Fig 1.
Path diagram of conditional latent growth mixture model (LGMM).
The y variable represents observed outcome in each time point, ε is the error term, and the factor loadings are placed on the arrows.
Table 1.
Descriptive statistics of RTA death rates and HDI.
Table 2.
Parameter estimates and fit indices of different LGMs.
Fig 2.
Overall growth trajectories of observed and estimated mean of RTA death rates.
(a) Unconditional nonlinear LGM, the estimated line is the same as the observed line (b) Unconditional linear LGM (c) conditional nonlinear LGM (d) conditional linear LGM.
Table 3.
Goodness of fit indices for the fitted growth mixture models.
Table 4.
Results of the fitted 7-class unconditional growth mixture model to the RTA death rate data.
Fig 3.
Observed and estimated mean growth trajectories of RTA death rates by 7-class.
Fig 4.
The adjusted estimate and observed growth trajectories of RTA rates by HDI in seven classes.
Table 5.
Results of the fitted 7-class conditional growth mixture model to the RTA death rate data.