Sentence examples for weighted estimation from inspiring English sources

Methods that use propensity scores can be categorized into four categories: matching, stratification, adjusting, and inverse probability weighted estimation [ 36, 53].

This problem can be overcome by inverse probability weighted estimation of Marginal Structural Cox Models (Cox MSM) or G-estimation of Structural Nested Cumulative Failure Time Models (SNCFTM).

There is a large recent literature on analysis of two-stage case control designs using more efficient inverse probability weighted estimation procedures and semiparametric efficiency procedures [ 116].

This might be the case because the unweighted estimator is more efficient, so that the immigration coefficient in the weighted estimation is less precisely estimated.

Firstly, we give weighted fair share from the very beginning, i.e., we estimate traffic loads of all APs in a distributed manner and distribute the transmission intervals to the contending APs according to this weighted estimation.

13Little and Rubin (1987) also add procedures based on completely recorded units (analysing only observations with complete data), as well as design-based weighted estimation and imputation-based procedures (the missing values are filled in) to their taxonomy of methods with partially missing data.

The propensity scores were used to calculate the inverse probability of treatment weighted estimations for each patient included in the study [ 31].

Weighted estimations of whole-site NO3− removal based on denitrification hot spots were higher than site estimations based on average denitrification rates, suggesting that studies using the latter approach may be underestimating NO3− removal at the landscape level.

Weighted estimations for Europe were computed based on countries for which at least 10 completed replies were available, using total country population as a weight.

Unlike the prior alternatives, the methods proposed here consider explicitly the physical properties of the raw materials, without the need of a linear weighted average estimation.

After all the determinant baseline maps were identified and prepared, weighted value estimation for each factor and its field value was computed as all the factors have no equal importance in controlling groundwater occurrence.