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GMM/Evidence
Method evidence record

GMM

The Growth Mixture Model, introduced by Muthén and Shedden in 1999, is a longitudinal latent variable method that identifies distinct subpopulations — latent trajectory classes — each following its own growth curve over time. It extends the standard Latent Growth Curve (LGC) model by allowing the sample to be composed of an unknown mixture of classes with different intercepts, slopes, and variance structures.

Sources recorded, not reviewed

Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Growth Mixture Model
Taxonomic method record · latent-structure / statistics
  • Muthén, B. O. & Shedden, K. (1999). Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm. Biometrics, 55(2), 463–469. · DOI 10.1111/j.0006-341x.1999.00463.x
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

No curated claims yet

This view does not invent a claim assessment when the ledger has none.

Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyEFAmachine-suggested · Relational suggestion, not evidence.Used in the same domainHierarchical Linear Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyLCAmachine-suggested · Relational suggestion, not evidence.Used in the same domainMultiple Imputationmachine-suggested · Relational suggestion, not evidence.Same method familySEMmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

1 recorded citation, copied from the method source record.

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