Results 61 to 70 of about 1,248,041 (248)
Demographics after inverse probability weighting.
Demographics after inverse probability weighting.
Kiyuk Chang (3620258) +18 more
core +1 more source
Protocol for quantifying miRNA trafficking across the endosomal membrane
An in vitro protocol measures miRNA uptake into endosomes isolated from mammalian cell extracts, which are free of subcellular contaminants. Performed at 37 °C in the presence of ATP, it ensures the import of single‐stranded miRNA into the endosomal lumen.
Syamantak Ghosh +2 more
wiley +1 more source
Inverse probability weighting for causal inference in hierarchical data
Objective The aim of this study was to explore the impact of model misspecification, balance, and extreme weights on average treatment effect (ATE) estimation in hierarchical data with unmeasured cluster-level confounders using the multilevel propensity ...
Lin Hu +10 more
doaj +1 more source
IGF2 knockout reduces but does not abolish osteosarcoma growth in vitro and in vivo
To test whether endogenous IGF2 promotes osteosarcoma growth, IGF2 was knocked out in Saos2 cells via CRISPR‐Cas9. KO cells showed reduced proliferation in vitro, and knockout xenografts in mice reached only ~25% of wild‐type tumor volume. Insulin‐like growth factor 2 (IGF2) is implicated in osteosarcoma, but direct functional evidence of its role is ...
Shun Yao, Marco Archetti
wiley +1 more source
ipw: An R Package for Inverse Probability Weighting
We describe the R package ipw for estimating inverse probability weights. We show how to use the package to fit marginal structural models through inverse probability weighting, to estimate causal effects.
Ronald B. Geskus, Willem M. van der Wal
doaj
Among existing preference elicitation methods, the trade-off method offers an advantage over others in mitigating the influence of probability weighting on preferences, as it does not require assuming a specific form for the probability weighting ...
Rongyuan Liu, Chunhao Li
doaj +1 more source
Nonparametric augmented probability weighting with sparsity
Nonresponse frequently arises in practice, and simply ignoring it may lead to erroneous inference. Besides, the number of collected covariates may increase as the sample size in modern statistics, so parametric imputation or propensity score weighting usually leads to inefficiency without consideration of sparsity.
Xin He, Xiaojun Mao, Zhonglei Wang
openaire +3 more sources
Insurance and Probability Weighting Functions [PDF]
Evidence shows that (i) people overweight low probabilities and underweight high probabilities, but (ii) ignore events of extremely low probability and treat extremely high probability events as certain.
Ali al-Nowaihi, Sanjit Dhami
core
This prospective study demonstrates that laparoscopic sphincter‐preserving surgery is feasible for elderly patients. While overall survival reaches 70% at 5 years, advanced T‐stage and the omission of neoadjuvant therapy significantly drive recurrence, highlighting the need for personalized geriatric protocols despite logistical challenges.
Huu Duc Ho +4 more
wiley +1 more source
Portfolio Selection with Narrow Framing: Probability Weighting Matters [PDF]
This paper extends the model with narrow framing suggested by Barberis and Huang (2009) to also account for probability weighting and a convex-concave value function in the specification of cumulative prospect theory preferences on narrowly framed assets.
Enrico G. De Giorgi, Shane Legg
core

