Results 151 to 160 of about 2,029,988 (242)
Partial Identification of the Average Treatment Effect Using Instrumental Variables: Review of Methods for Binary Instruments, Treatments, and Outcomes. [PDF]
Swanson SA +4 more
europepmc +1 more source
Embryo‐like structures (stembryos) are an innovative tool, but they are hindered by experimental variability and limited developmental potential. DNA methylation is crucial for mammalian development, but its status in stembryo models is poorly characterized.
Sara Canil +4 more
wiley +1 more source
A doubly robust estimator for the average treatment effect in the context of a mean-reverting measurement error. [PDF]
Lenis D, Ebnesajjad CF, Stuart EA.
europepmc +1 more source
Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure +3 more
wiley +1 more source
Directed Acyclic Graph Assisted Method For Estimating Average Treatment Effect. [PDF]
Sun J, Duncan S, Pal S, Kong M.
europepmc +1 more source
Approaches to the Estimation of the Local Average Treatment Effect in a Regression Discontinuity Design. [PDF]
O'Keeffe AG, Baio G.
europepmc +1 more source
Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
Estimating the average treatment effect on survival based on observational data and using partly conditional modeling. [PDF]
Gong Q, Schaubel DE.
europepmc +1 more source
Estimating the Average Treatment Effect using Propensity Score Weighting is highly sensitive to the choice of propensity score model, especially when there is heterogeneity in treatment effects and limited overlap in covariates. In practice, the true treatment assignment mechanism is rarely known, and ATE estimates based on a single propensity score ...
openaire +1 more source

