Multivariate statistical analysis in fMRI.
Explore the source record for details and available documents.
Algorithms↗
Biomedical subjects
Raymond G Hoffmann
Publications and source records attributed to Raymond G Hoffmann.
A Bayesian approach to net health benefits: an illustration and application to modeling HIV prevention.
PURPOSE: To conduct a cost-effectiveness analysis of HIV prevention when costs and effects cannot be measured directly. To quantify the total estimation of uncertainty due to sampling variability as well as inexact knowledge of HIV transmission parameters. METHODS: The authors focus on estimating the incremental net health benefit (INHB) in a randomized trial of HIV prevention with intervention and control conditions. Using a Bernoulli model of HIV transmission, changes in the participants' risk behaviors are converted into the number of HIV infections averted. A sampling model is used to account for variation in the behavior measurements. Bayes's theorem and Monte Carlo methods are used to attain the stated objectives. RESULTS: The authors obtained a positive mean INHB of 0.0008, indicating that advocacy training is just slightly favored over the control condition for men, assuming a $50,000 per quality-adjusted life year (QALY) threshold. To be confident of a positive INHB, the decision maker would need to spend more than $100,000 per QALY.
Bayes Theorem↗
Disparities for latino children in the timely receipt of medical care.
OBJECTIVE: It is not known whether Latino children, the largest minority population in the United States, experience disparities in the timeliness of their access to health care. We compared timeliness of care among Latino, white, and African American children. METHODS DESIGN: cross-sectional cohort from the 2000 Medical Expenditure Panel Survey. PATIENTS: children with a usual source of care. OUTCOME MEASURE: timeliness of care was assessed using parent reports of their child's 1) routine care, 2) illness care, 3) phone help, and 4) experiencing of a brief wait time. ANALYSIS: multiple logistic regression was used to determine the adjusted odds of not always receiving timely medical care. RESULTS: Four-thousand one-hundred twenty children were included. Latino children were less likely to always (P < .05) receive timely care compared with whites and African Americans, respectively, in 3 areas: routine care, phone help, and brief wait time. Multiple regression revealed decreased relative risks (RR, 95% CI) of always receiving timely medical care for Latinos in the same areas: routine care, compared with whites (0.88, 0.79-0.98) and African Americans (0.81, 0.70-0.93); phone help, compared with whites (0.84, 0.76-0.92) and African Americans (0.86, 0.76-0.960); and brief wait time, compared with whites (0.71, 0.65-0.80) and African Americans (0.81, 0.70-0.92). With parental survey language in the model, Latinos experienced decreased timeliness of care for routine care compared with African Americans (0.85, 0.72-0.98); phone help compared with whites (0.87, 0.77-0.96); and brief wait times compared with whites (0.79, 0.71-0.87). CONCLUSIONS: Latino children experience marked disparities in obtaining timely medical care, only some of which is associated with language differences.
Black or African American↗