Background on Latent Profile Analysis (LPA) | Description of the goals of tidyLPA | Software approach to carrying out LPA: Interface to mclust (and to MPlus) | Example | Installation | Mclust | Mplus | Comparing a wide range of solutions | Passing additional arguments | More information on model specifications | Model specification | 1. Equal variances, and covariances fixed to 0 (model 1) | 2. Varying variances and covariances fixed to 0 (model 2) | 3. Equal variances and equal covariances (model 3) | 4. Varying means, varying variances, and equal covariances (model 4) | 5. Varying means, equal variances, and varying covariances (model 5) | 6. Varying variances and varying covariances (model 6) | Other functionality | Getting estimates | Getting data | Getting fit statistics | Acknowledgments

Quantifying the Robustness of Inferences | Functionality | konfound | Example for linear models fit with lm() | ITCV example for linear models fit with lm() | RIR example for linear models fit with lm() | pkonfound | ITCV example for a regression analysis | RIR example for a regression analysis | Doing and Learning More | Acknowledgements | References

Purpose | Using mclust | Just one fit | Using MPlus | Many fits

Example