Results 11 to 20 of about 2,349,452 (293)
The impact of lockdown on child adjustment: a propensity score matched analysis
BMC PsychologyThe COVID-19 pandemic has had an inestimable impact worldwide, challenging the daily lives and interactions of children and their families. In 2022, Shanghai implemented a three-month lockdown in response to an acceleration of positive cases during the ...
Wanjuan Weng +7 more
doaj +3 more sources
Propensity score adjustment with several follow-ups [PDF]
Biometrika, 2014 Summary: Propensity score weighting adjustment is commonly used to handle unit nonresponse. When the response mechanism is nonignorable in the sense that the response probability depends directly on the study variable, a follow-up sample is commonly used to obtain an unbiased estimator using the framework of two-phase sampling, where the follow-up ...
Kim, Jae Kwang, Im, Jongho
openaire +5 more sources
Multiple comparisons for survival data with propensity score adjustment. [PDF]
Comput Stat Data Anal, 2015 This article considers the practical problem in clinical and observational studies where multiple treatment or prognostic groups are compared and the observed survival data are subject to right censoring. Two possible formulations of multiple comparisons are suggested.
Zhu H, Lu B.
europepmc +4 more sources
Comparison of Placebos and Propensity Score Adjustment in Multiple Sclerosis Nonrandomized Studies. [PDF]
JAMA Neurol, 2020 This comparative effectiveness research study examines propensity scores adjustment in multiple sclerosis studies comparing disease-modifying treatments.
Signori A +5 more
europepmc +3 more sources
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 +2 more
openaire +3 more sources
Cutting Feedback in Bayesian Regression Adjustment for the Propensity Score [PDF]
The International Journal of Biostatistics, 2010 McCandless, Gustafson and Austin (2009) describe a Bayesian approach to regression adjustment for the propensity score to reduce confounding. A unique property of the method is that the treatment and outcome models are combined via Bayes theorem. However, this estimation procedure can be problematic if the outcome model is misspecified.
McCandless, Lawrence C +3 more
openaire +2 more sources
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 +2 more
doaj +1 more source
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 +3 more
doaj +1 more source
Methods to Counter Self-Selection Bias in Estimations of the Distribution Function and Quantiles
Mathematics, 2022 Many surveys are performed using non-probability methods such as web surveys, social networks surveys, or opt-in panels. The estimates made from these data sources are usually biased and must be adjusted to make them representative of the target ...
María del Mar Rueda +2 more
doaj +1 more source