With individual characteristics at the first level and township variable (Type of MFA benefit package) at the second level, Two-level Linear Multilevel models were fitted in terms of the following modeling strategy [ 27, 28, 31].
Random coefficient models (multilevel models) were used to examine simultaneously the predictors and course of the variables of interest.
Bayesian multilevel models were used to describe gender-specific AD-SoS variations among participants during pubertal years.
Lagged multilevel models were used to investigate the effect of the different types of touch on infant emotional regulation in the groups for the episodes.
Multilevel models were estimated to assess the effect of high racial isolation and high racial clusters on IUGR and preterm birth, controlling for maternal race, single marital status, smoking and area-level poverty.
Separate 3-stage multilevel models were fitted to partition the different nested variance components (i.e., classroom, school and city levels), and intra-class correlation (ICC) coefficients were computed to bring out the similarities of pollutants' concentrations among these spatial units.
Multilevel models were used to examine the relationship between CABG surgery and cognitive decline over time.
In order to test the derived hypotheses, multilevel models were specified (see, inter alia, de Leeuw and Meijer 2010; Hox 2010; Raudenbush and Bryk 2002; Snijders and Bosker 2012).
Descriptive data and data regarding the microbiological outcome variables were analyzed using IBM SPSS Statistics 22 Version 22.0 (IBM Corp. Armonk, NY: IBM Corp .. Multilevel models were analyzed using MLwiN version 2.12 (Centre for Multilevel Modeling, University of Bristol, Bristol, UK).
Multilevel models were estimated using SAS version 9.2.
In this study multilevel models were used for similar reasons.
