A method of optimal scaling for multivariate ordinal data and its extensions

This paper develops a method of optimal scaling for multivariate ordinal data, in the framework of a generalized principal component analysis. This method yields a multidimensional configuration of items, a unidimensional scale of category weights for each item and, optionally, a multidimensional configuration of subjects. The computation is performed by alternately solving an eigenvalue problem and executing a quasi-Newton projection method. The algorithm is extended for analysis of data with mixed measurement levels or for analysis with a combined weighting of items. Numerical examples and simulations are provided. The algorithm is discussed and compared with some related methods.Earlier results of this research appeared in Saito and Otsu (1983). The authors would like to acknowledge the helpful comments and encouragement of the editor.     

Using item-specific instructional information in achievement modeling

The problem of detecting instructional sensitivity (item basis) in test items is considered. An illustration is given which shows that for tests with many biased items, traditional item bias detection schemes give a very poor assessment of bias. A new method is proposed instead. This method extends item response theory (IRT) by including item-specific auxiliary measurement information related to opportunity-to-learn. Item-specific variation in measurement relations across students with varying opportunity-to-learn is allowed for.This paper was presented at the 1987 AERA meeting in Washington, DC. This research was supported by grant OERI-G-86-003 from the Office of Educational Research and Improvement, Department of Education. The author thanks Michael Hollis and Chih-fen Kao for valuable research assistance, and appreciates valuable comments made by an anonymous reviewer.     

A note on the computation of the second-order derivatives of the elementary symmetric functions in the rasch model

Jansen (1984) gave explicit formulas for the computation of the second-order derivatives of the elementary symmetric functions. But they are only applicable to those pairs of items which have unequal parameters. It is shown here that for equal parameters similar explicit formulas do exist, too, facilitating the application of the Newton-Raphson procedure to estimate the parameters in the Rasch model and related models according to the conditional maximum likelihood principle.The author wishes to thank the reviewers for their helpful comments on an earlier draft of this paper.     

What analytic metaphysics can do for scientific metaphysics

The apparent chasm between two camps in metaphysics, analytic metaphysics and scientific metaphysics, is well recognized. I argue that the relationship between them is not necessarily a rivalry; a division of labour that resembles the relationship between pure mathematics and science is possible. As a case study, I look into the metaphysical underdetermination argument for ontic structural realism, a well-known position in scientific metaphysics, together with an argument for the position in analytic metaphysics known as ontological nihilism. I argue that we can ascribe the same schema to both arguments, which indicates that analytic metaphysics can offer an abstract model that scientific metaphysics may find useful.     

L’approche existentielle dans l’accompagnement de personnes au chômage en perte de repères : les processus de construction du sens de la vie et du travail (études de cas)

The guidance design for unemployed people in changing career must increasingly take into account their existential concerns about career meaning. The literature about life and work meaning has highlighted the multifactorial complexity of meaning definition and determinants of meaning. This fact does not facilitate their use in counselling design. Bernaud et al. (2020) “Guidance for life and work meaning” device takes into account this problem; it offers many thinking prospects that organize meaning questioning in order to help people who loosed professional and personal markers. By analyzing an application of this device with the multiple cases method, our article examines how a meaning guidance helps unemployed people in giving a new direction of their career. The study of five cases with chronologic analysis unities shows how various meaning dimensions help people to clarify, to enrich and to transform their initial problematic during accompaniment and how they progress with different rhythms to major personal and vocational decisions.     

Effect of Daily Life Reward Loop Functioning on the Course of Depression

Engagement in activities increases positive affect (Reward Path 1), which subsequently reinforces motivation (Reward Path 2), and hence future engagement in activities (Reward Path 3). Strong connections between these three reward loop components are considered adaptive, and might be disturbed in depression. Although some ecological nomentary assessment (EMA) studies have investigated the cross-sectional association between separate reward paths and individuals’ level of depression, no EMA study has looked into the association between individuals’ reward loop strength and depressive symptom course. The present EMA study assessed reward loop functioning (5x/day, 28 days) of 46 outpatients starting depression treatment at secondary mental health services and monitored with the Inventory of Depressive Symptomatology—Self-Report (IDS-SR) during a 7-month period. Results of multilevel regression analyses showed significant within-person associations for Reward Path 1 (b = 0.21, p < .001), Reward Path 2 (b = 0.43, p < .001), and Reward Path 3 (b = 0.20, p < .001). Stronger average reward loops (i.e., within-person mean of all reward paths) did not relate to participants’ improvement in depressive symptoms over time. Path-specific results revealed that Reward Paths 1 and 2 may have partly opposite effects on depressive symptom course. Together, our findings suggest that reward processes in daily life might be best studied separately and that further investigation is warranted to explore under what circumstances strong paths are adaptive or not.     

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.     

Structural connectivity between the hippocampus and cortical/subcortical area relates to cognitive impairment in schizophrenia but not in mood disorders

Cognitive impairment in schizophrenia and other psychiatric disorders is a challenge to be overcome in order to maintain patients' quality of life and social function. The neurological pathogenesis of cognitive impairment requires further elucidation. In general, the hippocampus interacts between the cortical and subcortical areas for information processing and consolidation and has an important role in memory. We examined the relationship between structural connectivity of the hippocampus and cortical/subcortical areas and cognitive impairment in schizophrenia, major depressive disorder and bipolar disorder. Subjects comprised 21 healthy controls, 19 patients with schizophrenia, 20 patients with bipolar disorder and 18 patients with major depressive disorder. Diffusion-weighted tensor images data were processed using ProbtrackX2 to calculate the structural connectivity between the hippocampus and cortical/subcortical areas. Cognitive function was assessed using the Brief Assessment of Cognition in schizophrenia composite score. Hippocampal structural connectivity index was significantly correlated with composite score in the schizophrenia group but not in the healthy control, major depressive disorder or bipolar disorder groups. There were no statistically significant differences in hippocampal structural connectivity index between the four groups. Structural connectivity between the hippocampus and cortical/subcortical areas is suggested to be a pathophysiological mechanism of comprehensive cognitive impairment in schizophrenia.     

驾驶员心理品质检测中的杆型人形图法

在汽车驾驶员心理品质检测研究中,我们根据数学中的多变量图分析方法,并汲取简笔画的优点,用19个人形图变量代表检测所得的17种心理品质数据,来具体、形象地再现每个驾驶员心理品质变量的整体关系。这对于检测结果的分类或进行系统化分析具有重要的实用意义。