12 to 1 p.m.
Speaker: Mary Ryan Baumann, PhD, (she/her/hers), is an assistant professor of biostatistics at the University of Wisconsin – Madison, with joint appointments in the Department of Population Health Sciences and the Department of Biostatistics and Medical Informatics. She researches both methodological and logistical issues in clustered data analysis and study design, particularly cluster randomized and pragmatic trials. This allows her to help her UW and UW Health colleagues conduct sophisticated health and health services research for Wisconsin and beyond.
Summary
CRTs (cluster randomized trials) and stepped-wedge trials are popular study designs used to answer large-scale, community-based research questions. However, it can be difficult to obtain information to reliably inform design parameters like intracluster correlation. I’ll discuss some recent work documenting the challenges real study teams have faced in designing and analyzing these trials, and several tools I and colleagues have developed to bridge these gaps.
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Meeting ID: 267 990 466 73 Passcode: jB3Gt6Cb
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Video Conference ID: 112 391 070 8
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+1 213-533-9530,,548530361# United States, Los Angeles
Phone Conference ID: 548 530 361#
4 to 5 p.m.
Speaker: Linda McEvoy, PhD (she/her) is a senior investigator at KWPHRI and an MPI on the Adult Changes in Thought Study. She is also Professor Emerita at Herbert Wertheim School of Public Health and Longevity Sciences, University of California San Diego. She studies risk and protective factors for cognitive and brain health in aging using multidisciplinary approaches.
Summary
The Adult Changes in Thought Study is a landmark, longitudinal prospective study of cognitive health in aging. It enrolls members of KPWA aged 65+ (>6500 participants enrolled) and follows them every 2 years, obtaining measures of cognitive and physical function, life course exposures to dementia risk factors, objective measures of physical activity and sleep, and a multitude of other measures including clinical and pharmacy data, genetics, and neuroimaging. Approximately one third of the cohort consents to brain donation, and state-of-the-art neuropathology data is available on >1000 participants. This panel presentation will provide an overview of the study, our efforts to enroll a more diverse cohort, information on how to access ACT data and opportunities for collaboration.
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Meeting ID: 250 722 539 94 Passcode: Ge9CA9qp
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Video Conference ID: 112 980 670 2
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+1 213-533-9530,,899893098# United States, Los Angeles
Phone Conference ID: 899 893 098#
12 to 1 p.m.
Speaker: Pamela A. Shaw, PhD is a Senior Investigator in the Biostatistics Division of Kaiser Permanente Washington Health Research Institute with expertise in measurement error, design and analysis of complex epidemiologic studies, clinical trials, and survival analysis. Dr. Shaw’s current statistical research includes a focus on methodology and two phase study design to allow correction for covariate and outcome measurement error, with application to studies reliant on electronic health records and large observational cohort studies. She is co-Director of the Data Analysis Core for the Adult Changes in Thought (ACT), a long-running study of aging, and has continued collaborations in a variety of epidemiologic and clinical studies, with a focus on chronic and infectious diseases and lifestyle exposures.
Summary
Electronic health record (EHR) data are increasingly used for biomedical research, but these data have recognized data quality challenges. Data validation is necessary to use EHR data with confidence, but limited resources make complete data validation typically impossible. Using EHR data, we illustrate prospective, multiwave, two-phase validation sampling as a practical way to estimate the association between maternal weight gain during pregnancy and the risks of her child developing obesity or asthma, while correcting for errors in the EHR data. The proposed optimal validation sampling design depends on the unknown parameters, which are initially estimated using unaudited data and then adaptively updated as validation data accumulate. For efficiency, estimation combines multiple sampling frames that target different outcomes of interest and incorporates the unvalidated data using survey calibration. We validated 996 of 10,335 mother-child EHR dyads in six sampling waves. Estimated associations between childhood obesity/asthma and maternal weight gain, as well as other covariates, are compared to naïve estimates that only use unvalidated data. In some cases, estimates markedly differ, underscoring the importance of efficient validation sampling to obtain accurate estimates incorporating validated data.
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Meeting ID: 279 209 815 727 Passcode: Hz648BW9
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Video Conference ID: 115 135 680 0
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+1 213-533-9530,,660684374# United States, Los Angeles
Phone Conference ID: 660 684 374#
Land Acknowledgment
Our Seattle offices sit on the occupied land of the Duwamish and by the shared waters of the Coast Salish people, who have been here thousands of years and remain. Learn about practicing land acknowledgment.