In this paper, we first define two-level longitudinal-dynamic hierarchical models. These models are designed to fit longitudinal data sets where the dependency structure is not derived from observations but from a second-level model, which is a dynamic model for the parameters of the hierarchical model. First, we will discuss different methods for estimating the superparameters of two-level longitudinal-dynamic hierarchical models. Then, we will present the corresponding types of estimation for the superparameter that is the factor that creates the correlation in this model. This is followed by a simulation study along with the analysis of a real data set.
Qureshi, S. K. & Sadat Qureshi, G. (2021). Empirical Bayes estimates of correlation types for longitudinal-dynamic data in heterogeneous hierarchical models. Andishe_ye Amari, 25(2), 113-120.
MLA
Qureshi, S. K., & Sadat Qureshi, G. "Empirical Bayes estimates of correlation types for longitudinal-dynamic data in heterogeneous hierarchical models", Andishe_ye Amari, 25, 2, 2021, 113-120.
HARVARD
Qureshi S. K., Sadat Qureshi G. (2021). 'Empirical Bayes estimates of correlation types for longitudinal-dynamic data in heterogeneous hierarchical models', Andishe_ye Amari, 25(2), pp. 113-120.
CHICAGO
S. K. Qureshi & G. Sadat Qureshi, "Empirical Bayes estimates of correlation types for longitudinal-dynamic data in heterogeneous hierarchical models," Andishe_ye Amari, 25 2 (2021): 113-120,
VANCOUVER
Qureshi S. K., Sadat Qureshi G. Empirical Bayes estimates of correlation types for longitudinal-dynamic data in heterogeneous hierarchical models. Andishe_ye Amari. 2021;25(2):113-120 (In Persian).
