Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Lotspeich, Sarah C"'
Autor:
Lotspeich, Sarah C., Alt, Ethan M.
Censored, missing, and error-prone covariates are all coarsened data types for which the true values are unknown. Many methods to handle the unobserved values, including imputation, are shared between these data types, with nuances based on the mecha
Externí odkaz:
http://arxiv.org/abs/2410.10723
Healthy foods are essential for a healthy life, but accessing healthy food can be more challenging for some people than others. This disparity in food access may lead to disparities in well-being, potentially with disproportionate rates of diseases i
Externí odkaz:
http://arxiv.org/abs/2405.16385
Missing data is a common challenge when analyzing epidemiological data, and imputation is often used to address this issue. Here, we investigate the scenario where a covariate used in an analysis has missingness and will be imputed. There are recomme
Externí odkaz:
http://arxiv.org/abs/2310.17434
To select outcomes for clinical trials testing experimental therapies for Huntington disease, a fatal neurodegenerative disorder, analysts model how potential outcomes change over time. Yet, subjects with Huntington disease are often observed at diff
Externí odkaz:
http://arxiv.org/abs/2303.01602
Autor:
Lotspeich, Sarah C., Richardson, Brian D., Baldoni, Pedro L., Enders, Kimberly P., Hudgens, Michael G.
People living with HIV on antiretroviral therapy often have undetectable virus levels by standard assays, but "latent" HIV still persists in viral reservoirs. Eliminating these reservoirs is the goal of HIV cure research. The quantitative viral outgr
Externí odkaz:
http://arxiv.org/abs/2302.00516
Autor:
Lotspeich, Sarah C., Garcia, Tanya P.
Modeling symptom progression to identify informative subjects for a new Huntington's disease clinical trial is problematic since time to diagnosis, a key covariate, can be heavily censored. Imputation is an appealing strategy where censored covariate
Externí odkaz:
http://arxiv.org/abs/2209.04716
Publikováno v:
Biometrical Journal, vol. 64, pp. 858-862, 2022
Analysts are often confronted with censoring, wherein some variables are not observed at their true value, but rather at a value that is known to fall above or below that truth. While much attention has been given to the analysis of censored outcomes
Externí odkaz:
http://arxiv.org/abs/2109.11989
Autor:
Gorsline, Chelsea A., Lotspeich, Sarah C., Belaunzarán-Zamudio, Pablo F., Mejia, Fernando, Cortes, Claudia P., Crabtree-Ramírez, Brenda, Severe, Damocles Patrice, Rouzier, Vanessa, McGowan, Catherine C., Rebeiro, Peter F.
Publikováno v:
In Public Health in Practice June 2024 7
The growing availability of observational databases like electronic health records (EHR) provides unprecedented opportunities for secondary use of such data in biomedical research. However, these data can be error-prone and need to be validated befor
Externí odkaz:
http://arxiv.org/abs/2108.13263
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.