thumb|A cross-lagged longitudinal MZ discordant twin design. This model can take account of relationships among differences across traits at time one, and then examine the distinct hypotheses that increments in trait1 drive subsequent change in that trait in the future, or, importantly, in other traits. As may be seen in the next Figure, this design can be extended to multiple measurements, with consequent increase in the kinds of information that one can learn. This is called a cross-lagged model (multiple traits measured over more than one time).
thumb|A cross-lagged longitudinal MZ discordant twin design. This model can take account of relationships among differences across traits at time one, and then examine the distinct hypotheses that increments in trait1 drive subsequent change in that trait in the future, or, importantly, in other traits. As may be seen in the next Figure, this design can be extended to multiple measurements, with consequent increase in the kinds of information that one can learn. This is called a cross-lagged model (multiple traits measured over more than one time).