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A parameter estimate was calculated for each latent and observational variable, to determine statistical significance and evaluate convergent validity.
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In this example the observed correlation between schooling and earning could emerge because of effects of IQ on both observational variables and not a causal relationship between the observed variables.
In previous applications we assumed that all models θ have the same causal structure, i.e. considering multivariate random variables a t and o t, we assumed that the same variables a t are intervened for all θ and the same causal model is used to predict the consequences of these interventions on the observational variables o t.
To assess construct validity, a compliance task was utilized to determine whether children identified as high on anxiety/withdrawal, anger/aggression, or social competence with the parent version of the SCBE-30 (n=20 for each group) could be distinguished behaviorally on several observational variables.
The consistency of observational variables was calculated in Table 3.
This indicated that the observational variables were derived from the latent variables.
Firstly, it is cross-sectional design that precludes from drawing conclusions concerning the causal relationships among the observational variables.
The following 2 nonrandomized observational variables represented compliance: the total number of tablets consumed and duration of supplementation.
The means, standard deviations, and bivariate correlations for all the observational variables are shown in Table 3.
Only observational variables with p < 0.05 on univariate analyses were included in the multivariate logistic regression model to ascertain their independent effects on TUR syndrome.
Only observational variables with p < 0.05 in univariate analyses were included in the logistic regression model to ascertain their independent effects on the symptom occurring.
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