Sentence examples for missing audited data from inspiring English sources

The full likelihood model generates an imputation of the missing audited data from the reported and audited data, and performs the randomized trial comparison simultaneously.

Secondly, the missing audited data is generated using the parameter estimates from this modelling.

Multiple imputation generates several realisations of the missing audited data, given the observed data.

The imputation models do not have these problems, as the missing audited data is imputed from the observed audited data.

We are only interested in imputing the missing audited data, as ultimately this is considered the most accurate, and the pre-intervention data can be used in the modelling.

This was improved upon by the methods here which estimate the missing audited data, with the exception of the regression method, which was conservative, probably due to too much extra variation being add by the random effect for imputed values.

Then estimated parameters from these models were used to estimate the missing values from the audited data.

This comes from observed audited data where available (l = 0), and fitted audited data where it is missing (l = 1).

The basic method is to take bootstrap re-samples of the known audited data and from these, take smaller bootstrap samples to simulate the missing data.

Neither the audited data nor the reported data is complete.

The reported data is strongly related to the audited data.