I provide advanced Latent Profile Analysis (LPA) and mixture modeling for research studies, PhD dissertations, and applied data projects.
As a PhD-qualified statistical consultant, I support researchers and analysts in identifying hidden population segments using rigorous model-based clustering approaches. My work focuses on producing statistically defensible and publication-ready results using Mplus, R, and IBM SPSS.
Latent Profile Analysis is widely used in psychology, marketing, health sciences, education, and social science research to uncover latent subgroups within complex datasets.
I can assist with:
• Latent Profile Analysis (LPA) model estimation
• Mixture modeling and model comparison
• Model selection using AIC, BIC, entropy, and likelihood ratio tests
• Conditional LPA with covariates using R3STEP procedures
• Distal outcome analysis using BCH methods
• Interpretation of latent classes and profile structures
• Preparation of publication-ready statistical tables
Typical deliverables include:
• Mplus syntax and model outputs
• Reproducible R scripts (if required)
• Model comparison tables and diagnostics
• Clear interpretation of latent profiles for research reports or manuscripts
My approach emphasizes methodological rigor, transparent modeling decisions, and reproducible statistical workflows.
If you require reliable support for Latent Profile Analysis, mixture modeling, or advanced quantitative research, I would be glad to assist with your project.