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From 50 Monte Carlo simulations of the observation period, with missing data replaced by an estimate randomly selected from its corresponding Gaussian distribution, 50 estimates of annual NEE and ET and their corresponding standard deviation were obtained.
Apart from complete subject analysis, analyses with missing data replaced by last observation carried forward (LOCF) were done.
Missing data replaced in this way amounted to 8 out of a total of 336 data points in each analysis.
Table 4 shows the changes in the BDI within and between the intervention and usual care group with missing data replaced using last value carried forward.
Table 5 shows the changes in the EQ-5D within and between the intervention and usual care group with missing data replaced using last value carried forward.
Given no difference in the pattern of results, the more conservative analysis with missing data replaced by baseline weights (assuming no weight loss) was selected for detailed reporting.
Similar(52)
A baseline last observation carried forward imputation method was utilized to impute missing data replacing the missing value with the baseline value if the responder rate was missing at week 32 for any reason.
Weight-loss predictors with missing data were replaced by multiple imputation.
As noted above, missing data was replaced using the last observation carried forward method.
All analyses were intent-to-treat, and missing data were replaced using the last observation carried forward method.
All of the missing data were replaced.
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CEO of Professional Science Editing for Scientists @ prosciediting.com