Zobrazeno 1 - 10
of 3 143
pro vyhledávání: '"Cole Stephen"'
Autor:
Wolock, Charles J., Jacob, Susan, Bennett, Julia C., Elias-Warren, Anna, O'Hanlon, Jessica, Kenny, Avi, Jewell, Nicholas P., Rotnitzky, Andrea, Cole, Stephen R., Weil, Ana A., Chu, Helen Y., Carone, Marco
For infectious diseases, characterizing symptom duration is of clinical and public health importance. Symptom duration may be assessed by surveying infected individuals and querying symptom status at the time of survey response. For example, in a SAR
Externí odkaz:
http://arxiv.org/abs/2407.04214
Autor:
Shook-Sa, Bonnie E., Zivich, Paul N., Lee, Chanhwa, Xue, Keyi, Ross, Rachael K., Edwards, Jessie K., Stringer, Jeffrey S. A., Cole, Stephen R.
Doubly robust estimators have gained popularity in the field of causal inference due to their ability to provide consistent point estimates when either an outcome or exposure model is correctly specified. However, for nonrandomized exposures the infl
Externí odkaz:
http://arxiv.org/abs/2404.16166
Patient care may be improved by recommending treatments based on patient characteristics when there is treatment effect heterogeneity. Recently, there has been a great deal of attention focused on the estimation of optimal treatment rules that maximi
Externí odkaz:
http://arxiv.org/abs/2401.03084
Autor:
Zivich, Paul N, Edwards, Jessie K, Shook-Sa, Bonnie E, Lofgren, Eric T, Lessler, Justin, Cole, Stephen R
Studies intended to estimate the effect of a treatment, like randomized trials, may not be sampled from the desired target population. To correct for this discrepancy, estimates can be transported to the target population. Methods for transporting be
Externí odkaz:
http://arxiv.org/abs/2311.09388
The Metropolis algorithm is a Markov chain Monte Carlo (MCMC) algorithm used to simulate from parameter distributions of interest, such as generalized linear model parameters. The "Metropolis step" is a keystone concept that underlies classical and m
Externí odkaz:
http://arxiv.org/abs/2306.16188
Iterated conditional expectation (ICE) g-computation is an estimation approach for addressing time-varying confounding for both longitudinal and time-to-event data. Unlike other g-computation implementations, ICE avoids the need to specify models for
Externí odkaz:
http://arxiv.org/abs/2306.10976
Autor:
Valancius, Michael, Pang, Herb, Zhu, Jiawen, Cole, Stephen R, Funk, Michele Jonsson, Kosorok, Michael R
We consider the challenges associated with causal inference in settings where data from a randomized trial is augmented with control data from an external source to improve efficiency in estimating the average treatment effect (ATE). Through the deve
Externí odkaz:
http://arxiv.org/abs/2305.08969
Autor:
Shook-Sa, Bonnie E., Zivich, Paul N., Rosin, Samuel P., Edwards, Jessie K., Adimora, Adaora A., Hudgens, Michael G., Cole, Stephen R.
While randomized controlled trials (RCTs) are critical for establishing the efficacy of new therapies, there are limitations regarding what comparisons can be made directly from trial data. RCTs are limited to a small number of comparator arms and of
Externí odkaz:
http://arxiv.org/abs/2305.00845