Report of the Mplus Working Group on Issues regarding Change in Cognition Psychometrics Working Group Friday Harbor Laboratories September 21-24, 2005 Members of the Mplus group included Rosemary Abbott Dagmar Amtmann Mark Chatfield Rich Jones Carla Sharp Doug Tommett (did I forget anyone?) Dagmar Amtmann has slides regarding Mplus Growth Mixture Modeling of these data.

Single-Group Latent Growth Modeling

Single-Group Latent Growth Modeling

The results for the MG-LGM with regard to the influence of ApoE4 presence on the rate of cognitive chance implied that ApoE4 contributed to the pace of accumulation of impaired cognition, but had little apparent effect among the youngest old.

y h Multiple Group LGM e z L = 1 2 3 9 [ a ] (4) (5) age-65 (1) (2) p We implemented a multiple-group (MG) latent growth model (LGM) of cognitive change as a function of study year. Notes about this path diagram: - p=9, where p is the number of observed dependent variables (repeated assessments) - Numbers in parenthesis identify parameter constraints. In Mplus, the # that identifies the constraint is nominal. In this diagram, the number used to assign the constraint for the residual variances of the observed variables are also equal to the age of observation. - 18 groups were included: groups were defined by year of birth (group 1 = age 65 in 1989, group 18 = age 82 in 1989). Group 1 was 73 at last observation, group 18 was 90 at last observation. - The means of initial status [a1] and rate of change [a2] are held constant across groups, as are their disturbance terms. Differences across groups in terms of where people in different birth cohorts are handled by different values for the time steps in the lambda matrix. - Time steps in the lambda matrix correspond to the age at which persons were measured. Send email to Rich Jones for the text of the Mplus command file (jones@mail.hrca.harvard.edu). Future work will involve specifying a quadratic MG-LGM for these data.