Coefficient alpha, the most commonly used estimate of internal consistency, is often considered a lower bound estimate of reliability, though the extent of its underestimation is not typically known. Many researchers are unaware that coefficient alpha is based on the essentially tau-equivalent measurement model. It is the violation of the assumptions required by this measurement model that are often responsible for coefficient alpha's underestimation of reliability. This article presents a hierarchy of measurement models that can be used to estimate reliability and illustrates a procedure by which structural equation modeling can be used to test the fit of these models to a set of data. Test and data characteristics that can influence the extent to which the assumption of tau-equivalence is violated are discussed. Both heuristic and applied examples are used to augment the discussion.

This study aimed to develop risk scores based on clinical characteristics at presentation to predict intensive care unit (ICU) admission and mortality in COVID-19 patients. 641 hospitalized patients with laboratory-confirmed COVID-19 were selected from 4997 persons under investigation. We performed a retrospective review of medical records of demographics, comorbidities and laboratory tests at the initial presentation. Primary outcomes were ICU admission and death. Logistic regression was used to identify independent clinical variables predicting the two outcomes. The model was validated by splitting the data into 70% for training and 30% for testing. Performance accuracy was evaluated using area under the curve (AUC) of the receiver operating characteristic analysis (ROC). Five significant variables predicting ICU admission were lactate dehydrogenase, procalcitonin, pulse oxygen saturation, smoking history, and lymphocyte count. Seven significant variables predicting mortality were heart failure, procalcitonin, lactate dehydrogenase, chronic obstructive pulmonary disease, pulse oxygen saturation, heart rate, and age. The mortality group uniquely contained cardiopulmonary variables. The risk score model yielded good accuracy with an AUC of 0.74 ([95% CI, 0.63-0.85], p = 0.001) for predicting ICU admission and 0.83 ([95% CI, 0.73-0.92], p<0.001) for predicting mortality for the testing dataset. This study identified key independent clinical variables that predicted ICU admission and mortality associated with COVID-19. This risk score system may prove useful for frontline physicians in clinical decision-making under time-sensitive and resource-constrained environment.

We conducted a reliability generalization meta‐analysis to examine the internal consistency of Dyadic Adjustment Scale (DAS; Spanier, 1976) scores across 91 published studies with 128 samples and 25,035 participants. The DAS was found to produce total and Dyadic cohesion, Consensus, and Satisfaction scores of acceptable internal consistency, although lower than those originally reported by Spanier (1976). Reliability estimates of these scores did not differ by the sexual orientation, gender, marital status, or ethnicity of the sample. The Affective Expression subscale was found to produce scores with poor Cronbach’s alpha across studies. Reliability estimates of Affective Expression scores were highly influenced by sample characteristics. The implications of these results are discussed as they relate to the use of the DAS in research.

The self-expansion model of close relationships posits that when couples engage in exciting and activating conjoint activities, they feel connected with their partners and more satisfied with their relationships. In the present study, the experience sampling method was used to examine the predictions of the self-expansion model in couples' momentary experiences. In addition, the author generated several new hypotheses by integrating the self-expansion model with existing research on flow. Over the course of 1 week, 20 couples were signaled at quasi-random intervals to provide data on 1,265 unique experiences. The results suggest that the level of activation experienced during an activity was positively related to experience-level relationship quality. This relationship was consistent across free-time and nonfree-time contexts and was mediated by positive affect. Activation was not found to predict later affect unless the level of activation exceeded what was typical for the individual. Also examined was the influence of interpersonal context and activity type on self-expansion. The results support the self-expansion model and suggest that it could be considered under the broader umbrella of flow.