Suggestions(1)
Exact(2)
Variables with less 30% missing values Model 2: No. observations: 7,412.
Two models were fitted adding to the above-reported one (Model 1) the variable FARMA with missing values (Model 2) and FARMA with imputation of missing values using the three imputation methods (Model 3: with mean imputation is shown in Table 2).
Similar(58)
Single item missing values in model A were more frequent than in model B (e.g. Hernia repair at T1: model A: 23.5%, model B: 7.9%.
Missing values in model A were compared with those in model B at T1 and T2.
As already mentioned, when the covariates have missing values, a model is needed for the distribution of covariates in addition to the structural equation model.
A limitation of the sample size and missing values prevented model estimation using all variables simultaneously.
Missing values in model 3 are assumed to be missing at random, since similar patient characteristics were shown in intervals with missing and non-missing values.
Missing values were modelled using a separate indicator variable.
Because the alcohol intake variable had 8.9% of missing values, we modeled dummy variables for missing values of this variable.
In most ICU databases, there is a high percentage of missing values, making modeling of these data more difficult.
Due to missing values, the models were analyzed with n = 81 and n = 78 for 'Overall quality of life" and the POS sum score, respectively.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com