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In educational studies the evaluation of longitudinal student performances has called for an increasing attention to identify critical aspects of students’ learning growth. Latent growth curve model and autoregressive model are the popular approaches to explain growth trend. However, in some cases, these models fail to fit data well and leave some pattern of change unexplained. The present study utilized a combination of latent growth curve model and autoregressive model to (1) estimate K-4 students’ reading achievement growth with time-invariant socioemotional covariates and (2) identify gender differences on the effects of socioemotional factors on growth trend of academic performance. We found that the autoregressive latent trajectory conditional on time-invariant covariates fits this data better than regular latent growth model.