Prints the estimates, then the classification diagnostics, then draws every
plot the fit supports. A first look, not a substitute for the verbs: each
section is what summary(), diagnostics() and plot() return, and the
tables are reachable from those rather than from here.
Usage
report(
x,
data = NULL,
plots = TRUE,
by = c("profile", "overall"),
rows = 10L,
...
)Arguments
- x
A fitted model of this package.
- data
Optional. The data the model was fitted to; a fit carries the columns it was built from.
- plots
TRUE, the default, draws the plots.FALSEprints only.- by
Passed to
diagnostics(), and from there to the bivariate residuals:"profile", the default, assesses each profile separately,"overall"pools them.- rows
How many rows of each of the summary's tables to print, passed to
print(summary(x)). A first look at a fit with thousands of observations would otherwise be mostly posteriors.- ...
Nothing further is accepted. An argument this function cannot forward raises an error of class
latents_bad_argumentnaming it, before anything has been printed, rather than being dropped.
What it prints
summary(), which is every table the fit can
produce, then descriptives(), then the condensed reading of
diagnostics(), then every plot view the fit supports. Each section is
what that verb returns, and the tables are reached from get_results()
rather than from here.
Examples
fit <- multilpa(
course_engagement,
vars = c("browse", "lectures", "forum_read", "forum_post", "attendance"),
id = "student", n_profiles = 2, n_group_classes = 2, n_starts = 4,
seed = 1
)
report(fit, plots = FALSE)
#> Multilevel LPA: 2 profiles and 2 group classes
#> Individuals: 1422; groups: 106; parameters: 23; converged: TRUE
#> Log likelihood: -8439.816424; AIC: 16925.633
#> BIC (groups): 16986.892; BIC (individuals): 17046.609
#> Best likelihood replicated in 4/4 starts (absolute tolerance 0.00844).
#>
#> -- profiles --------------------------------------------------------
#> profile indicator mean variance standard_deviation mean_standard_error
#> 1 browse 0.5396 0.5899 0.7680 0.02710
#> 1 lectures 0.4274 0.8447 0.9191 0.03249
#> 1 forum_read 0.6198 0.4815 0.6939 0.02473
#> 1 forum_post 0.5305 0.6888 0.8299 0.02953
#> 1 attendance 0.6490 0.3841 0.6198 0.02226
#> 2 browse -0.7656 0.5285 0.7270 0.03121
#> 2 lectures -0.6065 0.5384 0.7337 0.03093
#> 2 forum_read -0.8792 0.3631 0.6026 0.02622
#> 2 forum_post -0.7527 0.4212 0.6490 0.02768
#> 2 attendance -0.9207 0.3736 0.6113 0.02643
#> variance_standard_error
#> 0.02948
#> 0.04210
#> 0.02440
#> 0.03482
#> 0.01956
#> 0.03222
#> 0.03209
#> 0.02279
#> 0.02608
#> 0.02279
#>
#> -- responses -------------------------------------------------------
#> (no rows)
#>
#> -- covariances -----------------------------------------------------
#> profile indicator indicator_2 covariance
#> 1 browse browse 0.5899
#> 1 lectures browse 0.0000
#> 1 forum_read browse 0.0000
#> 1 forum_post browse 0.0000
#> 1 attendance browse 0.0000
#> 1 browse lectures 0.0000
#> 1 lectures lectures 0.8447
#> 1 forum_read lectures 0.0000
#> 1 forum_post lectures 0.0000
#> 1 attendance lectures 0.0000
#> ... 40 more rows. get_results(x, what = "covariances")
#>
#> -- profile_probabilities -------------------------------------------
#> group_class profile probability group_class_probability
#> 1 1 0.7859 0.6747
#> 1 2 0.2141 0.6747
#> 2 1 0.1705 0.3253
#> 2 2 0.8295 0.3253
#>
#> -- counts ----------------------------------------------------------
#> level class effective_count effective_proportion
#> individuals 1 834.10 0.5866
#> individuals 2 587.90 0.4134
#> groups 1 71.52 0.6747
#> groups 2 34.48 0.3253
#>
#> -- posteriors ------------------------------------------------------
#> row group profile posterior modal
#> 1 1 1 9.996e-01 TRUE
#> 2 1 1 9.851e-01 TRUE
#> 3 1 1 2.421e-06 FALSE
#> 4 1 1 3.863e-06 FALSE
#> 5 1 1 5.749e-06 FALSE
#> 6 1 1 2.278e-05 FALSE
#> 7 1 1 2.301e-05 FALSE
#> 8 1 1 1.107e-05 FALSE
#> 9 1 1 2.173e-06 FALSE
#> 10 1 1 9.510e-06 FALSE
#> ... 2834 more rows. get_results(x, what = "posteriors")
#>
#> -- group_posteriors ------------------------------------------------
#> group group_size log_likelihood group_class posterior modal
#> 1 13 -61.52 1 1.473e-05 FALSE
#> 2 13 -71.94 1 6.391e-08 FALSE
#> 3 14 -76.69 1 1.000e+00 TRUE
#> 4 13 -67.56 1 1.000e+00 TRUE
#> 5 14 -78.80 1 1.248e-06 FALSE
#> 6 12 -80.90 1 9.802e-01 TRUE
#> 7 15 -89.36 1 1.000e+00 TRUE
#> 8 14 -85.22 1 1.067e-03 FALSE
#> 9 14 -83.80 1 1.000e+00 TRUE
#> 10 15 -82.06 1 1.565e-06 FALSE
#> ... 202 more rows. get_results(x, what = "group_posteriors")
#>
#> -- assignments -----------------------------------------------------
#> student browse lectures forum_read forum_post attendance profile group_class
#> 1 0.73 -0.08 0.30 0.67 0.72 1 2
#> 1 0.68 0.53 -0.02 -0.55 0.70 1 2
#> 1 -1.51 -0.51 -0.91 -0.80 -0.97 2 2
#> 1 0.64 -1.02 -1.62 -1.20 -1.26 2 2
#> 1 -0.94 -0.37 -0.71 -0.28 -1.52 2 2
#> 1 -0.36 -0.46 -0.77 -0.43 -1.34 2 2
#> 1 0.38 -1.85 -0.84 -1.09 -1.12 2 2
#> 1 -1.44 0.66 -0.67 -1.67 -1.00 2 2
#> 1 -0.76 -0.43 -1.04 -0.69 -1.37 2 2
#> 1 0.26 -0.95 -0.51 -1.89 -1.45 2 2
#> uncertainty posterior_profile_1 posterior_profile_2
#> 4.436e-04 9.996e-01 0.0004436
#> 1.485e-02 9.851e-01 0.0148536
#> 2.421e-06 2.421e-06 0.9999976
#> 3.863e-06 3.863e-06 0.9999961
#> 5.749e-06 5.749e-06 0.9999943
#> 2.278e-05 2.278e-05 0.9999772
#> 2.301e-05 2.301e-05 0.9999770
#> 1.107e-05 1.107e-05 0.9999889
#> 2.173e-06 2.173e-06 0.9999978
#> 9.510e-06 9.510e-06 0.9999905
#> ... 1412 more rows. get_results(x, what = "assignments")
#>
#> -- classification --------------------------------------------------
#> level class n_modal proportion_modal estimated_n estimated_proportion
#> individuals 1 836 0.5879 834.10 0.5866
#> individuals 2 586 0.4121 587.90 0.4134
#> groups 1 71 0.6698 71.52 0.6747
#> groups 2 35 0.3302 34.48 0.3253
#> average_posterior odds_correct_classification
#> 0.9849 46.08
#> 0.9818 76.35
#> 0.9920 59.89
#> 0.9690 64.80
#>
#> -- average_posteriors ----------------------------------------------
#> level assigned_class class n_assigned average_posterior
#> individuals 1 1 836 0.984935
#> individuals 1 2 836 0.015065
#> individuals 2 1 586 0.018243
#> individuals 2 2 586 0.981757
#> groups 1 1 71 0.992014
#> groups 1 2 71 0.007986
#> groups 2 1 35 0.031015
#> groups 2 2 35 0.968985
#>
#> -- classification_errors -------------------------------------------
#> level true_class assigned_class probability
#> individuals 1 1 0.98718
#> individuals 1 2 0.01282
#> individuals 2 1 0.02142
#> individuals 2 2 0.97858
#> groups 1 1 0.98482
#> groups 1 2 0.01518
#> groups 2 1 0.01644
#> groups 2 2 0.98356
#>
#> -- bch_weights -----------------------------------------------------
#> level unit assigned_class class weight
#> individuals 1 1 1 1.01327
#> individuals 1 1 2 -0.01327
#> individuals 2 1 1 1.01327
#> individuals 2 1 2 -0.01327
#> individuals 3 2 1 -0.02218
#> individuals 3 2 2 1.02218
#> individuals 4 2 1 -0.02218
#> individuals 4 2 2 1.02218
#> individuals 5 2 1 -0.02218
#> individuals 5 2 2 1.02218
#> ... 3046 more rows. get_results(x, what = "bch_weights")
#>
#> -- entropy ---------------------------------------------------------
#> level n_classes n_units entropy_sum relative_entropy
#> individuals 2 1422 60.940 0.9382
#> groups 2 106 4.435 0.9396
#>
#> -- residuals -------------------------------------------------------
#> profile indicator_1 indicator_2 kind observed expected residual
#> profile_1 lectures attendance gaussian 0.23393 0 0.23393
#> profile_2 forum_read attendance gaussian 0.22869 0 0.22869
#> profile_1 forum_read attendance gaussian 0.20880 0 0.20880
#> profile_1 forum_post attendance gaussian 0.20314 0 0.20314
#> profile_2 browse attendance gaussian 0.19248 0 0.19248
#> profile_1 browse attendance gaussian 0.17312 0 0.17312
#> profile_2 lectures attendance gaussian 0.12018 0 0.12018
#> profile_2 forum_post attendance gaussian 0.11883 0 0.11883
#> profile_2 browse forum_read gaussian 0.10925 0 0.10925
#> profile_2 forum_read forum_post gaussian 0.06676 0 0.06676
#> effective_n statistic df p_value p_adjusted
#> 834.1 6.871 NA 6.374e-12 6.374e-12
#> 587.9 5.630 NA 1.799e-08 1.799e-08
#> 834.1 6.109 NA 1.001e-09 1.001e-09
#> 834.1 5.939 NA 2.867e-09 2.867e-09
#> 587.9 4.714 NA 2.429e-06 2.429e-06
#> 834.1 5.042 NA 4.619e-07 4.619e-07
#> 587.9 2.921 NA 3.493e-03 3.493e-03
#> 587.9 2.888 NA 3.883e-03 3.883e-03
#> 587.9 2.653 NA 7.983e-03 7.983e-03
#> 587.9 1.617 NA 1.059e-01 1.059e-01
#> ... 10 more rows. get_results(x, what = "residuals")
#>
#> -- information_criteria --------------------------------------------
#> log_likelihood n_parameters aic kic bic_groups bic_individual sabic_groups
#> -8440 23 16926 16952 16987 17047 16914
#> sabic_individual caic_groups caic_individual awe_groups awe_individual
#> 16974 17010 17070 17172 17404
#> icl_groups icl_individual clc_groups clc_individual
#> 16996 17168 16889 17002
#>
#> -- model -----------------------------------------------------------
#> n_observations n_informative n_groups n_profiles n_group_classes centering
#> 1422 1422 106 2 2 none
#> covariance_structure n_parameters n_parameters_with_measurement log_likelihood
#> VVI 23 23 -8440
#> aic bic_groups bic_individual converged iterations boundary small_classes
#> 16926 16987 17047 TRUE 9 FALSE FALSE
#> best_start n_best_replicated weights
#> 1 4 <NA>
#>
#> -- stages ----------------------------------------------------------
#> stage group_classes fixed log_likelihood parameters
#> joint 2 <NA> -8440 23
#> parameters_with_measurement converged
#> 23 TRUE
#>
#> -- starts ----------------------------------------------------------
#> start log_likelihood converged iterations error boundary
#> 1 -8440 TRUE 9 <NA> FALSE
#> 2 -8440 TRUE 12 <NA> FALSE
#> 3 -8440 TRUE 9 <NA> FALSE
#> 4 -8440 TRUE 12 <NA> FALSE
#>
#> -- data ------------------------------------------------------------
#> student browse lectures forum_read forum_post attendance
#> 1 0.73 -0.08 0.30 0.67 0.72
#> 1 0.68 0.53 -0.02 -0.55 0.70
#> 1 -1.51 -0.51 -0.91 -0.80 -0.97
#> 1 0.64 -1.02 -1.62 -1.20 -1.26
#> 1 -0.94 -0.37 -0.71 -0.28 -1.52
#> 1 -0.36 -0.46 -0.77 -0.43 -1.34
#> 1 0.38 -1.85 -0.84 -1.09 -1.12
#> 1 -1.44 0.66 -0.67 -1.67 -1.00
#> 1 -0.76 -0.43 -1.04 -0.69 -1.37
#> 1 0.26 -0.95 -0.51 -1.89 -1.45
#> ... 1412 more rows. get_results(x, what = "data")
#>
#> 19 tables above, truncated to fit. get_results(x, what = ) returns any
#> of them whole, and get_results(x, what = "all") returns every one.
#>
#> variable n n_missing mean sd min max n_distinct
#> 1 browse 1422 0 -2.812940e-05 0.9890804 -3.14 2.49 398
#> 2 lectures 1422 0 -4.219409e-05 0.9889178 -2.91 3.22 399
#> 3 forum_read 1422 0 7.032349e-05 0.9890236 -2.73 2.81 400
#> 4 forum_post 1422 0 -2.109705e-05 0.9890038 -2.61 3.10 397
#> 5 attendance 1422 0 7.735584e-05 0.9889426 -2.45 2.41 401
#> n_groups icc
#> 1 106 0.19229259
#> 2 106 0.08779169
#> 3 106 0.22403384
#> 4 106 0.15034618
#> 5 106 0.22145308
#>
#> Classification quality: 2 profiles, 2 group classes
#>
#> Relative entropy individuals 0.938 groups 0.940
#> Smallest class individuals 587.9 (41.3%) groups 34.5 (32.5%)
#> Lowest avg posterior individuals 0.982 groups 0.969
#> Largest residual 0.234 (lectures, attendance; profile_1)
#>
#> Tables: get_results(x, what = "entropy" | "classification" |
#> "average_posteriors" | "residuals" | "all"). plot(x) draws them.