1. 1 Family Variables: Latent Class & Latent Transtion Alan C. Acock Presented at the Conference on Research with Dyads and families Purdue University May, 2010

2. 2 Family Variables Demographic variables are often considered family variables Household income Ethnicity Location Family variables because they influence opportunity structure of all family members

3. 3 A family variable Individuals characteristics & actions may create family variables These are family variables because they locate the opportunity structure of all family members, not just the individual A child with a profound disability A parent who is incarcerated

4. 4 From Variable to Person to Family Centered Analysis Most research is variable centered a single dependent variable Marital happiness What other variables predict Number of children Spouse’s social support

5. 5 From Variable to Person to Family Centered Analysis Variable Centered research can be extended Multiple outcomes, Longitudinal Analysis Including family level variables Variables about other family members This is still variable centered

6. 6 From Variable to Person to Family Centered Analysis A variable’s distribution may belie the fact that there are multiple distributions of the variable Person centered analysis identifies clusters of people who have fundamentally different distributions

7. 7 From Variable to Person to Family Centered Analysis A high school may have a distribution on a standardized test Person centered research says there may be two or more distributions What explains the distribution in which a person is located? What outcomes flow from the distribution in which a person is located?

8. 8 From Variable to Person to Family Centered Analysis

9. 9 Text Schaeffer, C.M., Petras, H., Ialongo, N., Poduska, J. & Kellam, S. (2003). Modeling growth in boys aggressive behavior across elementary school: Links to later criminal involvement, conduct disorder, and antisocial personality disorder. Developmental Psychology, 39, 1020- 1035.

10. 10 From Variable to Person to Family Centered Analysis Individual Level Variable: An Attitude Multiple indicators May have multiple informants

11. 11 From Variable to Person to Family Centered Analysis

12. 12 Latent Class Analysis of Family Level Variables Identify Subsets of families who have fundamentally different distributions on variables Latent Classes are homogeneous within clusters Latent Classes are heterogeneous between clusters

13. 13 Latent Class Analysis of Family Level Variables

14. 14 Latent Class Analysis of Family Level Variables

15. 15 Latent Class Analysis of Family Level Variables We may want to know what causes a families to be in one class rather than another We may want to know what are the consequences of class membership for individual members as well as the family

16. 16 Latent Class Analysis of Family Level Variables

17. 17 Mixture Models & Longitudinal Analysis LCA is a special type of Mixture modeling Mixture modeling identifies latent classes in any type of analysis There are two broad classes of mixture modeling for longitudinal analysis

18. 18 Classes Applied to a Variable Centered Approach We construct a growth curve Then will see if there are two or more latent classes that Are heterogeneous across classes Have homogeneous growth trajectories within classes

19. 19 Classes Applied to aVariable Centered Approach

20. 20 An Auto-Regressive Model: Latent Transition Analysis LTA begins with latent classes Identifies how these classes are stable and how they change over time Focus is on transitions over time

21. 21 An Auto-Regressive Model: Latent Transition Analysis

22. 22 LTA with Antecedent Covariates & Distal Outcomes

23. 23 LTA with Mover-Stayer Latent Transition Model

24. 24 Summary Family variables are scores attached to families that influence any and all family members We can treat family members, e.g., mother, father, focal child as multiple informants

25. 25 Summary Mixture Models identify clusters of units being analyszed that are homogeneous within clusters and heterogeneous between clusters Latent class analysi (LCA) identifies these clusters of families or whatever unit of analysis is used

26. 26 Summary Clusters may be ordinal such as strong moderate and challenged Clusters may be dis-ordinal where one cluster has different strengths than another cluster

27. 27 Summary Research should identify sets of covariates that lead to membership in different clusters Research should identify sets of outcomes that are caused by cluster membership

28. 28 Summary Latent transition analysis is an alternative to growth models as a way of studying change LTA focuses on transitions between classes. Why do some families move toward increased solidarity when their oldest child becomes an adolescent?

29. 29 Summary Research should identify sets of covariates that differentiate what class a family is in Research should identify sets of outcomes that very with the class the family is in

30. 30 Summary The mover-stayer model identifies classes of people who are moved and those who are not.