Search Results - "Cai, Zhuangyu"

Methods of Estimating or Accounting for Neighborhood Associations With Health Using Complex Survey Data by Brumback, Babette A., Cai, Zhuangyu, Dailey, Amy B.

“…Reasons for health disparities may include neighborhood-level factors, such as availability of health services, social norms, and environmental determinants,…”
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Abstract PD5-02: Effective and globally reproducible digital pathologist training program on PD-L1 immunohistochemistry scoring on immune cells as a predictive biomarker for cancer immunotherapy in triple negative breast cancer by Dennis, Eslie, Kockx, Mark, Harlow, Greg, Cai, Zhuangyu, Bloom, Ken, ElGabry, Ehab

“…Abstract BACKGROUND: The VENTANA PD-L1 (SP142) Assay (SP142 assay) is the FDA-approved companion diagnostic for the combination of TECENTRIQ (atezolizumab) and…”
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Development of an FRα Companion Diagnostic Immunohistochemical Assay for Mirvetuximab Soravtansine by James, Racheal L, Sisserson, Taryn, Cai, Zhuangyu, Dumas, Megan E, Inge, Landon J, Ranger-Moore, James, Mason, Albert, Sloss, Callum M, McArthur, Katherine

“…Folate receptor-α (FRα, encoded by the FOLR1 gene) is overexpressed in several solid tumor types, including epithelial ovarian cancer (EOC), making it an…”
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Model-based standardization to adjust for unmeasured cluster-level confounders with complex survey data by Cai, Zhuangyu, Brumback, Babette A.

“…Model‐based standardization uses a statistical model to estimate a standardized, or unconfounded, population‐averaged effect. With it, one can compare groups…”
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On the use of between-within models to adjust for confounding due to unmeasured cluster-level covariates by Brumback, Babette A., Li, Li, Cai, Zhuangyu

“…Between-within models are generalized linear mixed models (GLMMs) for clustered data that incorporate a random intercept together with fixed effects for…”
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Conditional pseudolikelihood methods for clustered ordinal, multinomial, or count outcomes with complex survey data by Brumback, Babette A., Cai, Zhuangyu, He, Zhulin, Zheng, Hao W., Dailey, Amy B.

“…In order to adjust individual‐level covariate effects for confounding due to unmeasured neighborhood characteristics, we have recently developed conditional…”
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Conditional pseudo-likelihood and generalized linear mixed model methods to adjust for confounding due to cluster by Cai, Zhuangyu

“…This dissertation focuses on adjusting for confounding due to unmeasured cluster covariates using generalized linear mixed models(GLMMs). In social…”
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