Forced classification: A simple application of a quantification method

This study formulates a property of a quantification method, the principle of equivalent partitioning (PEP). When the PEP is used together with Guttman's principle of internal consistency (PIC) in a simple way, the combination offers an interesting way of analyzing categorical data in terms of the variate(s) chosen by the investigator, a type of canonical analysis. The study discusses applications of the technique to multiple-choice, rank-order, and paired comparison data.This study was supported by the Natural Sciences and Engineering Research Council of Canada (Grant No. A7942). Comments on the earlier drafts from anonymous reviewers and the editor were much appreciated.     

Redundancy analysis for qualitative variables

Redundancy analysis (also called principal components analysis of instrumental variables) is a technique for two sets of variables, one set being dependent of the other. Its aim is maximization of the explained variance of the dependent variables by a linear combination of the explanatory variables. The technique is generalized to qualitative variables; it then gives implicitly a simultaneous optimal scaling of the dependent, qualitative variables. Examples are taken from the Dutch Life Situation Survey 1977, using Satisfaction with Life and Happiness as dependent variables. The analysis leads to one well-being scale, defined by the explanatory variables Marital status, Schooling, Income and Activity.The views expressed in this paper are those of the author and do not necessarily reflect the policies of the Netherlands Central Bureau of Statistics.     

Reinforcer pathology,probabilistic choice,and medication adherence in patients with multiple sclerosis

The reinforcer pathology model posits that core behavioral economic mechanisms, including delay discounting and behavioral economic demand, underlie adverse health decisions and related clinical disorders. Extensions beyond substance use disorder and obesity, however, are limited. Using a reinforcer pathology framework, this study evaluates medical adherence decisions in patients with multiple sclerosis. Participants completed behavioral economic measures, including delay discounting, probability discounting, and a medication purchase task. A medical decision-making task was also used to evaluate how sensitivity to mild side effect risk and efficacy contributed to the likelihood of taking a hypothetical disease-modifying therapy. Less steep delay discounting and more intense (greater) medication demand were independently associated with greater adherence to the medication decision-making procedure. More generally, the pattern of interrelations between the medication-specific and general behavioral economic metrics was consistent with and contributes to the reinforcer pathology model. Additional research is warranted to expand these models to different populations and health behaviors, including those of a positive health orientation (i.e., medication adherence).     

So you think you are an ally? Effects of (in)congruence between men's self-perceptions and women's perceptions of men's values and allyship on women's inclusion and vitality

As public consciousness of sexism is increasing in the workplace (e.g., #MeToo movement), labelling oneself as an ally (e.g., UN HeforShe campaign) is becoming more socially desirable for men. However, do women agree with such men in their assessments of being allies? Importantly, how does women's agreement (or not) with men's self-assessments of allyship affect women's inclusion-relevant outcomes? Using a multi-informant design and data from 101 men–women colleague pairs, this study considered men's self-perceptions and women's other-reports of men's key allyship-relevant characteristics—justice, moral courage, civility and allyship. Polynomial regression and response surface analyses revealed differential impacts of (in)congruence between men's and women's perceptions on women's sense of inclusion and vitality. Simply, when women perceived men as higher (or the same) in justice, moral courage and civility than men reported themselves, it positively predicted women's outcomes. This suggests that humble self-presentation by men on characteristics that are parallel to allyship (but not allyship) may be ideal. Yet, both under- and overestimation by men on allyship itself predicted poorer outcomes for women, suggesting that the ideal is for men to have an accurate assessment of their own strengths and weaknesses as an ally.     

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.     

“‘WE' AND ‘THEY'”: WHY MUST WE ENGAGE IN CROSS-CULTURAL CONVERSATION?

This article contains the principal ideas that I presented in four different sessions at the IRAS 2022 conference, on the theme “‘We' and ‘They’: Cross-Cultural Conversation on Identity.” Focusing on the central topic, the article begins with (i) the contents of my opening lecture; followed by (ii) a broad outline of the concerns discussed in my book, Cross-Cultural Conversation: A New Way of Learning, intertwined with glimpses of the intellectual journey that led me to CCC, delivered in the Book-discussion session; (iii) a summary of the main ideas about the importance of meeting of religions today, which formed the background for the CCC Panel discussion on religion, where I was in conversation with spokespersons of five world religions; and (iv) my comments on how science–religion dialogue can help promote a sense for human solidarity by combining knowledge with wisdom, in the concluding session.     

EXPERIMENTAL ANALYSIS AND TREATMENT OF MULTIPLY CONTROLLED SELF-INJURY

A functional analysis of the self-injurious behavior (SIB) of 3 adults with profound developmental disabilities showed that each engaged in SIB in more than one assessment condition. Such outcomes may result from a failure to isolate the variable maintaining SIB, or they may reflect multiple sources of control over SIB. In order to identify more clearly the determinants of SIB, each subject was exposed to a series of treatments appropriate to one or both of the apparent functions of SIB. These treatments, applied sequentially on baselines appropriate to each behavioral function, identified the maintaining variables for SIB through differential outcomes across baselines. Results indicated that the SIB of 2 subjects was multiply controlled, confirming the outcomes of the functional analysis. However, the SIB of the 3rd subject was eliminated using a treatment designed for a single function, suggesting spurious results of the original assessment. Alternative interpretations of undifferentiated assessment data are discussed, as are analysis and treatment issues related to multiply determined behavior disorders.     

Momentary maximizing in concurrent schedules with a minimum interchangeover interval

Eight pigeons were trained on concurrent variable-interval variable-interval schedules with a minimum interchangeover time programmed as a consequence of changeovers. In Experiment 1 the reinforcement schedules remained constant while the minimum interchangeover time varied from 0 to 200 s. Relative response rates and relative time deviated from relative reinforcement rates toward indifference with long minimum interchangeover times. In Experiment 2 different reinforcement ratios were scheduled in successive experimental conditions with the minimum interchangeover time constant at 0, 2, 10, or 120 s. The exponent of the generalized matching equation was close to 1.0 when the minimum interchangeover time was 0 s (the typical procedure for concurrent schedules without a changeover delay) and decreased as that duration was increased. The data support the momentary maximizing theory and contradict molar maximizing theories and the melioration theory.     

An alternating least squares method for the weighted approximation of a symmetric matrix

Bailey and Gower examined the least squares approximationC to a symmetric matrixB, when the squared discrepancies for diagonal elements receive specific nonunit weights. They focussed on mathematical properties of the optimalC, in constrained and unconstrained cases, rather than on how to obtainC for any givenB. In the present paper a computational solution is given for the case whereC is constrained to be positive semidefinite and of a fixed rankr or less. The solution is based on weakly constrained linear regression analysis.The authors are obliged to John C. Gower for stimulating this research.     

A maximum likelihood method for latent class regression involving a censored dependent variable

The standard tobit or censored regression model is typically utilized for regression analysis when the dependent variable is censored. This model is generalized by developing a conditional mixture, maximum likelihood method for latent class censored regression. The proposed method simultaneously estimates separate regression functions and subject membership in K latent classes or groups given a censored dependent variable for a cross-section of subjects. Maximum likelihood estimates are obtained using an EM algorithm. The proposed method is illustrated via a consumer psychology application.