The cross-lagged panel model is a type of discrete time structural equation model used to analyze panel data in which two or more variables are repeatedly measured at two or more different time points.
This model aims to estimate the directional effects that one variable has on another at different points in time.
[1][2] This model was first introduced in 1963 by Donald T. Campbell and refined during the 1970s by David A.
"[4] Though this approach is commonly believed to be a valid technique to identify causal relationships from panel data, its use for this purpose has been criticized, as it depends on certain assumptions, such as synchronicity and stationarity, that may not be valid.
This statistics-related article is a stub.