Erin Gabriel on Muck Rack

Erin Gabriel

Colorado
As seen in: CNN, CNN en Español, MSN, MSN Canada, Nature, Wiley Online Library, KDKA-TV (Pittsburgh, PA), Taylor & Francis Online, KPRC-TV (Houston, TX), The Lancet and
✨I want to live and feel all the shades, tones and variations of mental and physical experience possible in my life -Sylvia Plath✨
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Articles

Bespoke instrumental variables with nonideal reference populations

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By Arvid Sjölander, Erin Gabriel
| Dialnet - Universidad de La Rioja
Ayuda Buscar en la ayuda Buscar en la ayuda Bespoke instrumental variables with nonideal reference populations Sjölander, Arvid [1] ; Gabriel, Erin E [2] [1] Department of Medical Epidemiology and Biostatistics, Karolinska Institute , Nobels väg 12A, 17177 Stockholm , [2] Department of Public Health, University of Copenhagen , Øster Farimagsgade 51353 København K, Copenhagen , Localización: American journal of epidemiology, ISSN-e 1476-6256, ISSN 0002-9262, Vol. 194, Nº. 4, 2025, págs.
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RumbleOn, Inc. Announces Leadership Changes

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By Erin Gabriel
| EIN Presswire
IRVING, Texas -- RumbleOn, Inc. (the "Company" or "RumbleOn"), the largest powersports retailer in North America, today announced the following leadership changes, each effective as of January 13, 2025: Michael Quartieri, Chairman of the Board of Directors, has been appointed Chief Executive Officer. Cameron Tkach, Vice President of Dealership Operations, has been promoted to Executive Vice President and Chief Operating Officer of the Company.
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Inverse probability of treatment weighting with generalized linear outcome models for doubly robust estimation

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By Erin Gabriel, Michael Sachs, Torben Martinussen, Ingeborg Waernbaum
| Wiley Online Library
1 INTRODUCTION Recently it has become well-known that many commonly used outcome models have the property that, within clinical trials where there is assumed to be no confounding, maximum likelihood in combination with regression standardization or the g-formula delivers unbiased estimates of the average causal effect (ACE) of the intervention (in large samples) even if the model is misspecified.
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