Bootstrap the likelihood-ratio test statistic for mixture components

bootstrap_lrt(df, ..., n_profiles, model = 1)



data.frame with two or more columns with continuous variables


unquoted variable names separated by commas


the number of profiles (or mixture components) to be estimated


the mclust model to explore: 1 (varying means, equal variances, and residual covariances fixed to 0); 2 (varying means, equal variances and covariances; 3 (varying means and variances, covariances fixed to 0), 4 (varying means and covariances, equal variances; can only be specified in Mplus); 5 (varying means, equal variances, varying covariances); and 6 (varying means, variances, and covariances), in order least to most freely-estimated; see the introductory vignette for more information


Bootstrap the p-values for the likelihood-ratio test statistic for the number of mixture components for an mclust model.


not_run({ d <- pisaUSA15 d <- dplyr::sample_n(d, 200) bootstrap_lrt(d, broad_interest, enjoyment, self_efficacy) })