Analysis of the cross-effects in a cross-lagged panel study

Panel studies are statistical studies in which two or more variables are observed for two or more subjects at two or more points in time, Cross-lagged panel studies are comprised of continuous variables which divide naturally into two sets, and often the primary statistical issue is to estimate and test the cross-effects which indicate the degree to which each set is related to the other over time. By taking a regression approach to modeling the relationships, we apply multivariate regression methodology to make inferences about the regression coefficients in a cross-lagged panel model. In particular we develop a test of the hypothesis that the regression coefficients indicating the cross-effects are equal and develop simultaneous confidence bounds for various linear combinations of these regression coefficients.