Search thoroughlyUse many random starts and document likelihood replication.
Compare responsiblyRead information criteria, entropy, class size, and theory together.
Report uncertaintyInspect posterior probabilities instead of treating assignments as certain.

WHAT IS INSIDE

A complete latent profile workflow.

The package connects indicator review, model estimation, enumeration, classification quality, validation, visualization, and reporting in one reproducible report.

01

Prepare the indicators

Review distributions, missingness, correlations, scaling choices, and whether the variables support a person-centered question.

02

Fit candidate models

Estimate one- through six-profile diagonal Gaussian models with documented seeds and many random starts.

03

Evaluate enumeration

Compare AIC, BIC, adjusted BIC, likelihood-ratio evidence, convergence, class sizes, and substantive interpretability.

04

Assess classification

Review entropy, average posterior probabilities, individual uncertainty, and the limits of modal assignment.

05

Describe and validate profiles

Create standardized and original-scale summaries, accessible profile plots, and clearly labeled external comparisons.

06

Report the retained solution

Generate dynamic model-selection tables, profile summaries, figures, and APA-style results text from fitted results.

DESIGNED FOR DOCTORAL RESEARCH

Use it when combinations of continuous indicators are the research question.

This workflow is useful when:

  • You expect unobserved subgroups with different multivariate response patterns.
  • You need to compare several plausible profile solutions.
  • You want reproducible random-start and local-maximum checks.
  • You need to describe classification uncertainty and posterior probabilities.
  • Your committee expects transparent profile naming, validation, and reporting.

Longitudinal profiles, categorical indicators, sampling weights, nested data, distal outcomes, or complex auxiliary-variable methods require extensions beyond this introductory workflow.

PUBLIC PREVIEW

Review the complete analysis output.

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Latent Profile Analysis · Public Preview

The public preview shows the analysis output, figures, model-selection guidance, and dynamic reporting. The paid package includes the complete editable R Markdown source, reusable LPA module, all analysis code, synthetic data, documentation, and exported results.

THE DOWNLOADABLE PACKAGE

Run the example.
Then adapt your study.

The synthetic psychology dataset contains four known profiles across continuous indicators plus external variables for validation. The complete analysis runs before you introduce your own data.

  • Editable R Markdown source and rendered report
  • Reusable multi-start LPA module
  • Documented synthetic psychology dataset
  • Package installer and RStudio project
  • Enumeration and likelihood-replication tables
  • Classification-quality and posterior-probability diagnostics
  • Accessible standardized and original-scale profile plots
  • External validation and sensitivity guidance
  • Start guide, reporting checklist, and individual license

The workflow supports analysis and documentation. Profile enumeration, naming, validation, and use remain the researcher's responsibility and should be reviewed with the dissertation advisor, committee, or a qualified statistician.

VERSION 1.0

Complete workflow.
$59 one time.

Pay securely and receive the version 1.0 ZIP with the editable analysis, reusable LPA module, synthetic data, documentation, rendered report, and exported results.

Purchase for $59 Review purchase terms