For both methods and whatever the treatment effect, the smallest variance was observed when baseline covariates were strongly associated to the outcome, but moderately to treatment.
The model predictions matched the observed episodes better in Goni, where the smallest variance was observed (Δ=626.8, SE=6.6), versus Nouna (Δ=733.7, SE=4.8) and Cissé (Δ=882.8, SD=6.7).
The estimator with the smallest variance is found for u = L.
The most representative features, i.e. the ones with the smallest variance were Energy, SRE (GLRLM), and GLN (GLSZM).
We repeated this selection 100 times, and a set of the five spectra with the smallest variance were selected.
Z-scores of the teachers and job consultants were negative, indicating a flat distribution, meaning that large variance was found; z-score of driving instructors was positive, indicating a pointy distribution, meaning that small variance was found (Table 1).
Only a small variance was explained by the maternal and child characteristics (R Adj: 0.028) therefore, other factors needs investigation which may determine feeding practices such as influence of extended family members e.g. mother – in – law, maternal self – efficacy, parity, socio – economic status, standard living index, etc.
The smallest variances were generally shown for the disability based non-means tested benefits, and this is consistent with their explaining a greater proportion of the variation in mental health scores than the Townsend score and the means tested benefits.
The scores of the hidden reference, close to 100 with small variance, are not displayed.
These results suggest that the point estimate is inappropriate even when bigger or smaller variances are used for prior distributions of factor loadings and thresholds.
We then considered a smaller value of that effect β = 0.5 (medium effect) and no effect β = 0. Regarding scenario 2, as smaller variances were considered, we reduced the values of β to generate a strong covariate effect (β = 0.5), a medium effect (β = 0.2), or no effect (β = 0).
