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Data are said to be missing completely at random (MCAR) if the reason for a missing observation is unrelated to observed values of the outcome and covariates.
Here the considered cases are, when the first missing observation is at position i then the missing observation will be sequential up to (i+3), for i = 2,3,..., n − 4.
Estimation of artificially missed value for the known series of data (Y_ Actual), when a missing observation is at any point between the first and the last observation of the variable values.
One approach to deal with missing data is simple imputation, which is the process whereby a single estimated value for the missing observation is obtained, thereby enabling standard statistical methods to be applied to the augmented data set.
Here the considered cases are, when the first missing observation is at position i the second is at position i + 4, for i = 2,3,..., n − 5.
Similar(55)
Since the 'not applicable' response is coded together with missing observations, any missing observation was also substituted by a mean of the remaining responses in the respective variable.
For the LVCF method, missing observations were replaced with the last observed value carried forward for reasons other than death or zero value carried forward at death.
Furthermore, in longitudinal panel data, missing observations are a growing problem also with nonparametric methods when cumulative outcome measures are used.
In several current large-scale assessment programs (Allen et al. [2001]; Foy et al. [2008]; OECD [2009]) missing observations were dummy coded and the dummy variables were subsequently used in the population model.
The general perception is that, to achieve a fixed significance level and power, a group sequential test will require a larger maximum total sample size than required by the corresponding standard single-stage test because missing observations are possible under the group sequential test setting.
In both cases, missing observations were excluded from the model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com