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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
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Family Variables: Latent Class & Latent Transtion
Alan C. AcockPresented at the Conference on Research with
Dyads and familiesPurdue University
May, 2010
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Family Variables• Demographic variables are often
considered family variables• Household income• Ethnicity• Location
• Family variables because they influence opportunity structure of all family members
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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
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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
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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
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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
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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?
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From Variable to Person to Family Centered
Analysis
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From Variable to Person to Family Centered
Analysis
TextTextTextText
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.
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From Variable to Person to Family Centered Analysis
• Individual Level Variable: An Attitude• Multiple indicators • May have multiple informants
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From Variable to Person to Family Centered Analysis
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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
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Latent Class Analysis of Family Level Variables
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Latent Class Analysis of Family Level Variables
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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
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Latent Class Analysis of Family Level Variables
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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
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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
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Classes Applied to aVariable Centered
Approach
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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
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An Auto-Regressive Model: Latent Transition
Analysis
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LTA with Antecedent Covariates & Distal Outcomes
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LTA with Mover-Stayer Latent Transition Model
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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
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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
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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
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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
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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?
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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
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Summary
• The mover-stayer model identifies classes of people who are moved and those who are not.
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