Bayesian Using Gibbs Sampling Manual. Cambridge: MRC Bio-statistic Unit

In this paper we propose a methodology for measuring the 'relative effectiveness' of healthcare services (i.e. the effect of hospital care on patients) under general conditions, in which: α) a healthcare outcome underlies qualitative and quantitative observable indicators; β) we are interested in studying the simultaneous dependency of multiple outcomes on covariates (where the outcomes can also be correlated to each other); γ) the relative effectiveness is adjusted for hospital-specific covariates; δ) we hypothesise a general distribution for random disturbances and the random parameters of relative effectiveness. For this topic, a generalisation of the SURE (seemingly unrelated regression equations) multilevel model is proposed. Albert & Chib (1997, J. Am. Stat. Assoc., 92, 916-925). In addition, a new theoretical result regarding the joint posterior distribution for the parameters is provided. The model proposed has been implemented for an effectiveness study of a selection of Lombard hospitals

On the effect of measurementmodel misspecification in PLS Path Modeling: the reflective case

The specification of a measurement model as reflective or formative is the object of a lively debate. Part of the existing literature focuses on measurement model misspecification. This means that a true model is assumed and the impact on the path coefficients of using a wrong model is investigated. The majority of these studies is restricted to Structural Equation Modeling (SEM). Regarding PLS-Path Modeling (PLS-PM), a few authors have carried out simulation studies to investigate the robustness of the estimates, but their focus is the comparison with SEM. The present paper discusses the misspecification problem in the PLSPM context from a novel perspective. First, a real application on Alumni Satisfaction will be used to verify whether different assumptions for the measurements models influence the results. Second, the results of a Monte-Carlo simulation study, in the reflective case, will help to bring some clarity on a complex problem that has not been sufficiently studied yet

Model-based clustering via linear cluster-weighted models

A novel family of twelve mixture models with random covariates, nested in the linear $t$ cluster-weighted model (CWM), is introduced for model-based clustering. The linear $t$ CWM was recently presented as a robust alternative to the better known linear Gaussian CWM. The proposed family of models provides a unified framework that also includes the linear Gaussian CWM as a special case. Maximum likelihood parameter estimation is carried out within the EM framework, and both the BIC and the ICL are used for model selection. A simple and effective hierarchical random initialization is also proposed for the EM algorithm. The novel model-based clustering technique is illustrated in some applications to real data. Finally, a simulation study for evaluating the performance of the BIC and the ICL is presented

Longitudinal Patterns of HBA1c Trajectories in Patients with Type 1 Diabetes

Introduction: Type 1 diabetes is a chronic condition that affects adolescents’ quality of life and raises the risk of developing mental health concerns and diabetes-related complications. Measuring glycated hemoglobin (HbA1c) over time is the standard of care within the management of type 1 diabetes; however, the determinants of different HbA1c trajectories remain poorly understood. In the secondary analysis of the data collected for the Integrated Care Model (1), we aimed to identify groups of HbA1c trajectories with similar trends and examine the association between these groups and demographic and psychosocial variables. Methods: HbA1c data were collected at 4 consecutive time points with a gap of 3±1 months. We used Leffondré’s method (2) and Group-based trajectory modeling (GBTM) (3) to derive the groups of HbA1c trajectories among 91 adolescents. Baseline characteristics of the adolescents included in the groups were analyzed by univariate analysis. Results: Leffondré’s method identified three groups of trajectories: stable (63%), decreasing (17%), and increasing (20%). The baseline HbA1c levels for the three groups were 8.00±0.93, 10.07±1.63, and 8.21±1.14, respectively. Among the baseline characteristics, only the treatment method distinguished the groups of adolescents with similar trajectories of HbA1c over time (p=0.015). The GBTM method identified similar groups: stable (67%), decreasing (18%) and increasing (15%). The baseline HbA1c levels for the three groups were 7.89±0.88, 9.81±1.61, and 9.00±1.38, respectively. Groups produced by GBTM were also distinguished by treatment modality at baseline (p=0.022). Discussion: We identified three distinct patterns of HbA1c trajectories in adolescents. The only baseline characteristic that significantly distinguished these trajectories was the treatment modality. References J. Versloot, et al., An Integrated Care Model to Support Adolescents With Diabetes-related Quality-of-life Concerns: An Intervention Study. Can J Diabetes (2022). K. Leffondré, et al., Statistical measures were proposed for identifying longitudinal patterns of change in quantitative health indicators. J Clin Epidemiol 57, 1049–1062 (2004). D. S. Nagin, Group-based trajectory modeling: an overview. Ann Nutr Metab 65, 205–210 (2014)

Development of an individual index of social vulnerability that predicts negative healthcare events: a proposed tool to address healthcare equity in primary care research and practice

Abstract Purpose Socially disadvantaged patients may lack self-efficacy to navigate a complex health system making them vulnerable to healthcare inequity. We aimed to develop an Index of social vulnerability that predicts increased risk of negative healthcare events (e.g. emergency hospitalization), independent of chronic disease burden. The analysis illustrates the conceptual and practical steps leading to the development of a pragmatic Index of social vulnerability to limited healthcare self-efficacy. Methods Using data from a 3-year cohort of 2507 adult primary care patients in Québec (Canada), we applied two complementary structural equation modelling approaches—Partial Least Squares Path Modelling (PLS-PM) and Multiple indicators and Multiple Causes (MIMIC) modelling—to identify a minimal set of social characteristics that could be summed into an Index related to limited healthcare self-efficacy. We then used logistic regression to determine if the Index predicted: hospital emergency department use; hospital admissions; unmet need for care, and others. We privileged parsimony over explanatory capacity in our analytic decisions to make the Index pragmatic for epidemiologic and clinical use. Results The Individual Social Vulnerability Index is the weighted sum of five indicators: two indicators of social support; educational achievement; financial status; limited language proficiency. The Index predicts increased likelihood of all negative healthcare outcomes except unmet need, with a clear threshold at Index ≥ 2. The effect is independent of chronic disease burden. Conclusion When social deficits outweigh social assets by two or more (Index ≥ 2), there is an increased risk of negative healthcare events beyond the risk attributable to poor health. The Index is a pragmatic tool to identify a minority of patients who will require additional support to receive equitable healthcare

Predicting changes in cataract surgery health outcomes using a cataract surgery appropriateness and prioritization instrument.

ObjectiveDetermine whether items in a cataract surgery appropriateness and prioritization questionnaire can predict change in best corrected visual acuity (BCVA) and health related quality of life (HRQOL) following cataract surgery.Methods313 patients with a cataract in Ontario, Canada were recruited to participate. BCVA was measured using the Snellen chart. HRQOL was measured using a generic instrument (EQ5D), a visual functioning instrument (Catquest-9SF), and an appropriateness and prioritization instrument (17 items). Outcomes were measured preoperatively and 3-6 months postoperatively. Descriptive statistics were used to describe demographics and outcomes. For each appropriateness and prioritization questionnaire item, a one-way ANOVA was used to compare group means of the change in BCVA, EQ5D, and Catquest-9SF.ResultsParticipants had a mean age of 69 years and were 56% female. BCVA improved in 81%, EQ5D in 49.6%, and Catquest-9SF score in 84% of patients. Improvement in both BCVA and Catquest-9SF scores were found in 68.5% of patients. The ANOVA showed a statistically significant association between a change in BCVA and the ability to participate in social life, and a statistically significant association between a change in Catquest-9SF and glare, extent of impairment in visual function, safety and injury concerns, ability to work and care for dependents, ability to take care of local errands, ability to assist others and ability to participate in social life.ConclusionsAlmost all patients had improved BCVA and/or visual functioning after surgery. Seven variables from the cataract appropriateness and prioritization instrument were found to be predictors of improvement in Catquest-9SF measuring visual functioning