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Third, by exploiting the longitudinal data structure using panel econometric models, we investigated determinants of the above mentioned dependent variables.
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Contrasts of the correlates of the above-mentioned dependent variables were tested by repeating the logistic regression analyses using a different reference group for each categorical independent variable each time.
As mentioned above, four fixed-effects models for the dependent variables AZG, AZS, AMB, MED (i.e., outpatient services) and two random-effects models for the dependent variables HOS and SOM (i.e., inpatient services) are calculated.
Additional analyses were carried out, as mentioned, modelling baseline social support measures as continuous dependent variables against incident/persistent depression as binary independent variables in linear regression models (tables 6– 8).
Before presenting the results, it should be mentioned that the first three analyses were ANOVAs made on three different dependent variables: (a) the estimated-to-target duration ratio, (b) the absolute standardized error and (c) a Weber Fraction (WF -like index.
The dependent variables will be values after 6 and 12 months in the four before mentioned domains.
Multivariable analyses with each of the dependent variables were divided in two sets: first without and then with the pregnancy complications mentioned above.
For the dependent variable, as mentioned earlier, we chose different body parameter.
Dependent variables.
All these dependent variables were continuous variables.
Formally define the dependent variables.
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