Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Multiple Imputation for Longitudinal Data: A Tutorial.
Stat Med
February 2025
Clinical Epidemiology & Biostatistics (CEBU), Murdoch Children's Research Institute, Parkville, Australia.
Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thus an analytic approach that accounts for this clustering by individual is required. While almost all research suffers from missing data, this can be particularly problematic in longitudinal studies as participation often becomes harder to maintain over time.
View Article and Find Full Text PDFMulticategory matched learning for estimating optimal individualized treatment rules in observational studies with application to a hepatocellular carcinoma study.
Stat Methods Med Res
January 2025
School of Mathematics, Sun Yat-sen University, Guangzhou, Guangdong, China.
One primary goal of precision medicine is to estimate the individualized treatment rules that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in practice. However, most existing individualized treatment rule estimation methods were developed for the studies with binary treatments.
View Article and Find Full Text PDFPrincipal investigator gender and clinical trial success: analysis of over 3000 obstetrics and gynecology trials.
AJOG Glob Rep
February 2025
Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, Chicago, IL (Steinberg, Young, Strom, Andebrhan, Perry, Barry, Holder, Roque, and Yee).
Background: In obstetrics and gynecology (OBGYN) research, gender disparities permeate through leadership, funding, promotion, mentorship, publishing, compensation, and publicity. Few studies have investigated OBGYN clinical trial leadership as it relates to investigator gender. Thus, we undertook an investigation of principal investigator (PI) gender and clinical trial success.
View Article and Find Full Text PDFCan an Acceptance and Commitment Therapy-Based Smartphone App Help Individuals with Mental Health Disorders Quit Smoking?
Depress Anxiety
January 2025
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Background: Individuals with mental health disorders face major barriers in accessing smoking cessation care, often due to the stigmas associated with mental disorders and addiction. Consequently, accessible population-based smoking cessation interventions are needed for this vulnerable group.
Objective: This secondary analysis utilized data from a 12-month randomized trial to examine whether an acceptance and commitment therapy-based app (iCanQuit) demonstrated greater efficacy, engagement, and satisfaction compared to a United States (US) Clinical Practice Guidelines-based app (QuitGuide) in helping adults with mental health disorders quit smoking.
High-dimensional multiple imputation (HDMI) for partially observed confounders including natural language processing-derived auxiliary covariates.
Am J Epidemiol
January 2025
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Multiple imputation (MI) models can be improved with auxiliary covariates (AC), but their performance in high-dimensional data remains unclear. We aimed to develop and compare high-dimensional MI (HDMI) methods using structured and natural language processing (NLP)-derived AC in studies with partially observed confounders. We conducted a plasmode simulation with acute kidney injury as outcome and simulated 100 cohorts with a null treatment effect, incorporating creatinine labs, atrial fibrillation (AFib), and other investigator-derived confounders in the outcome generation.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!