I will perform lpa lca analysis with r3step and bch in mplus and r

Please provide your research question, sample size, indicator variables, variable types and coding, missing-data information, and any proposed covariates or distal outcomes. An anonymized dataset, codebook, and previous output are helpful.

LPA is generally used with continuous indicators, while LCA is generally used with categorical indicators. I can review your variables and research question and recommend the appropriate approach.

I primarily use Mplus and R. The software will be selected according to the model, indicator types, auxiliary-variable requirements, and required outputs.

Yes. I compare candidate solutions using fit indices, likelihood-ratio tests, entropy, class sizes, convergence, local maxima, theoretical meaning, separation, and interpretability.

No. The selected solution must be supported by the data, statistical evidence, theory, stability, and substantive interpretability. I do not force a preferred class solution.

Yes. Covariates may be examined using R3STEP and distal outcomes using BCH where appropriate. The number, type, and coding of auxiliary variables must be agreed before ordering.

Yes. I can review syntax, output, convergence problems, local maxima, fit indices, class sizes, model-comparison results, and interpretation. Extensive reanalysis may require a custom offer.

A revision covers correction or clarification within the agreed indicator set, class range, covariates, outcomes, and deliverables. New variables, models, datasets, or class-enumeration strategies are additional work.

Yes. I can support statistical Methods/Results, model-selection justification, interpretation, publication-ready tables, and statistical reviewer responses within the agreed LPA/LCA scope.