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As part of the development of the statistical analysis plan, more detailed rules for handling the missing pain VAS scores have been developed for each missing data scenario (sleep, spoilt, score missing but participant remained in trial and score missing because participant withdrawn from trial).
To characterize the missing data scenario, a stochastic variable satisfying Bernoulli distributed white sequence is introduced.
This paper proposes an active resilient control strategy for singular networked control systems with external disturbances and missing data scenario based on sampled-data scheme.
Other methods include for example modelling missing data, scenario analysis or sensitivity analysis [ 21].
Table 4 demonstrates how agreement measures change as individual subjects have increasing missing items in the 20% MCAR (p = 0.20) missing data scenario.
More specifically, scenario 1 (S1) assigned 20 arrays to each treatment without missing data, scenario 2 (S2) assumed an unbalanced design with 10 and 30 arrays for treatments A and B, respectively (no missing data), and scenario 3 (S3) assumed two groups of 20 arrays with a 5% of randomly distributed missing data.
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The evaluation of the methods here is much more comprehensive than previous studies, as it uses much longer air quality time series with no missing data, under significantly larger number missing data scenarios.
In missing data scenarios, there are a number of possible missingness mechanisms.
We assessed this for three different missing data scenarios (MCAR-p = 0.10, MAR-age and sex and MNAR).
They go on to provide a useful checklist that researchers should apply when considering the use of simple imputation methods for missing data scenarios.
Such missing data scenarios leave researchers with the choice of dropping cases entirely when they have missing responses to some questions, or alternatively, finding an imputation solution to deal with missing information.
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