Sentence examples for sample selection framework from inspiring English sources

This result suggests the presence of selection bias, thus lending support to the use of a sample selection framework to estimate separate SPFs for the beneficiaries and control groups.

We also again control for sample selection within this framework; we follow Buchinsky (2001) by implementing a two stage approach, whereby step one involves estimating selection models for both established and new migrants using a semi-nonparametric estimator13, and in step 2, we augment the quantile regressions with level and squared terms of the inverse mills ratios derived from step 1.

We proposed a resampling correction for sample selection bias using a mathematical framework modeling the sampling process.

We develop a mathematical framework for sample selection bias in models for population structure and also proposed a correction for sample selection bias using auxiliary information about the sample.

In this work, we develop a mathematical framework for modeling sample selection bias in genotype data.

To achieve this, BlinkDB uses two key ideas: (1) an adaptive optimization framework that builds and maintains a set of multi-dimensional stratied samples from original data over time, and (2) a dynamic sample selection strategy that selects an appropriately sized sample based on a query's accuracy or response time requirements.

Further, in Sect. 4 we form the analytical framework comprised of two main elements: (a) sample selection and data and (b) model and econometrics.

We also propose a mathematical framework to correct for sample selection bias in ancestry inference reduce its effects on ancestry estimates.

This framework fits well under the sample selection (Heckman correction) specification introduced by Heckman (1979).

Selection term Term constructed from the selection   model that controls for sample selection   bias.

Results: Here, we develop such a model selection framework based on approximate Bayesian computation and employing sequential Monte Carlo sampling.