Numerous studies have shown increasing item reliabilities as an effect of the item position in personality scales. Traditionally, these context effects are analyzed based on item-total correlations. This approach neglects that trends in item reliabilities can be caused either by an increase in true score variance or by a decrease in error variance. This article presents the Confirmatory Analysis of Item Reliability Trends (CAIRT) that allows estimating both trends separately within a structural equation modeling framework. Results of a simulation study prove the CAIRT method to provide reliable and independent parameter estimates; the power exceeds the analysis of item-total correlations. We present an empirical application to self- and peer ratings collected in an Internet-based experiment. Results show that reliability trends are caused by increasing true score variance in self-ratings and by decreasing error variance in peer ratings.