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Exact(35)
Therefore, the missing data have been synthesized to provide a complete set of elastic logs for the interval of interest for all the wells.
Statistical methods to solve the problem of missing data have improved significantly, as demonstrated by Schafer and Graham (2002), although misconceptions still remain abundant.
It indicates the increase in variance of the estimates because of the missing values: the closer the number is to zero, the less effect missing data have on the variance of the estimate.
Fortunately, solutions to impute the missing data have been developed, in particular in the field of social sciences, where multiple questions polls are usually only partially filled and where removing any sample partially filled would amount to discarding most of the dataset.
What impact would missing data have?
Many methods for how to deal with missing data have been proposed.
Similar(25)
Initial GDP estimates are based on partial information; missing data has to be based on the recent past.
The main assumption is that the missing data has linear relation with available data.
Additionally, their ability to handle situations of missing data has also been reported [16].
The presence and impact of missing data has received little attention in the RBA literature.
Therefore, after consultation with the biostatistician, we assumed the missing data had no impact on our conclusions.
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