefficients and strong measurement invariance. Overall, the results show that the suggested approach is a useful extension of the original 2SLS/IV estimator and allows for the effective handling of equality constraints in structural equation models.     

A generative joint model for spike trains and saccades during perceptual decision-making

Theory development in both psychology and neuroscience can benefit by consideration of both behavioral and neural data sets. However, the development of appropriate methods for linking these data sets is a difficult statistical and conceptual problem. Over the past decades, different linking approaches have been employed in the study of perceptual decision-making, beginning with rudimentary linking of the data sets at a qualitative, structural level, culminating in sophisticated statistical approaches with quantitative links. We outline a new approach, in which a single model is developed that jointly addresses neural and behavioral data. This approach allows for specification and testing of quantitative links between neural and behavioral aspects of the model. Estimating the model in a Bayesian framework allows both data sets to equally inform the estimation of all model parameters. The use of a hierarchical model architecture allows for a model, which accounts for and measures the variability between neurons. We demonstrate the approach by re-analysis of a classic data set containing behavioral recordings of decision-making with accompanying single-cell neural recordings. The joint model is able to capture most aspects of both data sets, and also supports the analysis of interesting questions about prediction, including predicting the times at which responses are made, and the corresponding neural firing rates.     

A quantitative evaluation of sex differences in implicit personality theories

An investigation is conducted into whether male and female perceivers hold substantially different implicit theories of personality. 24 male and 24 female subjects were asked to sort a set of 36 trait names into groups of similar traits. On the basis of these data, proximities between trait names and proximities between groupings (or partitions) were computed and subjected to a differential statistical analysis. Neither a global test for sex-specific groupings of trait names nor tests at the level of perceived pairwise trait relationships yielded significant differences. It is concluded that aggregation of sorting data over both male and female perceivers is warranted without too big a loss of information. On the methodological side, this paper demonstrates the feasibility of a quantitative approach to handling the problem of data aggregation in the context of studies using the sorting method as a data-gathering technique.     

Integration of Analytic Hierarchy Process with Regression Analysis to Identify Attractive Locations for Market Expansion

Selection of new geographies in which to expand is a key decision for businesses aspiring to go beyond the opportunities in the existing markets. The conventional approaches of market selection can only provide a set of systematic steps for problem solving without considering the relationships between the decision factors. Decision models based on statistical techniques are able to examine the relationship between decision factors but are unable to effectively assist decision makers in identifying the most promising market, particularly in terms of prioritizing across decision factors. Analytic Hierarchy Process (AHP) is a commonly used approach for choosing alternatives by prioritizing across multiple decision factors. The typical AHP modelling requires knowledge of criteria and/or alternatives along with their relative weights, generally elicited from field experts. Quite often, firms encounter situations where decision makers are aware of only the overall objective and a set of earmarked geographies for setting up market locations while being relatively unaware of decision criteria and relative weights. This precludes using AHP to identify promising market locations. This paper conceptualizes a market selection decision model that integrates AHP with statistical modelling techniques to identify the attractive market locations for the purpose of expansion. The model first uses principal component analysis and multiple regression to determine significant decision criteria and their weights. Thereafter, it applies AHP to prioritize the market locations across the decision criteria. This integrative approach is illustrated for identifying the attractive locations in rural markets for a steel firm in India. The major advantage of this approach is that unlike the existing models, it works in situations when firms have not enough knowledge about factors for evaluating alternative market locations. Another key advantage of the proposed model is that of economizing resources for data collection on variables representing decision factors. Copyright © 2012 John Wiley & Sons, Ltd.     

Reconsidering the “relative” in relative ingroup prototypicality

Relative ingroup prototypicality (RIP) is an important concept in the ingroup projection model (IPM) of social discrimination and tolerance. This paper reviews measures of RIP currently in use and critically examines how the notion of RIP is captured by statistical tests treating RIP as a single variable. It is concluded that composite measures of RIP imply multiple statistical hypotheses that have previously been confounded. The value of an alternative multiple regression approach is illustrated in a study testing the hypothesis of a negative relationship between RIP and outgroup attitudes. Results based on the conventional univariate analyses would have confirmed or disconfirmed the hypothesis depending on the scoring method. In contrast, the multiple regression approach described in this paper resolves this ambiguity by suggesting that only outgroup prototypicality may be necessary to predict outgroup attitudes. Copyright © 2008 John Wiley & Sons, Ltd.     

Enhancing Digital Fluency through a Training Program for Creative Problem Solving Using Computer Programming

The purpose of this paper is to propose a training program for creative problem solving based on computer programming. The proposed program will encourage students to solve real‐life problems through a creative thinking spiral related to cognitive skills with computer programming. With the goal of enhancing digital fluency through this proposed training program, we investigated its effects. Two sets of experiments were performed in which 119 typical students and 30 younger, gifted students participated. Two synthetic creative problem solving tests, which had a high correlation with logical ability, scientific problem solving ability and divergent thinking ability, were developed to measure creative problem solving ability. We provided the treatment group with a paper‐based booklet with relevant problems developed specifically for that group. ANCOVA statistical procedures were used to analyze the pre‐ and post‐synthetic creative problem solving tests. The findings of our study are as follows: with typical students, the originality of the treatment group outperformed the control group, a result that was compatible with previous research. With gifted students, the fluency of the treatment group outperformed the control group, and overall creative problem solving ability was enhanced. Remarkably, fluency increased significantly, a notable difference from the results of prior studies. In conclusion, we inferred that, given the definition of digital fluency, if creative problem solving ability is enhanced by a training program for creative problem solving based on computer programming, digital fluency will ultimately be improved. In this paper, we discuss the result of fluency enhancement that contradicts prior research. We suggest that this training program could be a new learning environment for the students who have grown up with digital media.     

Truth-ratios,process, task,and knowledge

In this paper, I delineate two major problems facing reliabilist approaches in epistemology. I argue that Alvin Goodman's (1986) position fails to solve either problem. I then suggest an alternative reliabilist approach that ties truth-ratio assessments to particular, well-specified cognitive tasks. I claim that a well-specified cognitive task is an empirical hypothesis about a system that involves the specification of input and output types and nomic correlations (including statistical correlations) that underlie the system's performance. On my approach, one characterizes processes by reference to the system's dispositions across the situations consistent with the task. Characterization is best understood as revealing a strategy or a set of strategies for generating outputs from inputs relying on certain nomic correlations associated with the task.     

School System Evaluation by Value Added Analysis Under Endogeneity

Value added is a common tool in educational research on effectiveness. It is often modeled as a (prediction of a) random effect in a specific hierarchical linear model. This paper shows that this modeling strategy is not valid when endogeneity is present. Endogeneity stems, for instance, from a correlation between the random effect in the hierarchical model and some of its covariates. This paper shows that this phenomenon is far from exceptional and can even be a generic problem when the covariates contain the prior score attainments, a typical situation in value added modeling. Starting from a general, model-free definition of value added, the paper derives an explicit expression of the value added in an endogeneous hierarchical linear Gaussian model. Inference on value added is proposed using an instrumental variable approach. The impact of endogeneity on the value added and the estimated value added is calculated accurately. This is also illustrated on a large data set of individual scores of about 200,000 students in Chile.     

Peirce Snatching: Towards a More Pragmatic View of Evidence

The running debate between Peter Achinstein and his critics concerning the nature of scientific evidence is misguided as each side attempts to explicate a distinct notion of evidence. Achinstein's approach, however, is valuable in helping to point out a problem with Carnap's statistical relevance model. By claiming an increase in probability to be necessary for evidence, the received view is incapable of accounting for evidence which is statistically irrelevant but explanatorily relevant. A broader view of evidence which can account for pragmatic concerns such as explanation is thereby required. This revised version was published online in July 2006 with corrections to the Cover Date.