Next, we describe the existing AR and TAR models and we present the basic multilevel
TAR model for state - dependent regulation.
Not exact matches
The multilevel
TAR model that we develop in this study is suitable
for testing this hypothesis, and can be used in a broader context
for investigating various proposed mechanisms of
state - dependent regulation.
Importantly, using the multilevel
TAR model, researchers can use person - level variables as predictors both
for the inertias, representing the
state - dependent regulatory weakness, and
for the threshold representing a person's equilibrium.
In conclusion, we note that the
TAR model was clearly preferable to an AR
model for these data, since affect regulation was
state - dependent
for most of the individuals in the sample and a multilevel AR
model would misrepresent the underlying regulatory process.
Thus, a posterior distribution was obtained
for this difference, and the 95 % credible interval of this difference was then used as a decision criterion: When 0 was included in the credible interval, there was no evidence that there are two different mean inertias, so we selected the multilevel AR
model; when 0 was not included in the credible interval of the mean difference, this was taken as evidence that there are two distinct
states with different mean inertias, so we selected the multilevel
TAR model.