Results 11 to 20 of about 129,849 (273)

Estimating General Parameters from Non-Probability Surveys Using Propensity Score Adjustment

Mathematics, 2020
This study introduces a general framework on inference for a general parameter using nonprobability survey data when a probability sample with auxiliary variables, common to both samples, is available.
Luis Castro-Martín, María del Mar Rueda, Ramón Ferri-García   +2 more
doaj   +1 more source

Propensity score weighting for covariate adjustment in randomized clinical trials [PDF]

Statistics in Medicine, 2020
Chance imbalance in baseline characteristics is common in randomized clinical trials. Regression adjustment such as the analysis of covariance (ANCOVA) is often used to account for imbalance and increase precision of the treatment effect estimate. An objective alternative is through inverse probability weighting (IPW) of the propensity scores. Although
Shuxi Zeng, Fan Li, Rui Wang, Fan Li
openaire   +4 more sources

Adjusting for unmeasured spatial confounding with distance adjusted propensity score matching [PDF]

Biostatistics, 2018
31 ...
Papadogeorgou, Georgia, Choirat, Christine, Zigler, Corwin   +2 more
openaire   +3 more sources

On variance estimate for covariate adjustment by propensity score analysis [PDF]

Statistics in Medicine, 2016
Propensity score (PS) methods have been used extensively to adjust for confounding factors in the statistical analysis of observational data in comparative effectiveness research. There are four major PS-based adjustment approaches: PS matching, PS stratification, covariate adjustment by PS, and PS-based inverse probability weighting (IPW).
Zou, Baiming, Zou, Fei, Koch, Gary G., Tighe, Patrick J., Shuster, Jonathan J., Zhou, Haibo   +5 more
openaire   +4 more sources

Adjusting for indirectly measured confounding using large-scale propensity score

Journal of Biomedical Informatics, 2022
Confounding remains one of the major challenges to causal inference with observational data. This problem is paramount in medicine, where we would like to answer causal questions from large observational datasets like electronic health records (EHRs) and administrative claims. Modern medical data typically contain tens of thousands of covariates.
Linying Zhang, Yixin Wang, Martijn J. Schuemie, David M. Blei, George Hripcsak   +4 more
openaire   +3 more sources

Will land circulation sway "grain orientation"? The impact of rural land circulation on farmers' agricultural planting structures.

PLoS ONE, 2021
This study calculates the effect of different types of land circulation on farmers' decision-making regarding agricultural planting structure, using field survey data involving 1,120 households in Hubei province, China, and PSM (propensity score matching)
Jiquan Peng, Juan Chen, Chen Su, Zhifeng Wu, Liu Yang, Wenji Liu   +5 more
doaj   +1 more source

Robust Causal Estimation from Observational Studies Using Penalized Spline of Propensity Score for Treatment Comparison

Stats, 2021
Without randomization of treatments, valid inference of treatment effects from observational studies requires controlling for all confounders because the treated subjects generally differ systematically from the control subjects.
Tingting Zhou, Michael R. Elliott, Roderick J. A. Little   +2 more
doaj   +1 more source

Accounting for the mortality benefit of drug-eluting stents in percutaneous coronary intervention: a comparison of methods in a retrospective cohort study

BMC Medicine, 2011
Background Drug-eluting stents (DES) reduce rates of restenosis compared with bare metal stents (BMS). A number of observational studies have also found lower rates of mortality and non-fatal myocardial infarction with DES compared with BMS, findings not
McCulloch Charles E, Chandra Malini, Yeh Robert W, Go Alan S   +3 more
doaj   +1 more source

Pre-Treatment Neutrophil Count as a Predictor of Antituberculosis Therapy Outcomes: A Multicenter Prospective Cohort Study

Frontiers in Immunology, 2021
BackgroundNeutrophils have been associated with lung tissue damage in many diseases, including tuberculosis (TB). Whether neutrophil count can serve as a predictor of adverse treatment outcomes is unknown.MethodsWe prospectively assessed 936 patients ...
Anna Cristina C. Carvalho, Anna Cristina C. Carvalho, Gustavo Amorim, Mayla G. M. Melo, Mayla G. M. Melo, Ana Karla A. Silveira, Ana Karla A. Silveira, Pedro H. L. Vargas, Pedro H. L. Vargas, Adriana S. R. Moreira, Michael S. Rocha, Michael S. Rocha, Alexandra B. Souza, María B. Arriaga, María B. Arriaga, María B. Arriaga, Mariana Araújo-Pereira, Mariana Araújo-Pereira, Mariana Araújo-Pereira, Marina C. Figueiredo, Betina Durovni, José R. Lapa-e-Silva, Solange Cavalcante, Valeria C. Rolla, Timothy R. Sterling, Marcelo Cordeiro-Santos, Bruno B. Andrade, Bruno B. Andrade, Bruno B. Andrade, Bruno B. Andrade, Bruno B. Andrade, Bruno B. Andrade, Elisangela C. Silva, Elisangela C. Silva, Elisangela C. Silva, Afrânio L. Kritski, Afrânio L. Kritski, the RePORT Brazil consortium   +37 more
doaj   +1 more source

Outcome-adjusted balance measure for generalized propensity score model selection

Journal of Statistical Planning and Inference, 2022
In this article, we propose the outcome-adjusted balance measure to perform model selection for the generalized propensity score (GPS), which serves as an essential component in estimation of the pairwise average treatment effects (ATEs) in observational studies with more than two treatment levels. The primary goal of the balance measure is to identify
Zhao, Honghe, Yang, Shu
openaire   +2 more sources