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To assess the added value of multiple imputation (MI) of missing repeated outcomes measures in longitudinal data sets analyzed with linear mixed-effects (LME) models.
Individuals with SUD appear hypersensitive to reward, undersensitive to loss, and deficient in integrating information across repeated outcomes [2], [3], [4], [5].
Therefore, repeated outcomes assessment are performed.
Generalised additive mixed models include random effects to take into account correlation patterns in repeated outcomes.
GEE analysis was developed to correct for repeated outcomes within the same subject [ 36].
Longitudinal studies with binary repeated outcomes are now widespread in epidemiology.
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According to this traditional view, a scientific hypothesis may be tested and verified by obtaining the repeated outcome of substantiating observations.
The methods are based on a simple model for comparing two phases, where the level of the outcome is stable within each phase and the repeated outcome measurements are independent.
Primary analyses used the GENMOD procedure in SAS to develop generalized estimating equation (GEE) models [35] using an exchangeable correlation structure which examined the relationship between the repeated outcome measure of failure to remit at each assessment point and the independent variables.
GENMOD procedures were used to analyze repeated outcome measurements of glycemic control.
Model 3 described the relationship among the repeated outcome measures (alternating logistic regression) [ 55].
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