Combinatorial data analysis: Association and partial association

A combinatorial data analysis strategy is reviewed that is designed to compare two arbitrary measures of proximity defined between the objects from some set. Based on a particular cross-product definition of correspondence between these two numerically specified notions of proximity (typically represented in the form of matrices), extensions are then pursued to indices of partial association that relate the observed pattern of correspondence between the first two proximity measures to a third. The attendant issues of index normalization and significance testing are discussed; the latter is approached through a simple randomization model implemented either through a Monte Carlo procedure or distributional approximations based on the first three moments. Applications of the original comparison strategy and its extensions to partial association may be developed for a variety of methodological and substantive tasks. Besides rank correlation, we emphasize the topics of spatial autocorrelation for one variable and spatial association between two and mention the connection to the usual randomization approach for one-way analysis-of-variance.     

A family of chance-corrected association coefficients for metric scales

A chance-corrected version of the family of association coefficients for metric scales proposed by Zegers and ten Berge is presented. It is shown that a matrix with chance-corrected coefficients between a number of variables is Gramian. The members of the chance-corrected family are shown to be partially ordered. The author is obliged to Jos ten Berge for helpful comments.     

Premature conclusions about the signal-to-noise ratio in structural equation modeling research: A commentary on Yuan and Fang (2023)

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller standard errors, and thus corresponds to greater values of the [SNR].” In our commentary, we show that Yuan and Fang have made several incorrect assumptions and claims. Consequently, we recommend that empirical researchers not base their methodological choice regarding CB-SEM and regression analysis with composites on the findings of Yuan and Fang as these findings are premature and require further research.     

Ethics,AIDS, and community responsibility

In the discussion of the responsibilities of society to the HIV infected and uninfected, a serious question seems to have been left out of the picture: To what extent are people who are not infected, have no special relationship to the infected and have no professional responsibilities for the care of AIDS patients under an obligation to come to the aid of people with the HIV? In this paper, I shall examine our responsibilities, as members of society, for the welfare of others to whom we may or may not have a special relationship. I shall argue that those responsibilities flow from the conditions that structure our transactions with others; conditions that make such transactions possible.     

Interpreting canonical correlation analysis through biplots of structure correlations and weights

This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate regression and canonical correlation analysis/redundancy analysis is exploited for producing an optimal biplot that displays a matrix of regression coefficients. This plot can be made from the canonical weights of the predictors and the structure correlations of the criterion variables. An example is used to show how the proposed biplots may be interpreted.     

The logics of orthoalgebras

The notion of unsharp orthoalgebra is introduced and it is proved that the category of unsharp orthoalgebras is isomorphic to the category of D-posets. A completeness theorem for some partial logics based on unsharp orthoalgebras, orthoalgebras and orthomodular posets is proved.     

语义联系类型和强度对预期推理生成的制约作用

首先采用开放式问卷实验方法,由被试生成日常生活中的事件以及组成这些事件的各种活动和活动的参加者。然后,对这些事件熟悉性、对活动的典型性和可区分性三个维度进行主观评价,形成事件以及每个事件活动序列,并据此编制实验材料。实验主要考察活动的典型性和可区分性对于熟悉性高的事件的预期推理的影响,以及不同工作记忆能力的被试进行事件预期推理时的加工模式。实验结果表明：（１）高工艺记忆能力的被试对事件的预期量小于     

A further note on freeman's measure of association

This note extends and elaborates Hubert's attempt to provide an interpretation of Freeman's measure of association,. The measure is used in a a contingency table when observations are ordered on one variable and unordered on the other. No attempt is made explore the distribution of.