Table 4: Posttraumatic Stress in Young Children at Risk for Maltreatment

LONGSCAN consortium data features a sample of 1,354 children identified in infancy to early childhood as being maltreated or at risk. Glenn N. Saxe applied Causal Data Science methods to this longitudinal observational dataset to model the etiology of Posttraumatic Stress. The resulting causal network model contains 251 variables and 818 bivariate relations.

Use Cases

• Causal network discovery based on 251 variables and 818 bivariate relations.
• Longitudinal analysis of child development based on data collected from infancy to age 8.
• Risk factor modeling for Posttraumatic Stress based on variables like Emotional Maltreatment and Witnessing Violence.
• Validation of Causal Data Science methods against traditional correlational research in psychology.

Strengths

• Dataset contains 1,354 child records, providing a substantial sample size.
• Causal network model is explicitly defined with 251 nodes and 818 edges.
• Data is longitudinal, tracking children from infancy to age 8.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the specific table is unknown, which may limit suitability assessment.
• The 8.4 KB file size suggests a very limited scope, likely containing summary results rather than raw data.

Provenance

Source

Consortium for Longitudinal Studies in Child Abuse and Neglect (LONGSCAN).

Collection Method

Observational, longitudinal data collection.

Time Range

Covers from infancy to age 8 for the child cohort.

Freshness

Last updated 2026-04-22 05:49:28; freshness should be verified.