A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.     

Predicting Substance Use from Religiosity/Spirituality in Individuals with Cystic Fibrosis

Journal of Religion and Health - Religiosity and spirituality predict lower alcohol and other substance use in community samples of adolescents and adults. However, the roles of religiosity and...     

Enhancing the care of children with chronic diseases through the narratives of patient,physician, nurse and carer

We tested the hypothesis that a narrative approach may enhance a bio‐psycho‐social model (BPS) in caring for chronically ill children. Forty‐eight narratives were collected from 12 children with six different medical conditions, their mothers, physicians, and nurses. By a textual analysis, narratives were classified on their predominant focus as disease (biological focus), illness (psychologic focus), or sickness (social focus). Sixty‐one percent of narrative’ text were classified as illness, 28% as disease and 11% as sickness. All narratives had a degree of illness focus. Narratives by patients and physicians on the one hand, and nurses’ and mothers’ on the other were disease focused. Narratives were also evaluated with respect to the type of medical condition: Illness was largely prevalent in all but Crohn’s disease and HIV infection, the latter having a predominance of sickness most probably related to stigma. Narrative exploration proved a valuable tool for understanding and addressing the needs of children with complex conditions. Narrative approaches allow identification of the major needs of different patients according to health conditions and story tellers. In the narratives, we found a greater illness and disease focus and surprisingly a low sickness focus, except with HIV stories. Narrative medicine provides a tool to strengthen the BPS model in health care.     

Erratum to: A Further Comparison Of Oblique Factor Transformation Methods

Psychometrika - The on-line version of this article has contained mistakes in affiliation part.     

Hume’s theory of justice and Vanderschraaf’s vulnerablity objection

Philosophical Studies -     

Skepticism and the principle of sufficient reason

Philosophical Studies - The Principle of Sufficient Reason must be justified dialectically: by showing the disastrous consequences of denying it. We formulate a version of the Principle that is...     

Caught between Scylla and Charybdis: How Economic Stressors and Occupational Risk Factors Influence Workers’ Occupational Health Reactions to COVID-19

Workers and their families bear much of the economic burden of COVID-19. Even though they have declined somewhat, unemployment rates are considerably higher than before the start of the pandemic. Many workers also face uncertainty about their future employment prospects and increasing financial strain. At the same time, the workplace is a common source of transmission of COVID-19 and many jobs previously seen as relatively safe are now viewed as potentially hazardous. Thus, many workers face dual threats of economic stress and COVID-19 exposure. This paper develops a model of workers’ responses to these dual threats, including risk perception and resource depletion as mediating factors that influence the relationship of economic stress and occupational risk factors with COVID-19 compliance-related attitudes, safe behavior at work, and physical and mental health outcomes. The paper also describes contextual moderators of these relationships at the individual, unit, and regional level. Directions for future research are discussed.