The effects of autocorrelation on the curve-of-factors growth model

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a second model that included first-order autoregressive and moving average autocorrelation parameters. The results indicated that the estimates of the overall trend in the data were accurate regardless of model specification across most conditions. Variance components estimates were biased across many conditions but improved as sample size and series length increased. In general, the two models that incorporated autocorrelation parameters performed well when sample size and series length were large. The COFM had the best overal performance.