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However, we did not obtain detailed data on the estimation method of prematurity.
Prior to our full analysis, we investigated the effect of missing data on the estimation of ages.
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32 The effect of the missing data mechanism on the estimation was explored by comparing estimation results derived by traditional models with the ignorable missing data mechanism and the Diggle-Kenward selection models which included explicit models either for ignorable or non-ignorable missing data mechanism.
Simulations were used to study the influence of model adequacy and data structure on the estimation of genetic parameters for traits governed by direct and maternal effects.
To study the influence of data structure on the estimation of genetic parameters, several populations were simulated, with different degrees of known paternity and different levels of genetic connectedness between flocks.
The analysis here is to investigate the effect of missing data on the parameter estimation of HIV dynamic model (1).
A multiple imputation analysis was carried out to investigate the effect of missing data on the model estimation.
However, in children data on the sonographic estimation of abdominal fat compartments is sparse and restricted to older children [ 17].
Besides, temperature can be considered as the most affecting input data on the MMP estimations because of sensitivity analysis implemented here.
In this paper, we study the estimation of a function based on noisy inhomogeneous data (the amount of data can vary on the estimation domain).
Therefore, the evaluation of the effect of both point density and the data model used on the estimation of AGB becomes an important issue in the MRV process.
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