Mental health
Dimensionality
How many factors should
#unidimensionality of total item pool
(unidem_all = unidim(
mh_vars_num,
cor = "mixed"
))
## Warning in polychoric(data[, p], smooth = smooth, global = global, weight =
## weight, : The items do not have an equal number of response alternatives,
## global set to FALSE.
## Warning in matpLower(x, nvar, gminx, gmaxx, gminy, gmaxy): 271 cells were
## adjusted for 0 values using the correction for continuity. Examine your data
## carefully.
## Warning in cor.smooth(mat): Matrix was not positive definite, smoothing was
## done
## Warning in polydi(data[, p, drop = FALSE], data[, d, drop = FALSE], global =
## global, : The items do not have an equal number of response alternatives, I am
## setting global to FALSE
## In smc, smcs > 1 were set to 1.0
## In smc, smcs < 0 were set to .0
## In smc, smcs > 1 were set to 1.0
## In smc, smcs < 0 were set to .0
## In smc, smcs > 1 were set to 1.0
## In smc, smcs < 0 were set to .0
## Warning in cor.smooth(r): Matrix was not positive definite, smoothing was done
## Warning in fa.stats(r = r, f = f, phi = phi, n.obs = n.obs, np.obs = np.obs, :
## The estimated weights for the factor scores are probably incorrect. Try a
## different factor score estimation method.
## In smc, smcs > 1 were set to 1.0
## In smc, smcs < 0 were set to .0
## In smc, smcs > 1 were set to 1.0
## In smc, smcs < 0 were set to .0
## In smc, smcs > 1 were set to 1.0
## In smc, smcs < 0 were set to .0
## Warning in cor.smooth(r): Matrix was not positive definite, smoothing was done
## Warning in cor.smooth(r): The estimated weights for the factor scores are
## probably incorrect. Try a different factor score estimation method.
##
## A measure of unidimensionality
## Call: unidim(keys = mh_vars_num, cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.74 0.81 0.91 0.98 0.37 0.37 0.11 0.73
## F1/F2 MAP
## 4.04 0.04
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
#without diagnoses
(unidem_symptoms = unidim(
#subset to non-diagnoses
mh_vars_num %>% select(all_of(mh_vars_symptoms)),
cor = "mixed"
))
## Warning in polychoric(data[, p], smooth = smooth, global = global, weight =
## weight, : The items do not have an equal number of response alternatives,
## global set to FALSE.
## Warning in matpLower(x, nvar, gminx, gmaxx, gminy, gmaxy): 271 cells were
## adjusted for 0 values using the correction for continuity. Examine your data
## carefully.
## Warning in polydi(data[, p, drop = FALSE], data[, d, drop = FALSE], global =
## global, : The items do not have an equal number of response alternatives, I am
## setting global to FALSE
## In smc, smcs > 1 were set to 1.0
## In smc, smcs > 1 were set to 1.0
## In smc, smcs > 1 were set to 1.0
## Warning in cor.smooth(r): Matrix was not positive definite, smoothing was done
## In smc, smcs > 1 were set to 1.0
## In smc, smcs > 1 were set to 1.0
## In smc, smcs > 1 were set to 1.0
## Warning in cor.smooth(r): Matrix was not positive definite, smoothing was done
##
## A measure of unidimensionality
## Call: unidim(keys = mh_vars_num %>% select(all_of(mh_vars_symptoms)),
## cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.80 0.85 0.93 0.98 0.44 0.45 0.32 0.77
## F1/F2 MAP
## 3.99 0.05
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
#diagnoses only
(unidem_diag = unidim(
#subset to diagnoses
mh_vars_num %>% select(-all_of(mh_vars_symptoms)),
cor = "mixed"
))
## Warning in cor.smooth(mat): Matrix was not positive definite, smoothing was
## done
## In smc, smcs < 0 were set to .0
## In smc, smcs < 0 were set to .0
## In smc, smcs < 0 were set to .0
## In smc, smcs < 0 were set to .0
## In smc, smcs < 0 were set to .0
## In smc, smcs < 0 were set to .0
##
## A measure of unidimensionality
## Call: unidim(keys = mh_vars_num %>% select(-all_of(mh_vars_symptoms)),
## cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.75 0.84 0.89 0.92 0.39 0.40 0.07 0.71
## F1/F2 MAP
## 3.91 0.07
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
#MMPI items
(unidem_mmpi = unidim(
mh_vars_num %>% select(
Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen:I_get_all_the_sympathy_I_should
),
cor = "mixed"
))
##
## A measure of unidimensionality
## Call: unidim(keys = mh_vars_num %>% select(Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen:I_get_all_the_sympathy_I_should),
## cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.91 0.94 0.97 0.96 0.51 0.51 0.66 0.83
## F1/F2 MAP
## 6.16 0.04
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
#last 2 weeks items
(unidem_last2weeks = unidim(
mh_vars_num %>% select(
Little_interest_or_pleasure_in_doing_things:Using_any_of_the_following_medicines_ON_YOUR_OWN
),
cor = "mixed"
))
##
## A measure of unidimensionality
## Call: unidim(keys = mh_vars_num %>% select(Little_interest_or_pleasure_in_doing_things:Using_any_of_the_following_medicines_ON_YOUR_OWN),
## cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.91 0.93 0.98 0.96 0.54 0.56 0.73 0.84
## F1/F2 MAP
## 6.33 0.04
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
#satisfaction questions
(unidem_satisfaction = unidim(
mh_vars_num %>% select(
Life_satisfaction:If_I_could_live_my_life_over_I_would_change_almost_nothing
),
cor = "mixed"
))
##
## A measure of unidimensionality
## Call: unidim(keys = mh_vars_num %>% select(Life_satisfaction:If_I_could_live_my_life_over_I_would_change_almost_nothing),
## cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.93 0.93 1.00 0.95 0.63 0.65 0.92 0.92
## F1/F2 MAP
## 8.44 0.04
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
All items
#fit a full model with all items of all types
irt_mh_all = mirt(
mh_vars_num,
itemtype = mh_vars_options$itemtype,
model = 1
)
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Max-Change: 0.00025Iteration: 234, Log-Lik: -49933.038, Max-Change: 0.00022Iteration: 235, Log-Lik: -49933.038, Max-Change: 0.00031Iteration: 236, Log-Lik: -49933.038, Max-Change: 0.00057Iteration: 237, Log-Lik: -49933.037, Max-Change: 0.00046Iteration: 238, Log-Lik: -49933.037, Max-Change: 0.00026Iteration: 239, Log-Lik: -49933.037, Max-Change: 0.00019Iteration: 240, Log-Lik: -49933.037, Max-Change: 0.00015Iteration: 241, Log-Lik: -49933.037, Max-Change: 0.00050Iteration: 242, Log-Lik: -49933.037, Max-Change: 0.00076Iteration: 243, Log-Lik: -49933.037, Max-Change: 0.00065Iteration: 244, Log-Lik: -49933.036, Max-Change: 0.00037Iteration: 245, Log-Lik: -49933.036, Max-Change: 0.00055Iteration: 246, Log-Lik: -49933.036, Max-Change: 0.00047Iteration: 247, Log-Lik: -49933.036, Max-Change: 0.00025Iteration: 248, Log-Lik: -49933.036, Max-Change: 0.00019Iteration: 249, Log-Lik: -49933.036, Max-Change: 0.00017Iteration: 250, Log-Lik: -49933.035, Max-Change: 0.00037Iteration: 251, Log-Lik: -49933.035, Max-Change: 0.00066Iteration: 252, Log-Lik: -49933.035, Max-Change: 0.00054Iteration: 253, Log-Lik: -49933.035, Max-Change: 0.00024Iteration: 254, Log-Lik: -49933.035, Max-Change: 0.00040Iteration: 255, Log-Lik: -49933.035, Max-Change: 0.00032Iteration: 256, Log-Lik: -49933.035, Max-Change: 0.00024Iteration: 257, Log-Lik: -49933.034, Max-Change: 0.00037Iteration: 258, Log-Lik: -49933.034, Max-Change: 0.00065Iteration: 259, Log-Lik: -49933.034, Max-Change: 0.00037Iteration: 260, Log-Lik: -49933.034, Max-Change: 0.00055Iteration: 261, Log-Lik: -49933.034, Max-Change: 0.00047Iteration: 262, Log-Lik: -49933.034, Max-Change: 0.00023Iteration: 263, Log-Lik: -49933.033, Max-Change: 0.00025Iteration: 264, Log-Lik: -49933.033, Max-Change: 0.00022Iteration: 265, Log-Lik: -49933.033, Max-Change: 0.00023Iteration: 266, Log-Lik: -49933.033, Max-Change: 0.00037Iteration: 267, Log-Lik: -49933.033, Max-Change: 0.00030Iteration: 268, Log-Lik: -49933.033, Max-Change: 0.00022Iteration: 269, Log-Lik: -49933.033, Max-Change: 0.00040Iteration: 270, Log-Lik: -49933.032, Max-Change: 0.00071Iteration: 271, Log-Lik: -49933.032, Max-Change: 0.00024Iteration: 272, Log-Lik: -49933.032, Max-Change: 0.00035Iteration: 273, Log-Lik: -49933.032, Max-Change: 0.00030Iteration: 274, Log-Lik: -49933.032, Max-Change: 0.00021Iteration: 275, Log-Lik: -49933.032, Max-Change: 0.00042Iteration: 276, Log-Lik: -49933.032, Max-Change: 0.00063Iteration: 277, Log-Lik: -49933.031, Max-Change: 0.00021Iteration: 278, Log-Lik: -49933.031, Max-Change: 0.00040Iteration: 279, Log-Lik: -49933.031, Max-Change: 0.00032Iteration: 280, Log-Lik: -49933.031, Max-Change: 0.00021Iteration: 281, Log-Lik: -49933.031, Max-Change: 0.00023Iteration: 282, Log-Lik: -49933.031, Max-Change: 0.00032Iteration: 283, Log-Lik: -49933.031, Max-Change: 0.00043Iteration: 284, Log-Lik: -49933.031, Max-Change: 0.00075Iteration: 285, Log-Lik: -49933.030, Max-Change: 0.00061Iteration: 286, Log-Lik: -49933.030, Max-Change: 0.00036Iteration: 287, Log-Lik: -49933.030, Max-Change: 0.00063Iteration: 288, Log-Lik: -49933.030, Max-Change: 0.00052Iteration: 289, Log-Lik: -49933.030, Max-Change: 0.00026Iteration: 290, Log-Lik: -49933.030, Max-Change: 0.00047Iteration: 291, Log-Lik: -49933.030, Max-Change: 0.00038Iteration: 292, Log-Lik: -49933.030, Max-Change: 0.00019Iteration: 293, Log-Lik: -49933.030, Max-Change: 0.00021Iteration: 294, Log-Lik: -49933.030, Max-Change: 0.00016Iteration: 295, Log-Lik: -49933.029, Max-Change: 0.00025Iteration: 296, Log-Lik: -49933.029, Max-Change: 0.00036Iteration: 297, Log-Lik: -49933.029, Max-Change: 0.00031Iteration: 298, Log-Lik: -49933.029, Max-Change: 0.00019Iteration: 299, Log-Lik: -49933.029, Max-Change: 0.00021Iteration: 300, Log-Lik: -49933.029, Max-Change: 0.00038Iteration: 301, Log-Lik: -49933.029, Max-Change: 0.00041Iteration: 302, Log-Lik: -49933.029, Max-Change: 0.00063Iteration: 303, Log-Lik: -49933.029, Max-Change: 0.00053Iteration: 304, Log-Lik: -49933.029, Max-Change: 0.00033Iteration: 305, Log-Lik: -49933.028, Max-Change: 0.00050Iteration: 306, Log-Lik: -49933.028, Max-Change: 0.00043Iteration: 307, Log-Lik: -49933.028, Max-Change: 0.00022Iteration: 308, Log-Lik: -49933.028, Max-Change: 0.00032Iteration: 309, Log-Lik: -49933.028, Max-Change: 0.00028Iteration: 310, Log-Lik: -49933.028, Max-Change: 0.00088Iteration: 311, Log-Lik: -49933.027, Max-Change: 0.00017Iteration: 312, Log-Lik: -49933.027, Max-Change: 0.00025Iteration: 313, Log-Lik: -49933.027, Max-Change: 0.00040Iteration: 314, Log-Lik: -49933.027, Max-Change: 0.00061Iteration: 315, Log-Lik: -49933.027, Max-Change: 0.00051Iteration: 316, Log-Lik: -49933.027, Max-Change: 0.00034Iteration: 317, Log-Lik: -49933.027, Max-Change: 0.00052Iteration: 318, Log-Lik: -49933.027, Max-Change: 0.00044Iteration: 319, Log-Lik: -49933.027, Max-Change: 0.00026Iteration: 320, Log-Lik: -49933.027, Max-Change: 0.00039Iteration: 321, Log-Lik: -49933.027, Max-Change: 0.00034Iteration: 322, Log-Lik: -49933.027, Max-Change: 0.00016Iteration: 323, Log-Lik: -49933.026, Max-Change: 0.00020Iteration: 324, Log-Lik: -49933.026, Max-Change: 0.00017Iteration: 325, Log-Lik: -49933.026, Max-Change: 0.00016Iteration: 326, Log-Lik: -49933.026, Max-Change: 0.00019Iteration: 327, Log-Lik: -49933.026, Max-Change: 0.00015Iteration: 328, Log-Lik: -49933.026, Max-Change: 0.00016Iteration: 329, Log-Lik: -49933.026, Max-Change: 0.00022Iteration: 330, Log-Lik: -49933.026, Max-Change: 0.00019Iteration: 331, Log-Lik: -49933.026, Max-Change: 0.00015Iteration: 332, Log-Lik: -49933.026, Max-Change: 0.00013Iteration: 333, Log-Lik: -49933.026, Max-Change: 0.00010Iteration: 334, Log-Lik: -49933.026, Max-Change: 0.00026Iteration: 335, Log-Lik: -49933.026, Max-Change: 0.00038Iteration: 336, Log-Lik: -49933.026, Max-Change: 0.00033Iteration: 337, Log-Lik: -49933.026, Max-Change: 0.00015Iteration: 338, Log-Lik: -49933.026, Max-Change: 0.00021Iteration: 339, Log-Lik: -49933.026, Max-Change: 0.00019Iteration: 340, Log-Lik: -49933.026, Max-Change: 0.00015Iteration: 341, Log-Lik: -49933.025, Max-Change: 0.00011Iteration: 342, Log-Lik: -49933.025, Max-Change: 0.00008
irt_mh_all
##
## Call:
## mirt(data = mh_vars_num, model = 1, itemtype = mh_vars_options$itemtype)
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 342 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -49933
## Estimated parameters: 276
## AIC = 1e+05
## BIC = 101766; SABIC = 100890
irt_mh_all %>% summary()
## F1
## Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen 0.809
## Most_of_the_time_I_feel_blue 0.884
## I_often_feel_as_if_things_were_not_real 0.683
## I_sometimes_feel_that_I_am_about_to_go_to_pieces 0.819
## Even_when_I_am_with_people_I_feel_lonely_much_of_the_time 0.832
## I_feel_that_I_have_often_been_punished_without_cause 0.761
## Life_is_a_strain_for_me_much_of_the_time 0.864
## I_have_strange_and_peculiar_thoughts 0.625
## My_plans_have_frequently_seemed_so_full_of_difficulties_that_I_have_had_to_give_them_up 0.817
## Often_even_though_everything_is_going_fine_for_me_I_feel_that_I_don_t_care_about_anything 0.747
## I_do_many_things_which_I_regret_afterwards_I_regret_things_more_or_more_often_than_others_seem_to 0.712
## At_times_I_think_I_am_no_good_at_all 0.810
## I_have_often_felt_that_strangers_were_looking_at_me_critically 0.693
## I_am_happy_most_of_the_time 0.787
## I_very_seldom_have_spells_of_the_blues 0.658
## During_the_past_few_years_I_have_been_well_most_of_the_time 0.671
## My_daily_life_is_full_of_things_that_keep_me_interested 0.746
## I_am_usually_calm_and_not_easily_upset 0.663
## I_believe_that_my_home_life_is_as_pleasant_as_that_of_most_people_I_know 0.667
## Most_nights_I_go_to_sleep_without_thoughts_or_ideas_bothering_me 0.632
## I_am_liked_by_most_people_who_know_me 0.596
## I_am_not_easily_angered 0.545
## I_do_not_mind_meeting_strangers 0.453
## I_get_all_the_sympathy_I_should 0.579
## Little_interest_or_pleasure_in_doing_things 0.826
## Feeling_down_depressed_or_hopeless 0.902
## Feeling_more_irritated_grouchy_or_angry_than_usual 0.802
## Sleeping_less_than_usual_but_still_have_a_lot_of_energy 0.484
## Starting_lots_more_projects_than_usual_or_doing_more_risky_things_than_usual 0.491
## Feeling_nervous_anxious_frightened_worried_or_on_edge 0.839
## Feeling_panic_or_being_frightened 0.853
## Avoiding_situations_that_make_you_anxious 0.723
## Unexplained_aches_and_pains_e_g_head_back_joints_abdomen_legs 0.656
## Feeling_that_your_illnesses_are_not_being_taken_seriously_enough 0.768
## Thoughts_of_actually_hurting_yourself 0.797
## Hearing_things_other_people_couldn_t_hear_such_as_voices_even_when_no_one_was_around 0.537
## Feeling_that_someone_could_hear_your_thoughts_or_that_you_could_hear_what_another_person_was_thinking 0.528
## Problems_with_sleep_that_affected_your_sleep_quality_over_all 0.700
## Problems_with_memory_e_g_learning_new_information_or_with_location_e_g_finding_your_way_home 0.722
## Unpleasant_thoughts_urges_or_images_that_repeatedly_enter_your_mind 0.800
## Feeling_driven_to_perform_certain_behaviors_or_mental_acts_over_and_over_again 0.708
## Feeling_detached_or_distant_from_yourself_your_body_your_physical_surroundings_or_your_memories 0.795
## Not_knowing_who_you_really_are_or_what_you_want_out_of_life 0.826
## Not_feeling_close_to_other_people_or_enjoying_your_relationships_with_them 0.858
## Drinking_at_least_4_drinks_of_any_kind_of_alcohol_in_a_single_day 0.291
## Smoking_any_cigarettes_a_cigar_or_pipe_or_using_snuff_or_chewing_tobacco 0.302
## Using_any_of_the_following_medicines_ON_YOUR_OWN 0.476
## Life_satisfaction 0.799
## Job_satisfaction 0.602
## Social_satisfaction 0.711
## Romantic_satisfaction 0.533
## Mood_higher_means_better_mood 0.816
## Anxiety_levels_higher_means_less_anxious 0.447
## In_most_ways_my_life_is_close_to_my_ideal 0.718
## The_conditions_of_my_life_are_excellent 0.708
## I_am_satisfied_with_my_life 0.770
## So_far_I_have_gotten_the_important_things_I_want_in_life 0.692
## If_I_could_live_my_life_over_I_would_change_almost_nothing 0.566
## Attention_deficit_hyperactivity_disorder_ADHD 0.377
## Alcohol_abuse 0.347
## Non_alcohol_drug_abuse 0.468
## Autism_spectrum_disorder_ASD 0.468
## Anti_social_personality_disorder 0.741
## Bipolarity 0.447
## Borderline_Personality_Disorder 0.703
## Depression 0.617
## General_Anxiety_Disorder_GAD 0.518
## Obsessive_compulsive_disorder_OCD 0.368
## Panic_disorder 0.524
## Paranoia_Paranoid_personality_disorder 0.535
## Phobias_social 0.596
## Specific_phobias 0.558
## Post_traumatic_stress_disorder_PTSD 0.612
## Schizophrenia 0.481
## Schizoid_personality_disorder 0.564
## Sleeping_disorders 0.493
## h2
## Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen 0.6540
## Most_of_the_time_I_feel_blue 0.7809
## I_often_feel_as_if_things_were_not_real 0.4664
## I_sometimes_feel_that_I_am_about_to_go_to_pieces 0.6712
## Even_when_I_am_with_people_I_feel_lonely_much_of_the_time 0.6925
## I_feel_that_I_have_often_been_punished_without_cause 0.5786
## Life_is_a_strain_for_me_much_of_the_time 0.7463
## I_have_strange_and_peculiar_thoughts 0.3910
## My_plans_have_frequently_seemed_so_full_of_difficulties_that_I_have_had_to_give_them_up 0.6667
## Often_even_though_everything_is_going_fine_for_me_I_feel_that_I_don_t_care_about_anything 0.5581
## I_do_many_things_which_I_regret_afterwards_I_regret_things_more_or_more_often_than_others_seem_to 0.5065
## At_times_I_think_I_am_no_good_at_all 0.6558
## I_have_often_felt_that_strangers_were_looking_at_me_critically 0.4805
## I_am_happy_most_of_the_time 0.6188
## I_very_seldom_have_spells_of_the_blues 0.4325
## During_the_past_few_years_I_have_been_well_most_of_the_time 0.4498
## My_daily_life_is_full_of_things_that_keep_me_interested 0.5562
## I_am_usually_calm_and_not_easily_upset 0.4391
## I_believe_that_my_home_life_is_as_pleasant_as_that_of_most_people_I_know 0.4452
## Most_nights_I_go_to_sleep_without_thoughts_or_ideas_bothering_me 0.3997
## I_am_liked_by_most_people_who_know_me 0.3550
## I_am_not_easily_angered 0.2975
## I_do_not_mind_meeting_strangers 0.2051
## I_get_all_the_sympathy_I_should 0.3357
## Little_interest_or_pleasure_in_doing_things 0.6824
## Feeling_down_depressed_or_hopeless 0.8128
## Feeling_more_irritated_grouchy_or_angry_than_usual 0.6432
## Sleeping_less_than_usual_but_still_have_a_lot_of_energy 0.2341
## Starting_lots_more_projects_than_usual_or_doing_more_risky_things_than_usual 0.2415
## Feeling_nervous_anxious_frightened_worried_or_on_edge 0.7045
## Feeling_panic_or_being_frightened 0.7277
## Avoiding_situations_that_make_you_anxious 0.5220
## Unexplained_aches_and_pains_e_g_head_back_joints_abdomen_legs 0.4302
## Feeling_that_your_illnesses_are_not_being_taken_seriously_enough 0.5897
## Thoughts_of_actually_hurting_yourself 0.6356
## Hearing_things_other_people_couldn_t_hear_such_as_voices_even_when_no_one_was_around 0.2886
## Feeling_that_someone_could_hear_your_thoughts_or_that_you_could_hear_what_another_person_was_thinking 0.2789
## Problems_with_sleep_that_affected_your_sleep_quality_over_all 0.4898
## Problems_with_memory_e_g_learning_new_information_or_with_location_e_g_finding_your_way_home 0.5213
## Unpleasant_thoughts_urges_or_images_that_repeatedly_enter_your_mind 0.6407
## Feeling_driven_to_perform_certain_behaviors_or_mental_acts_over_and_over_again 0.5010
## Feeling_detached_or_distant_from_yourself_your_body_your_physical_surroundings_or_your_memories 0.6325
## Not_knowing_who_you_really_are_or_what_you_want_out_of_life 0.6820
## Not_feeling_close_to_other_people_or_enjoying_your_relationships_with_them 0.7368
## Drinking_at_least_4_drinks_of_any_kind_of_alcohol_in_a_single_day 0.0846
## Smoking_any_cigarettes_a_cigar_or_pipe_or_using_snuff_or_chewing_tobacco 0.0911
## Using_any_of_the_following_medicines_ON_YOUR_OWN 0.2267
## Life_satisfaction 0.6377
## Job_satisfaction 0.3621
## Social_satisfaction 0.5050
## Romantic_satisfaction 0.2840
## Mood_higher_means_better_mood 0.6658
## Anxiety_levels_higher_means_less_anxious 0.1998
## In_most_ways_my_life_is_close_to_my_ideal 0.5158
## The_conditions_of_my_life_are_excellent 0.5019
## I_am_satisfied_with_my_life 0.5927
## So_far_I_have_gotten_the_important_things_I_want_in_life 0.4793
## If_I_could_live_my_life_over_I_would_change_almost_nothing 0.3208
## Attention_deficit_hyperactivity_disorder_ADHD 0.1424
## Alcohol_abuse 0.1205
## Non_alcohol_drug_abuse 0.2187
## Autism_spectrum_disorder_ASD 0.2188
## Anti_social_personality_disorder 0.5488
## Bipolarity 0.1995
## Borderline_Personality_Disorder 0.4936
## Depression 0.3807
## General_Anxiety_Disorder_GAD 0.2687
## Obsessive_compulsive_disorder_OCD 0.1353
## Panic_disorder 0.2745
## Paranoia_Paranoid_personality_disorder 0.2867
## Phobias_social 0.3550
## Specific_phobias 0.3116
## Post_traumatic_stress_disorder_PTSD 0.3740
## Schizophrenia 0.2313
## Schizoid_personality_disorder 0.3185
## Sleeping_disorders 0.2427
##
## SS loadings: 34
## Proportion Var: 0.447
##
## Factor correlations:
##
## F1
## F1 1
#plot scale function
plot(
irt_mh_all,
type = "score"
)

#scores
irt_mh_all_scores = fscores(irt_mh_all, full.scores = T, full.scores.SE = T)
d$p_all = irt_mh_all_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_mh_all_scores)
## F1
## 0.967
marginal_rxx(irt_mh_all)
## [1] 0.966
get_reliabilities(irt_mh_all) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot
d %>%
GG_denhist("p_all")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Non-diagnoses only
#which are the symptom scales
mh_vars_symptoms = mh_vars_num %>% select(-c(Attention_deficit_hyperactivity_disorder_ADHD:Sleeping_disorders)) %>% names()
mh_vars_symptoms_idx = which(names(mh_vars_num) %in% mh_vars_symptoms)
#fit a model with all symptom scales without diagnoses
irt_mh_symptoms = mirt(
mh_vars_num %>% select(all_of(mh_vars_symptoms)),
itemtype = mh_vars_options %>% slice(mh_vars_symptoms_idx) %>% pull(itemtype),
model = 1
)
## Iteration: 1, Log-Lik: -48832.404, Max-Change: 3.07769Iteration: 2, Log-Lik: -47642.357, Max-Change: 1.08837Iteration: 3, Log-Lik: -47260.943, Max-Change: 0.40166Iteration: 4, Log-Lik: -47188.329, Max-Change: 0.16129Iteration: 5, Log-Lik: -47158.876, Max-Change: 0.09779Iteration: 6, Log-Lik: -47135.260, Max-Change: 0.07077Iteration: 7, Log-Lik: -47117.641, Max-Change: 0.08042Iteration: 8, Log-Lik: -47103.519, Max-Change: 0.04740Iteration: 9, Log-Lik: -47092.200, Max-Change: 0.05821Iteration: 10, Log-Lik: -47083.266, Max-Change: 0.07013Iteration: 11, Log-Lik: -47075.315, Max-Change: 0.04085Iteration: 12, Log-Lik: -47069.516, Max-Change: 0.03815Iteration: 13, Log-Lik: -47064.360, Max-Change: 0.05599Iteration: 14, Log-Lik: -47059.870, Max-Change: 0.04204Iteration: 15, Log-Lik: -47056.024, Max-Change: 0.03242Iteration: 16, Log-Lik: -47052.661, Max-Change: 0.03880Iteration: 17, Log-Lik: -47049.878, Max-Change: 0.03659Iteration: 18, Log-Lik: -47047.832, Max-Change: 0.02760Iteration: 19, 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irt_mh_symptoms
##
## Call:
## mirt(data = mh_vars_num %>% select(all_of(mh_vars_symptoms)),
## model = 1, itemtype = mh_vars_options %>% slice(mh_vars_symptoms_idx) %>%
## pull(itemtype))
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 262 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -47032
## Estimated parameters: 240
## AIC = 94544
## BIC = 95716; SABIC = 94954
irt_mh_symptoms %>% summary()
## F1
## Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen 0.811
## Most_of_the_time_I_feel_blue 0.885
## I_often_feel_as_if_things_were_not_real 0.686
## I_sometimes_feel_that_I_am_about_to_go_to_pieces 0.818
## Even_when_I_am_with_people_I_feel_lonely_much_of_the_time 0.833
## I_feel_that_I_have_often_been_punished_without_cause 0.762
## Life_is_a_strain_for_me_much_of_the_time 0.865
## I_have_strange_and_peculiar_thoughts 0.623
## My_plans_have_frequently_seemed_so_full_of_difficulties_that_I_have_had_to_give_them_up 0.818
## Often_even_though_everything_is_going_fine_for_me_I_feel_that_I_don_t_care_about_anything 0.747
## I_do_many_things_which_I_regret_afterwards_I_regret_things_more_or_more_often_than_others_seem_to 0.712
## At_times_I_think_I_am_no_good_at_all 0.808
## I_have_often_felt_that_strangers_were_looking_at_me_critically 0.688
## I_am_happy_most_of_the_time 0.789
## I_very_seldom_have_spells_of_the_blues 0.658
## During_the_past_few_years_I_have_been_well_most_of_the_time 0.666
## My_daily_life_is_full_of_things_that_keep_me_interested 0.747
## I_am_usually_calm_and_not_easily_upset 0.661
## I_believe_that_my_home_life_is_as_pleasant_as_that_of_most_people_I_know 0.666
## Most_nights_I_go_to_sleep_without_thoughts_or_ideas_bothering_me 0.630
## I_am_liked_by_most_people_who_know_me 0.595
## I_am_not_easily_angered 0.546
## I_do_not_mind_meeting_strangers 0.450
## I_get_all_the_sympathy_I_should 0.582
## Little_interest_or_pleasure_in_doing_things 0.829
## Feeling_down_depressed_or_hopeless 0.903
## Feeling_more_irritated_grouchy_or_angry_than_usual 0.803
## Sleeping_less_than_usual_but_still_have_a_lot_of_energy 0.487
## Starting_lots_more_projects_than_usual_or_doing_more_risky_things_than_usual 0.494
## Feeling_nervous_anxious_frightened_worried_or_on_edge 0.838
## Feeling_panic_or_being_frightened 0.853
## Avoiding_situations_that_make_you_anxious 0.720
## Unexplained_aches_and_pains_e_g_head_back_joints_abdomen_legs 0.653
## Feeling_that_your_illnesses_are_not_being_taken_seriously_enough 0.765
## Thoughts_of_actually_hurting_yourself 0.798
## Hearing_things_other_people_couldn_t_hear_such_as_voices_even_when_no_one_was_around 0.538
## Feeling_that_someone_could_hear_your_thoughts_or_that_you_could_hear_what_another_person_was_thinking 0.528
## Problems_with_sleep_that_affected_your_sleep_quality_over_all 0.695
## Problems_with_memory_e_g_learning_new_information_or_with_location_e_g_finding_your_way_home 0.720
## Unpleasant_thoughts_urges_or_images_that_repeatedly_enter_your_mind 0.798
## Feeling_driven_to_perform_certain_behaviors_or_mental_acts_over_and_over_again 0.707
## Feeling_detached_or_distant_from_yourself_your_body_your_physical_surroundings_or_your_memories 0.796
## Not_knowing_who_you_really_are_or_what_you_want_out_of_life 0.828
## Not_feeling_close_to_other_people_or_enjoying_your_relationships_with_them 0.860
## Drinking_at_least_4_drinks_of_any_kind_of_alcohol_in_a_single_day 0.291
## Smoking_any_cigarettes_a_cigar_or_pipe_or_using_snuff_or_chewing_tobacco 0.294
## Using_any_of_the_following_medicines_ON_YOUR_OWN 0.470
## Life_satisfaction 0.801
## Job_satisfaction 0.604
## Social_satisfaction 0.714
## Romantic_satisfaction 0.537
## Mood_higher_means_better_mood 0.819
## Anxiety_levels_higher_means_less_anxious 0.447
## In_most_ways_my_life_is_close_to_my_ideal 0.722
## The_conditions_of_my_life_are_excellent 0.711
## I_am_satisfied_with_my_life 0.774
## So_far_I_have_gotten_the_important_things_I_want_in_life 0.696
## If_I_could_live_my_life_over_I_would_change_almost_nothing 0.571
## h2
## Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen 0.6571
## Most_of_the_time_I_feel_blue 0.7839
## I_often_feel_as_if_things_were_not_real 0.4701
## I_sometimes_feel_that_I_am_about_to_go_to_pieces 0.6696
## Even_when_I_am_with_people_I_feel_lonely_much_of_the_time 0.6945
## I_feel_that_I_have_often_been_punished_without_cause 0.5799
## Life_is_a_strain_for_me_much_of_the_time 0.7480
## I_have_strange_and_peculiar_thoughts 0.3884
## My_plans_have_frequently_seemed_so_full_of_difficulties_that_I_have_had_to_give_them_up 0.6693
## Often_even_though_everything_is_going_fine_for_me_I_feel_that_I_don_t_care_about_anything 0.5576
## I_do_many_things_which_I_regret_afterwards_I_regret_things_more_or_more_often_than_others_seem_to 0.5071
## At_times_I_think_I_am_no_good_at_all 0.6526
## I_have_often_felt_that_strangers_were_looking_at_me_critically 0.4729
## I_am_happy_most_of_the_time 0.6221
## I_very_seldom_have_spells_of_the_blues 0.4325
## During_the_past_few_years_I_have_been_well_most_of_the_time 0.4437
## My_daily_life_is_full_of_things_that_keep_me_interested 0.5586
## I_am_usually_calm_and_not_easily_upset 0.4365
## I_believe_that_my_home_life_is_as_pleasant_as_that_of_most_people_I_know 0.4432
## Most_nights_I_go_to_sleep_without_thoughts_or_ideas_bothering_me 0.3971
## I_am_liked_by_most_people_who_know_me 0.3541
## I_am_not_easily_angered 0.2986
## I_do_not_mind_meeting_strangers 0.2022
## I_get_all_the_sympathy_I_should 0.3382
## Little_interest_or_pleasure_in_doing_things 0.6870
## Feeling_down_depressed_or_hopeless 0.8156
## Feeling_more_irritated_grouchy_or_angry_than_usual 0.6443
## Sleeping_less_than_usual_but_still_have_a_lot_of_energy 0.2369
## Starting_lots_more_projects_than_usual_or_doing_more_risky_things_than_usual 0.2444
## Feeling_nervous_anxious_frightened_worried_or_on_edge 0.7028
## Feeling_panic_or_being_frightened 0.7277
## Avoiding_situations_that_make_you_anxious 0.5182
## Unexplained_aches_and_pains_e_g_head_back_joints_abdomen_legs 0.4265
## Feeling_that_your_illnesses_are_not_being_taken_seriously_enough 0.5859
## Thoughts_of_actually_hurting_yourself 0.6373
## Hearing_things_other_people_couldn_t_hear_such_as_voices_even_when_no_one_was_around 0.2892
## Feeling_that_someone_could_hear_your_thoughts_or_that_you_could_hear_what_another_person_was_thinking 0.2793
## Problems_with_sleep_that_affected_your_sleep_quality_over_all 0.4835
## Problems_with_memory_e_g_learning_new_information_or_with_location_e_g_finding_your_way_home 0.5185
## Unpleasant_thoughts_urges_or_images_that_repeatedly_enter_your_mind 0.6362
## Feeling_driven_to_perform_certain_behaviors_or_mental_acts_over_and_over_again 0.4997
## Feeling_detached_or_distant_from_yourself_your_body_your_physical_surroundings_or_your_memories 0.6339
## Not_knowing_who_you_really_are_or_what_you_want_out_of_life 0.6861
## Not_feeling_close_to_other_people_or_enjoying_your_relationships_with_them 0.7392
## Drinking_at_least_4_drinks_of_any_kind_of_alcohol_in_a_single_day 0.0848
## Smoking_any_cigarettes_a_cigar_or_pipe_or_using_snuff_or_chewing_tobacco 0.0862
## Using_any_of_the_following_medicines_ON_YOUR_OWN 0.2207
## Life_satisfaction 0.6419
## Job_satisfaction 0.3644
## Social_satisfaction 0.5094
## Romantic_satisfaction 0.2884
## Mood_higher_means_better_mood 0.6703
## Anxiety_levels_higher_means_less_anxious 0.2000
## In_most_ways_my_life_is_close_to_my_ideal 0.5211
## The_conditions_of_my_life_are_excellent 0.5062
## I_am_satisfied_with_my_life 0.5986
## So_far_I_have_gotten_the_important_things_I_want_in_life 0.4842
## If_I_could_live_my_life_over_I_would_change_almost_nothing 0.3263
##
## SS loadings: 28.9
## Proportion Var: 0.498
##
## Factor correlations:
##
## F1
## F1 1
#plot scale function
plot(
irt_mh_symptoms,
type = "score"
)

#scores
irt_mh_symptoms_scores = fscores(irt_mh_symptoms, full.scores = T, full.scores.SE = T)
d$p_symptoms = irt_mh_symptoms_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_mh_symptoms_scores)
## F1
## 0.966
marginal_rxx(irt_mh_symptoms)
## [1] 0.966
get_reliabilities(irt_mh_symptoms) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot
d %>%
GG_denhist("p_symptoms")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Diagnoses only
#heatmap of latent cors
mh_vars_num %>% select(-all_of(mh_vars_symptoms)) %>%
psych::mixedCor() %>%
.[["rho"]] %>%
GG_heatmap(color_label = "Latent correlation", short_x_labels = T, font_size = 3)
## Warning in cor.smooth(mat): Matrix was not positive definite, smoothing was
## done

GG_save("figs/diagnoses_cor_heatmap.png")
#numbers
mh_vars_num %>% select(-all_of(mh_vars_symptoms)) %>%
psych::mixedCor() %>%
.[["rho"]] %>%
kirkegaard::MAT_half() %>%
describe2()
## Warning in cor.smooth(mat): Matrix was not positive definite, smoothing was
## done
#counts of each diagnosis
mh_vars_num %>% select(-all_of(mh_vars_symptoms)) %>% map_dfr(~(. - 1)) %>% colMeans() %>% sort()
## Paranoia_Paranoid_personality_disorder
## 0.00204
## Schizophrenia
## 0.00204
## Schizoid_personality_disorder
## 0.00204
## Anti_social_personality_disorder
## 0.01431
## Phobias_social
## 0.01738
## Specific_phobias
## 0.01738
## Non_alcohol_drug_abuse
## 0.01943
## Borderline_Personality_Disorder
## 0.01943
## Autism_spectrum_disorder_ASD
## 0.03170
## Obsessive_compulsive_disorder_OCD
## 0.03885
## Bipolarity
## 0.03988
## Alcohol_abuse
## 0.04601
## Panic_disorder
## 0.05215
## Post_traumatic_stress_disorder_PTSD
## 0.07464
## Sleeping_disorders
## 0.08998
## Attention_deficit_hyperactivity_disorder_ADHD
## 0.10838
## General_Anxiety_Disorder_GAD
## 0.20859
## Depression
## 0.25256
mh_vars_num %>% select(-all_of(mh_vars_symptoms)) %>% map_dfr(~(. - 1)) %>% map_df(as.logical) %>% map_df(ordered) %>% GG_ordinal() +
labs(
fill = "Has diagnosis"
)

GG_save("figs/diagnoses_counts.png")
#fit a model with diagnoses only
irt_mh_diag = mirt(
mh_vars_num %>% select(-all_of(mh_vars_symptoms)),
itemtype = mh_vars_options %>% slice(-mh_vars_symptoms_idx) %>% pull(itemtype),
model = 1
)
## Iteration: 1, Log-Lik: -2959.734, Max-Change: 2.26702Iteration: 2, Log-Lik: -2839.244, Max-Change: 0.91097Iteration: 3, Log-Lik: -2804.854, Max-Change: 0.37436Iteration: 4, Log-Lik: -2791.188, Max-Change: 0.26860Iteration: 5, Log-Lik: -2785.334, Max-Change: 0.16748Iteration: 6, Log-Lik: -2782.963, Max-Change: 0.11723Iteration: 7, Log-Lik: -2780.956, Max-Change: 0.10253Iteration: 8, Log-Lik: -2780.582, Max-Change: 0.22686Iteration: 9, Log-Lik: -2780.371, Max-Change: 0.02745Iteration: 10, Log-Lik: -2780.331, Max-Change: 0.02607Iteration: 11, Log-Lik: -2780.210, Max-Change: 0.01955Iteration: 12, Log-Lik: -2780.130, Max-Change: 0.01137Iteration: 13, Log-Lik: -2780.056, Max-Change: 0.00819Iteration: 14, Log-Lik: -2780.025, Max-Change: 0.00559Iteration: 15, Log-Lik: -2780.004, Max-Change: 0.00464Iteration: 16, Log-Lik: -2779.958, Max-Change: 0.00089Iteration: 17, Log-Lik: -2779.958, Max-Change: 0.00071Iteration: 18, Log-Lik: -2779.957, Max-Change: 0.00063Iteration: 19, Log-Lik: -2779.956, Max-Change: 0.00091Iteration: 20, Log-Lik: -2779.956, Max-Change: 0.00020Iteration: 21, Log-Lik: -2779.956, Max-Change: 0.00067Iteration: 22, Log-Lik: -2779.956, Max-Change: 0.00015Iteration: 23, Log-Lik: -2779.956, Max-Change: 0.00048Iteration: 24, Log-Lik: -2779.956, Max-Change: 0.00011Iteration: 25, Log-Lik: -2779.956, Max-Change: 0.00008
irt_mh_diag
##
## Call:
## mirt(data = mh_vars_num %>% select(-all_of(mh_vars_symptoms)),
## model = 1, itemtype = mh_vars_options %>% slice(-mh_vars_symptoms_idx) %>%
## pull(itemtype))
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 25 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -2780
## Estimated parameters: 36
## AIC = 5632
## BIC = 5808; SABIC = 5693
## G2 (262107) = 836, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
irt_mh_diag %>% summary()
## F1 h2
## Attention_deficit_hyperactivity_disorder_ADHD 0.564 0.318
## Alcohol_abuse 0.542 0.294
## Non_alcohol_drug_abuse 0.614 0.377
## Autism_spectrum_disorder_ASD 0.574 0.329
## Anti_social_personality_disorder 0.760 0.577
## Bipolarity 0.679 0.461
## Borderline_Personality_Disorder 0.830 0.689
## Depression 0.855 0.731
## General_Anxiety_Disorder_GAD 0.863 0.744
## Obsessive_compulsive_disorder_OCD 0.698 0.487
## Panic_disorder 0.816 0.667
## Paranoia_Paranoid_personality_disorder 0.567 0.322
## Phobias_social 0.820 0.673
## Specific_phobias 0.844 0.713
## Post_traumatic_stress_disorder_PTSD 0.840 0.705
## Schizophrenia 0.648 0.420
## Schizoid_personality_disorder 0.842 0.710
## Sleeping_disorders 0.716 0.512
##
## SS loadings: 9.73
## Proportion Var: 0.54
##
## Factor correlations:
##
## F1
## F1 1
#plot scale function
plot(
irt_mh_diag,
type = "score"
)

#scores
irt_mh_diag_scores = fscores(irt_mh_diag, full.scores = T, full.scores.SE = T)
d$p_diag = irt_mh_diag_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_mh_diag_scores)
## F1
## 0.599
marginal_rxx(irt_mh_diag)
## [1] 0.547
get_reliabilities(irt_mh_diag) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot
d %>%
GG_denhist("p_diag")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Comparison with symptoms
#compare
GG_scatter(d, "p_symptoms", "p_diag")
## `geom_smooth()` using formula = 'y ~ x'

#count of diagnoses
d$P_diag_count = mh_vars_num %>% select(-all_of(mh_vars_symptoms)) %>% map_df(~(. - 1)) %>% rowSums(na.rm = T)
d$P_diag_count %>% table2()
d$P_diag_count2 = d$P_diag_count %>% as.factor() %>% fct_lump_min(20, other_level = "5+")
d$P_diag_count2 %>% table2()
d$P_diag_any = d$P_diag_count > 0
#cohen d
SMD_matrix(d$p_symptoms, d$P_diag_any)
## FALSE TRUE
## FALSE NA -0.914
## TRUE -0.914 NA
SMD_matrix(d$p_symptoms, d$P_diag_count2)
## 0 1 2 3 4 5+
## 0 NA -0.568 -0.806 -1.115 -1.290 -1.691
## 1 -0.568 NA -0.238 -0.547 -0.723 -1.123
## 2 -0.806 -0.238 NA -0.310 -0.485 -0.885
## 3 -1.115 -0.547 -0.310 NA -0.175 -0.576
## 4 -1.290 -0.723 -0.485 -0.175 NA -0.401
## 5+ -1.691 -1.123 -0.885 -0.576 -0.401 NA
GG_group_means(d, "p_symptoms", "P_diag_count2", type = "violin") +
labs(
x = "Count of diagnoses",
y = "Symptoms (IRT score)"
)

GG_save("figs/p symptoms by diagnoses.png")
MMPI only
#item cors
mh_vars_num %>% select(
Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen:I_get_all_the_sympathy_I_should
) %>%
psych::mixedCor() %>%
.[["rho"]] %>%
GG_heatmap(color_label = "Latent correlation", short_x_labels = T)

#MMPI items fit
irt_mh_mmpi = mirt(
mh_vars_num %>% select(
Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen:I_get_all_the_sympathy_I_should
),
model = 1,
)
## Iteration: 1, Log-Lik: -10628.125, Max-Change: 0.78877Iteration: 2, Log-Lik: -10234.763, Max-Change: 0.62683Iteration: 3, Log-Lik: -10136.724, Max-Change: 0.35989Iteration: 4, Log-Lik: -10098.956, Max-Change: 0.26196Iteration: 5, Log-Lik: -10080.702, Max-Change: 0.18262Iteration: 6, Log-Lik: -10070.942, Max-Change: 0.15110Iteration: 7, Log-Lik: -10065.596, Max-Change: 0.11603Iteration: 8, Log-Lik: -10062.451, Max-Change: 0.08908Iteration: 9, Log-Lik: -10060.566, Max-Change: 0.05266Iteration: 10, Log-Lik: -10058.477, Max-Change: 0.03398Iteration: 11, Log-Lik: -10057.784, Max-Change: 0.02522Iteration: 12, Log-Lik: -10057.326, Max-Change: 0.02057Iteration: 13, Log-Lik: -10056.456, Max-Change: 0.01197Iteration: 14, Log-Lik: -10056.242, Max-Change: 0.01125Iteration: 15, Log-Lik: -10056.060, Max-Change: 0.00947Iteration: 16, Log-Lik: -10055.626, Max-Change: 0.00948Iteration: 17, Log-Lik: -10055.505, Max-Change: 0.00928Iteration: 18, Log-Lik: -10055.418, Max-Change: 0.00756Iteration: 19, Log-Lik: -10055.222, Max-Change: 0.00712Iteration: 20, Log-Lik: -10055.166, Max-Change: 0.00518Iteration: 21, Log-Lik: -10055.121, Max-Change: 0.00527Iteration: 22, Log-Lik: -10054.922, Max-Change: 0.00342Iteration: 23, Log-Lik: -10054.907, Max-Change: 0.00331Iteration: 24, Log-Lik: -10054.893, Max-Change: 0.00306Iteration: 25, Log-Lik: -10054.834, Max-Change: 0.00230Iteration: 26, Log-Lik: -10054.829, Max-Change: 0.00189Iteration: 27, Log-Lik: -10054.825, Max-Change: 0.00143Iteration: 28, Log-Lik: -10054.813, Max-Change: 0.00145Iteration: 29, Log-Lik: -10054.811, Max-Change: 0.00106Iteration: 30, Log-Lik: -10054.809, Max-Change: 0.00112Iteration: 31, Log-Lik: -10054.801, Max-Change: 0.00061Iteration: 32, Log-Lik: -10054.801, Max-Change: 0.00074Iteration: 33, Log-Lik: -10054.800, Max-Change: 0.00064Iteration: 34, Log-Lik: -10054.798, Max-Change: 0.00087Iteration: 35, Log-Lik: -10054.797, Max-Change: 0.00044Iteration: 36, Log-Lik: -10054.797, Max-Change: 0.00044Iteration: 37, Log-Lik: -10054.797, Max-Change: 0.00035Iteration: 38, Log-Lik: -10054.797, Max-Change: 0.00032Iteration: 39, Log-Lik: -10054.797, Max-Change: 0.00030Iteration: 40, Log-Lik: -10054.797, Max-Change: 0.00044Iteration: 41, Log-Lik: -10054.796, Max-Change: 0.00024Iteration: 42, Log-Lik: -10054.796, Max-Change: 0.00023Iteration: 43, Log-Lik: -10054.796, Max-Change: 0.00021Iteration: 44, Log-Lik: -10054.796, Max-Change: 0.00020Iteration: 45, Log-Lik: -10054.796, Max-Change: 0.00018Iteration: 46, Log-Lik: -10054.796, Max-Change: 0.00024Iteration: 47, Log-Lik: -10054.796, Max-Change: 0.00015Iteration: 48, Log-Lik: -10054.796, Max-Change: 0.00014Iteration: 49, Log-Lik: -10054.796, Max-Change: 0.00013Iteration: 50, Log-Lik: -10054.796, Max-Change: 0.00013Iteration: 51, Log-Lik: -10054.796, Max-Change: 0.00012Iteration: 52, Log-Lik: -10054.796, Max-Change: 0.00014Iteration: 53, Log-Lik: -10054.796, Max-Change: 0.00010Iteration: 54, Log-Lik: -10054.796, Max-Change: 0.00010
irt_mh_mmpi
##
## Call:
## mirt(data = mh_vars_num %>% select(Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen:I_get_all_the_sympathy_I_should),
## model = 1)
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 54 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -10055
## Estimated parameters: 48
## AIC = 20206
## BIC = 20440; SABIC = 20288
## G2 (16777167) = 9179, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
irt_mh_mmpi %>% summary()
## F1
## Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen 0.834
## Most_of_the_time_I_feel_blue 0.905
## I_often_feel_as_if_things_were_not_real 0.735
## I_sometimes_feel_that_I_am_about_to_go_to_pieces 0.858
## Even_when_I_am_with_people_I_feel_lonely_much_of_the_time 0.846
## I_feel_that_I_have_often_been_punished_without_cause 0.813
## Life_is_a_strain_for_me_much_of_the_time 0.899
## I_have_strange_and_peculiar_thoughts 0.657
## My_plans_have_frequently_seemed_so_full_of_difficulties_that_I_have_had_to_give_them_up 0.850
## Often_even_though_everything_is_going_fine_for_me_I_feel_that_I_don_t_care_about_anything 0.763
## I_do_many_things_which_I_regret_afterwards_I_regret_things_more_or_more_often_than_others_seem_to 0.769
## At_times_I_think_I_am_no_good_at_all 0.857
## I_have_often_felt_that_strangers_were_looking_at_me_critically 0.730
## I_am_happy_most_of_the_time 0.805
## I_very_seldom_have_spells_of_the_blues 0.713
## During_the_past_few_years_I_have_been_well_most_of_the_time 0.680
## My_daily_life_is_full_of_things_that_keep_me_interested 0.754
## I_am_usually_calm_and_not_easily_upset 0.718
## I_believe_that_my_home_life_is_as_pleasant_as_that_of_most_people_I_know 0.672
## Most_nights_I_go_to_sleep_without_thoughts_or_ideas_bothering_me 0.645
## I_am_liked_by_most_people_who_know_me 0.653
## I_am_not_easily_angered 0.617
## I_do_not_mind_meeting_strangers 0.490
## I_get_all_the_sympathy_I_should 0.628
## h2
## Several_times_a_week_I_feel_as_if_something_dreadful_is_about_to_happen 0.695
## Most_of_the_time_I_feel_blue 0.819
## I_often_feel_as_if_things_were_not_real 0.541
## I_sometimes_feel_that_I_am_about_to_go_to_pieces 0.737
## Even_when_I_am_with_people_I_feel_lonely_much_of_the_time 0.716
## I_feel_that_I_have_often_been_punished_without_cause 0.662
## Life_is_a_strain_for_me_much_of_the_time 0.809
## I_have_strange_and_peculiar_thoughts 0.431
## My_plans_have_frequently_seemed_so_full_of_difficulties_that_I_have_had_to_give_them_up 0.722
## Often_even_though_everything_is_going_fine_for_me_I_feel_that_I_don_t_care_about_anything 0.582
## I_do_many_things_which_I_regret_afterwards_I_regret_things_more_or_more_often_than_others_seem_to 0.591
## At_times_I_think_I_am_no_good_at_all 0.734
## I_have_often_felt_that_strangers_were_looking_at_me_critically 0.533
## I_am_happy_most_of_the_time 0.649
## I_very_seldom_have_spells_of_the_blues 0.508
## During_the_past_few_years_I_have_been_well_most_of_the_time 0.462
## My_daily_life_is_full_of_things_that_keep_me_interested 0.568
## I_am_usually_calm_and_not_easily_upset 0.515
## I_believe_that_my_home_life_is_as_pleasant_as_that_of_most_people_I_know 0.451
## Most_nights_I_go_to_sleep_without_thoughts_or_ideas_bothering_me 0.416
## I_am_liked_by_most_people_who_know_me 0.427
## I_am_not_easily_angered 0.381
## I_do_not_mind_meeting_strangers 0.240
## I_get_all_the_sympathy_I_should 0.394
##
## SS loadings: 13.6
## Proportion Var: 0.566
##
## Factor correlations:
##
## F1
## F1 1
#plot scale function
plot(
irt_mh_mmpi,
type = "score"
)

#plot item functions
plot(
irt_mh_mmpi,
type = "trace"
)

#scores
irt_mh_mmpi_scores = fscores(irt_mh_mmpi, full.scores = T, full.scores.SE = T)
d$p_mmpi = irt_mh_mmpi_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_mh_mmpi_scores)
## F1
## 0.851
marginal_rxx(irt_mh_mmpi)
## [1] 0.831
get_reliabilities(irt_mh_mmpi) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot scores
d %>%
GG_denhist("p_mmpi")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Last 2 weeks
#last 2 weeks items fit
irt_mh_last2weeks = mirt(
mh_vars_num %>% select(Little_interest_or_pleasure_in_doing_things:Using_any_of_the_following_medicines_ON_YOUR_OWN),
itemtype = "graded",
model = 1
)
## Iteration: 1, Log-Lik: -20832.286, Max-Change: 3.34204Iteration: 2, Log-Lik: -19929.474, Max-Change: 1.07182Iteration: 3, Log-Lik: -19774.154, Max-Change: 0.45882Iteration: 4, Log-Lik: -19709.234, Max-Change: 0.19396Iteration: 5, Log-Lik: -19665.609, Max-Change: 0.13948Iteration: 6, Log-Lik: -19635.996, Max-Change: 0.10491Iteration: 7, Log-Lik: -19614.685, Max-Change: 0.15725Iteration: 8, Log-Lik: -19599.800, Max-Change: 0.12546Iteration: 9, Log-Lik: -19589.936, Max-Change: 0.18390Iteration: 10, Log-Lik: -19582.724, Max-Change: 0.13221Iteration: 11, Log-Lik: -19576.902, Max-Change: 0.14946Iteration: 12, Log-Lik: -19572.270, Max-Change: 0.10134Iteration: 13, Log-Lik: -19568.521, Max-Change: 0.09331Iteration: 14, Log-Lik: -19565.134, Max-Change: 0.07681Iteration: 15, Log-Lik: -19562.261, Max-Change: 0.06670Iteration: 16, Log-Lik: -19560.789, Max-Change: 0.04381Iteration: 17, Log-Lik: -19558.377, Max-Change: 0.05111Iteration: 18, Log-Lik: -19556.331, Max-Change: 0.08628Iteration: 19, 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irt_mh_last2weeks
##
## Call:
## mirt(data = mh_vars_num %>% select(Little_interest_or_pleasure_in_doing_things:Using_any_of_the_following_medicines_ON_YOUR_OWN),
## model = 1, itemtype = "graded")
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 133 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -19540
## Estimated parameters: 115
## AIC = 39310
## BIC = 39872; SABIC = 39507
## G2 (1e+10) = 26576, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
irt_mh_last2weeks %>% summary()
## F1
## Little_interest_or_pleasure_in_doing_things 0.838
## Feeling_down_depressed_or_hopeless 0.868
## Feeling_more_irritated_grouchy_or_angry_than_usual 0.817
## Sleeping_less_than_usual_but_still_have_a_lot_of_energy 0.588
## Starting_lots_more_projects_than_usual_or_doing_more_risky_things_than_usual 0.672
## Feeling_nervous_anxious_frightened_worried_or_on_edge 0.849
## Feeling_panic_or_being_frightened 0.891
## Avoiding_situations_that_make_you_anxious 0.750
## Unexplained_aches_and_pains_e_g_head_back_joints_abdomen_legs 0.729
## Feeling_that_your_illnesses_are_not_being_taken_seriously_enough 0.805
## Thoughts_of_actually_hurting_yourself 0.888
## Hearing_things_other_people_couldn_t_hear_such_as_voices_even_when_no_one_was_around 0.777
## Feeling_that_someone_could_hear_your_thoughts_or_that_you_could_hear_what_another_person_was_thinking 0.771
## Problems_with_sleep_that_affected_your_sleep_quality_over_all 0.704
## Problems_with_memory_e_g_learning_new_information_or_with_location_e_g_finding_your_way_home 0.799
## Unpleasant_thoughts_urges_or_images_that_repeatedly_enter_your_mind 0.864
## Feeling_driven_to_perform_certain_behaviors_or_mental_acts_over_and_over_again 0.824
## Feeling_detached_or_distant_from_yourself_your_body_your_physical_surroundings_or_your_memories 0.888
## Not_knowing_who_you_really_are_or_what_you_want_out_of_life 0.838
## Not_feeling_close_to_other_people_or_enjoying_your_relationships_with_them 0.849
## Drinking_at_least_4_drinks_of_any_kind_of_alcohol_in_a_single_day 0.432
## Smoking_any_cigarettes_a_cigar_or_pipe_or_using_snuff_or_chewing_tobacco 0.380
## Using_any_of_the_following_medicines_ON_YOUR_OWN 0.584
## h2
## Little_interest_or_pleasure_in_doing_things 0.703
## Feeling_down_depressed_or_hopeless 0.754
## Feeling_more_irritated_grouchy_or_angry_than_usual 0.668
## Sleeping_less_than_usual_but_still_have_a_lot_of_energy 0.346
## Starting_lots_more_projects_than_usual_or_doing_more_risky_things_than_usual 0.452
## Feeling_nervous_anxious_frightened_worried_or_on_edge 0.721
## Feeling_panic_or_being_frightened 0.794
## Avoiding_situations_that_make_you_anxious 0.563
## Unexplained_aches_and_pains_e_g_head_back_joints_abdomen_legs 0.531
## Feeling_that_your_illnesses_are_not_being_taken_seriously_enough 0.649
## Thoughts_of_actually_hurting_yourself 0.789
## Hearing_things_other_people_couldn_t_hear_such_as_voices_even_when_no_one_was_around 0.604
## Feeling_that_someone_could_hear_your_thoughts_or_that_you_could_hear_what_another_person_was_thinking 0.594
## Problems_with_sleep_that_affected_your_sleep_quality_over_all 0.496
## Problems_with_memory_e_g_learning_new_information_or_with_location_e_g_finding_your_way_home 0.639
## Unpleasant_thoughts_urges_or_images_that_repeatedly_enter_your_mind 0.746
## Feeling_driven_to_perform_certain_behaviors_or_mental_acts_over_and_over_again 0.680
## Feeling_detached_or_distant_from_yourself_your_body_your_physical_surroundings_or_your_memories 0.789
## Not_knowing_who_you_really_are_or_what_you_want_out_of_life 0.703
## Not_feeling_close_to_other_people_or_enjoying_your_relationships_with_them 0.721
## Drinking_at_least_4_drinks_of_any_kind_of_alcohol_in_a_single_day 0.186
## Smoking_any_cigarettes_a_cigar_or_pipe_or_using_snuff_or_chewing_tobacco 0.144
## Using_any_of_the_following_medicines_ON_YOUR_OWN 0.341
##
## SS loadings: 13.6
## Proportion Var: 0.592
##
## Factor correlations:
##
## F1
## F1 1
#plot scale function
plot(
irt_mh_last2weeks,
type = "score"
)

#scores
irt_mh_last2weeks_scores = fscores(irt_mh_last2weeks, full.scores = T, full.scores.SE = T)
d$p_last2weeks = irt_mh_last2weeks_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_mh_last2weeks_scores)
## F1
## 0.922
marginal_rxx(irt_mh_last2weeks)
## [1] 0.915
get_reliabilities(irt_mh_last2weeks) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot scores
d %>%
GG_denhist("p_last2weeks")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Satisfaction
#satisfaction items fit
irt_mh_satisfaction = mirt(
mh_vars_num %>% select(Life_satisfaction:If_I_could_live_my_life_over_I_would_change_almost_nothing),
itemtype = "graded",
model = 1
)
## Iteration: 1, Log-Lik: -17261.348, Max-Change: 4.74325Iteration: 2, Log-Lik: -15966.731, Max-Change: 3.23578Iteration: 3, Log-Lik: -15559.911, Max-Change: 0.79657Iteration: 4, Log-Lik: -15449.248, Max-Change: 0.42745Iteration: 5, Log-Lik: -15412.663, Max-Change: 0.25303Iteration: 6, Log-Lik: -15390.040, Max-Change: 0.26829Iteration: 7, Log-Lik: -15372.920, Max-Change: 0.25317Iteration: 8, Log-Lik: -15358.428, Max-Change: 0.28573Iteration: 9, Log-Lik: -15347.268, Max-Change: 0.23856Iteration: 10, Log-Lik: -15337.766, Max-Change: 0.15906Iteration: 11, Log-Lik: -15329.978, Max-Change: 0.14260Iteration: 12, Log-Lik: -15323.443, Max-Change: 0.18383Iteration: 13, Log-Lik: -15318.689, Max-Change: 0.15645Iteration: 14, Log-Lik: -15314.484, Max-Change: 0.11813Iteration: 15, Log-Lik: -15310.902, Max-Change: 0.08488Iteration: 16, Log-Lik: -15309.104, Max-Change: 0.07564Iteration: 17, Log-Lik: -15306.101, Max-Change: 0.11286Iteration: 18, Log-Lik: -15303.773, Max-Change: 0.14263Iteration: 19, 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irt_mh_satisfaction
##
## Call:
## mirt(data = mh_vars_num %>% select(Life_satisfaction:If_I_could_live_my_life_over_I_would_change_almost_nothing),
## model = 1, itemtype = "graded")
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 137 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -15291
## Estimated parameters: 77
## AIC = 30736
## BIC = 31113; SABIC = 30868
irt_mh_satisfaction %>% summary()
## F1 h2
## Life_satisfaction 0.928 0.862
## Job_satisfaction 0.749 0.560
## Social_satisfaction 0.801 0.642
## Romantic_satisfaction 0.715 0.511
## Mood_higher_means_better_mood 0.841 0.707
## Anxiety_levels_higher_means_less_anxious 0.433 0.187
## In_most_ways_my_life_is_close_to_my_ideal 0.947 0.897
## The_conditions_of_my_life_are_excellent 0.928 0.861
## I_am_satisfied_with_my_life 0.960 0.921
## So_far_I_have_gotten_the_important_things_I_want_in_life 0.886 0.785
## If_I_could_live_my_life_over_I_would_change_almost_nothing 0.793 0.630
##
## SS loadings: 7.56
## Proportion Var: 0.688
##
## Factor correlations:
##
## F1
## F1 1
#plot scale function
plot(
irt_mh_satisfaction,
type = "score"
)

#scores
irt_mh_satisfaction_scores = fscores(irt_mh_satisfaction, full.scores = T, full.scores.SE = T)
d$p_satisfaction = irt_mh_satisfaction_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_mh_satisfaction_scores)
## F1
## 0.963
marginal_rxx(irt_mh_satisfaction)
## [1] 0.963
get_reliabilities(irt_mh_satisfaction) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot scores
d %>%
GG_denhist("p_satisfaction")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Ideology
#dimensionality
(unidem_pol = unidim(
pol_vars_num,
cor = "mixed"
))
##
## A measure of unidimensionality
## Call: unidim(keys = pol_vars_num, cor = "mixed")
##
## Unidimensionality index =
## u tau rho_c alpha av.r median.r CFI ECV
## 0.73 0.77 0.95 0.96 0.35 0.37 0.62 0.77
## F1/F2 MAP
## 4.81 0.03
##
## unidim adjusted index reverses negatively scored items.
## alpha Based upon reverse scoring some items.
## average and median correlations are based upon reversed scored items
#fit a full model with all items of all types
irt_pol_all = mirt(
pol_vars_num,
itemtype = pol_vars_options$itemtype,
model = 1
)
## Iteration: 1, Log-Lik: -70868.186, Max-Change: 2.91228Iteration: 2, Log-Lik: -64057.133, Max-Change: 1.02316Iteration: 3, Log-Lik: -63091.100, Max-Change: 0.65212Iteration: 4, Log-Lik: -62951.070, Max-Change: 0.37279Iteration: 5, Log-Lik: -62894.942, Max-Change: 0.08779Iteration: 6, Log-Lik: -62885.952, Max-Change: 0.06001Iteration: 7, Log-Lik: -62883.341, Max-Change: 0.02913Iteration: 8, Log-Lik: -62881.705, Max-Change: 0.02891Iteration: 9, Log-Lik: -62880.432, Max-Change: 0.02635Iteration: 10, Log-Lik: -62879.429, Max-Change: 0.02758Iteration: 11, Log-Lik: -62878.446, Max-Change: 0.02098Iteration: 12, Log-Lik: -62877.708, Max-Change: 0.02777Iteration: 13, Log-Lik: -62876.690, Max-Change: 0.01502Iteration: 14, Log-Lik: -62876.103, Max-Change: 0.02244Iteration: 15, Log-Lik: -62875.686, Max-Change: 0.01318Iteration: 16, Log-Lik: -62875.324, Max-Change: 0.01048Iteration: 17, Log-Lik: -62875.028, Max-Change: 0.02066Iteration: 18, Log-Lik: -62874.761, Max-Change: 0.00835Iteration: 19, Log-Lik: -62874.586, Max-Change: 0.01044Iteration: 20, Log-Lik: -62874.380, Max-Change: 0.01079Iteration: 21, Log-Lik: -62874.202, Max-Change: 0.00809Iteration: 22, Log-Lik: -62874.015, Max-Change: 0.00661Iteration: 23, Log-Lik: -62873.895, Max-Change: 0.00588Iteration: 24, Log-Lik: -62873.802, Max-Change: 0.00638Iteration: 25, Log-Lik: -62873.481, Max-Change: 0.00475Iteration: 26, Log-Lik: -62873.412, Max-Change: 0.00277Iteration: 27, Log-Lik: -62873.381, Max-Change: 0.00500Iteration: 28, Log-Lik: -62873.321, Max-Change: 0.00227Iteration: 29, Log-Lik: -62873.300, Max-Change: 0.00238Iteration: 30, Log-Lik: -62873.283, Max-Change: 0.00253Iteration: 31, Log-Lik: -62873.212, Max-Change: 0.00177Iteration: 32, Log-Lik: -62873.204, Max-Change: 0.00288Iteration: 33, Log-Lik: -62873.194, Max-Change: 0.00247Iteration: 34, Log-Lik: -62873.190, Max-Change: 0.00113Iteration: 35, Log-Lik: -62873.186, Max-Change: 0.00086Iteration: 36, Log-Lik: -62873.184, Max-Change: 0.00059Iteration: 37, Log-Lik: 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irt_pol_all
##
## Call:
## mirt(data = pol_vars_num, model = 1, itemtype = pol_vars_options$itemtype)
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 196 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -62873
## Estimated parameters: 287
## AIC = 126320
## BIC = 127722; SABIC = 126811
## G2 (1e+10) = 112278, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
irt_pol_all %>% summary()
## F1
## There_are_objective_measures_of_beauty_How_much_do_you_agree_with_the_following_statements -0.292
## The_label_overweight_is_offensive_How_much_do_you_agree_with_the_following_statements 0.107
## Beauty_standards_are_oppressive_How_much_do_you_agree_with_the_following_statements 0.507
## Body_positivity_is_harmful_How_much_do_you_agree_with_the_following_statements -0.282
## I_support_the_LGBT_community_How_much_do_you_agree_with_the_following_statements 0.888
## Homosexual_behavior_is_fine_when_it_is_private_and_chaste_How_much_do_you_agree_with_the_following_statements 0.106
## There_is_nothing_wrong_with_public_depictions_of_homosexual_relationships_How_much_do_you_agree_with_the_following_statements 0.868
## I_support_gay_marriage_How_much_do_you_agree_with_the_following_statements 0.870
## There_is_nothing_wrong_with_attending_a_gay_orgy_How_much_do_you_agree_with_the_following_statements 0.763
## Children_should_be_taught_about_gay_sex_in_sex_education_classes_How_much_do_you_agree_with_the_following_statements 0.776
## There_are_only_two_genders_How_much_do_you_agree_with_the_following_statements -0.846
## Everyone_be_addressed_by_their_desired_pronouns_How_much_do_you_agree_with_the_following_statements 0.850
## I_support_feminism_How_much_do_you_agree_with_the_following_statements 0.835
## The_country_would_be_better_if_women_couldn_t_vote_How_much_do_you_agree_with_the_following_statements -0.516
## Women_should_try_to_be_married_by_the_age_of_25_How_much_do_you_agree_with_the_following_statements -0.501
## The_government_should_help_ensure_sexual_equality_by_making_sure_women_are_not_discriminated_against_in_private_hiring_How_much_do_you_agree_with_the_following_statements 0.693
## Women_should_hold_the_majority_of_the_positions_of_power_in_society_How_much_do_you_agree_with_the_following_statements 0.542
## Marriage_is_oppressive_for_women_and_monogamy_should_be_moved_away_from_How_much_do_you_agree_with_the_following_statements 0.420
## Men_should_be_masculine_and_women_should_be_feminine_How_much_do_you_agree_with_the_following_statements -0.760
## Politics_suffers_from_male_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.806
## Abortion_should_be_available_to_women_for_use_for_any_reason_How_much_do_you_agree_with_the_following_statements 0.816
## I_support_sending_more_aid_to_Ukraine_How_much_do_you_agree_with_the_following_statements 0.664
## The_Western_response_to_the_Russian_invasion_of_Ukraine_went_too_far_How_much_do_you_agree_with_the_following_statements -0.511
## Progressive_taxation_where_the_rich_are_taxed_at_a_higher_rate_is_the_best_way_to_structure_a_tax_system_How_much_do_you_agree_with_the_following_statements 0.694
## Reducing_taxes_for_businesses_can_stimulate_economic_growth_How_much_do_you_agree_with_the_following_statements -0.553
## I_support_Israel_against_Hamas_How_much_do_you_agree_with_the_following_statements -0.504
## Israel_is_commiting_genocide_in_Gaza_How_much_do_you_agree_with_the_following_statements 0.647
## Black_Lives_Matter_is_a_virtuous_organization_How_much_do_you_agree_with_the_following_statements 0.708
## Europe_would_be_best_if_it_remained_all_white_How_much_do_you_agree_with_the_following_statements -0.604
## Immigration_policy_should_be_strict_and_heavily_meritorious_How_much_do_you_agree_with_the_following_statements -0.730
## The_government_should_ensure_racial_equality_by_prohibiting_racial_discrimination_in_private_business_dealings_such_as_hiring_How_much_do_you_agree_with_the_following_statements 0.641
## Black_people_deserve_reparations_for_the_legacy_of_slavery_How_much_do_you_agree_with_the_following_statements 0.622
## I_support_open_borders_How_much_do_you_agree_with_the_following_statements 0.615
## Politics_suffers_from_white_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.822
## Affirmative_action_is_discrimination_How_much_do_you_agree_with_the_following_statements -0.627
## Compared_to_other_civilizations_Western_civilization_is_uniquely_evil_How_much_do_you_agree_with_the_following_statements 0.248
## Racial_diversity_is_more_important_than_viewpoint_diversity_How_much_do_you_agree_with_the_following_statements 0.434
## The_world_is_suffering_from_overpopulation_How_much_do_you_agree_with_the_following_statements 0.380
## I_feel_overwhelmed_or_anxious_by_climate_change_How_much_do_you_agree_with_the_following_statements 0.651
## Public_policy_changes_do_not_need_to_be_made_to_deal_with_climate_change_How_much_do_you_agree_with_the_following_statements -0.670
## Are_you_politically_left_wing_or_right_wing -0.767
## h2
## There_are_objective_measures_of_beauty_How_much_do_you_agree_with_the_following_statements 0.0854
## The_label_overweight_is_offensive_How_much_do_you_agree_with_the_following_statements 0.0115
## Beauty_standards_are_oppressive_How_much_do_you_agree_with_the_following_statements 0.2574
## Body_positivity_is_harmful_How_much_do_you_agree_with_the_following_statements 0.0798
## I_support_the_LGBT_community_How_much_do_you_agree_with_the_following_statements 0.7894
## Homosexual_behavior_is_fine_when_it_is_private_and_chaste_How_much_do_you_agree_with_the_following_statements 0.0113
## There_is_nothing_wrong_with_public_depictions_of_homosexual_relationships_How_much_do_you_agree_with_the_following_statements 0.7531
## I_support_gay_marriage_How_much_do_you_agree_with_the_following_statements 0.7570
## There_is_nothing_wrong_with_attending_a_gay_orgy_How_much_do_you_agree_with_the_following_statements 0.5826
## Children_should_be_taught_about_gay_sex_in_sex_education_classes_How_much_do_you_agree_with_the_following_statements 0.6018
## There_are_only_two_genders_How_much_do_you_agree_with_the_following_statements 0.7155
## Everyone_be_addressed_by_their_desired_pronouns_How_much_do_you_agree_with_the_following_statements 0.7224
## I_support_feminism_How_much_do_you_agree_with_the_following_statements 0.6978
## The_country_would_be_better_if_women_couldn_t_vote_How_much_do_you_agree_with_the_following_statements 0.2663
## Women_should_try_to_be_married_by_the_age_of_25_How_much_do_you_agree_with_the_following_statements 0.2507
## The_government_should_help_ensure_sexual_equality_by_making_sure_women_are_not_discriminated_against_in_private_hiring_How_much_do_you_agree_with_the_following_statements 0.4808
## Women_should_hold_the_majority_of_the_positions_of_power_in_society_How_much_do_you_agree_with_the_following_statements 0.2940
## Marriage_is_oppressive_for_women_and_monogamy_should_be_moved_away_from_How_much_do_you_agree_with_the_following_statements 0.1764
## Men_should_be_masculine_and_women_should_be_feminine_How_much_do_you_agree_with_the_following_statements 0.5782
## Politics_suffers_from_male_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.6494
## Abortion_should_be_available_to_women_for_use_for_any_reason_How_much_do_you_agree_with_the_following_statements 0.6663
## I_support_sending_more_aid_to_Ukraine_How_much_do_you_agree_with_the_following_statements 0.4404
## The_Western_response_to_the_Russian_invasion_of_Ukraine_went_too_far_How_much_do_you_agree_with_the_following_statements 0.2608
## Progressive_taxation_where_the_rich_are_taxed_at_a_higher_rate_is_the_best_way_to_structure_a_tax_system_How_much_do_you_agree_with_the_following_statements 0.4818
## Reducing_taxes_for_businesses_can_stimulate_economic_growth_How_much_do_you_agree_with_the_following_statements 0.3054
## I_support_Israel_against_Hamas_How_much_do_you_agree_with_the_following_statements 0.2539
## Israel_is_commiting_genocide_in_Gaza_How_much_do_you_agree_with_the_following_statements 0.4189
## Black_Lives_Matter_is_a_virtuous_organization_How_much_do_you_agree_with_the_following_statements 0.5016
## Europe_would_be_best_if_it_remained_all_white_How_much_do_you_agree_with_the_following_statements 0.3647
## Immigration_policy_should_be_strict_and_heavily_meritorious_How_much_do_you_agree_with_the_following_statements 0.5326
## The_government_should_ensure_racial_equality_by_prohibiting_racial_discrimination_in_private_business_dealings_such_as_hiring_How_much_do_you_agree_with_the_following_statements 0.4105
## Black_people_deserve_reparations_for_the_legacy_of_slavery_How_much_do_you_agree_with_the_following_statements 0.3864
## I_support_open_borders_How_much_do_you_agree_with_the_following_statements 0.3786
## Politics_suffers_from_white_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.6758
## Affirmative_action_is_discrimination_How_much_do_you_agree_with_the_following_statements 0.3929
## Compared_to_other_civilizations_Western_civilization_is_uniquely_evil_How_much_do_you_agree_with_the_following_statements 0.0617
## Racial_diversity_is_more_important_than_viewpoint_diversity_How_much_do_you_agree_with_the_following_statements 0.1886
## The_world_is_suffering_from_overpopulation_How_much_do_you_agree_with_the_following_statements 0.1441
## I_feel_overwhelmed_or_anxious_by_climate_change_How_much_do_you_agree_with_the_following_statements 0.4232
## Public_policy_changes_do_not_need_to_be_made_to_deal_with_climate_change_How_much_do_you_agree_with_the_following_statements 0.4486
## Are_you_politically_left_wing_or_right_wing 0.5879
##
## SS loadings: 17.1
## Proportion Var: 0.417
##
## Factor correlations:
##
## F1
## F1 1
#item stats
irt_pol_all_item_stats = get_mirt_stats(irt_pol_all)
irt_pol_all_item_stats$loading %>% abs() %>% describe2()
#scores
irt_pol_all_scores = fscores(irt_pol_all, full.scores = T, full.scores.SE = T)
d$leftism = irt_pol_all_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_pol_all_scores)
## F1
## 0.968
marginal_rxx(irt_pol_all)
## [1] 0.969
get_reliabilities(irt_pol_all) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot
d %>%
GG_denhist("leftism") +
scale_x_continuous("Leftism (IRT score from 42 items)")
## Scale for x is already present.
## Adding another scale for x, which will replace the existing scale.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

GG_save("figs/dist leftism.png")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#by party
d %>%
GG_group_means("leftism", "What_is_your_party_registration")

#gaps in politics by party
SMD_matrix(d$leftism, d$What_is_your_party_registration)
## Democrat Independent Other - Write In Republican
## Democrat NA 0.787 0.490 1.752
## Independent 0.787 NA -0.297 0.965
## Other - Write In 0.490 -0.297 NA 1.263
## Republican 1.752 0.965 1.263 NA
lm(leftism ~ What_is_your_party_registration, data = d) %>% summary()
##
## Call:
## lm(formula = leftism ~ What_is_your_party_registration, data = d)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.1505 -0.5510 -0.0014 0.5261 2.7291
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 0.5750 0.0403 14.26
## What_is_your_party_registrationIndependent -0.6432 0.0627 -10.25
## What_is_your_party_registrationOther - Write In -0.4001 0.1828 -2.19
## What_is_your_party_registrationRepublican -1.4320 0.0650 -22.04
## Pr(>|t|)
## (Intercept) <2e-16 ***
## What_is_your_party_registrationIndependent <2e-16 ***
## What_is_your_party_registrationOther - Write In 0.029 *
## What_is_your_party_registrationRepublican <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.817 on 974 degrees of freedom
## Multiple R-squared: 0.334, Adjusted R-squared: 0.332
## F-statistic: 163 on 3 and 974 DF, p-value: <2e-16
#by wave
d %>%
GG_group_means("leftism", "survey_wave")

#gaps in politics by wave
SMD_matrix(d$leftism, d$survey_wave)
## wave 1 wave 2
## wave 1 NA 0.224
## wave 2 0.224 NA
#age
d %>%
GG_scatter("leftism", "age") +
geom_smooth()
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

GG_save("figs/leftism_age.png")
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
#sex
d %>%
GG_group_means("leftism", "sex")

#gaps in politics
SMD_matrix(d$leftism, d$sex)
## Female Male
## Female NA 0.345
## Male 0.345 NA
#make median split
d$leftism_median_split = d$leftism %>% kirkegaard::discretize(2, equal_range = F, labels = "integer") %>% case_match(1 ~ "Low", 2 ~ "High")
d$leftism_median_split %>% table2()
#with items reversed
pol_vars_num_rev = map2_df(pol_vars_num,
irt_pol_all_item_stats$loading > 0,
function(x, y) {
if (y) {
x
} else {
x %>% reverse_scale()
}
})
#refit
irt_pol_all_rev = mirt(
pol_vars_num_rev,
itemtype = pol_vars_options$itemtype,
model = 1,
technical = list(NCYCLES = 5000)
)
## Iteration: 1, Log-Lik: -64899.921, Max-Change: 1.96082Iteration: 2, Log-Lik: -63293.792, Max-Change: 0.33245Iteration: 3, Log-Lik: -63042.610, Max-Change: 0.20000Iteration: 4, Log-Lik: -63001.184, Max-Change: 0.18843Iteration: 5, Log-Lik: -62966.150, Max-Change: 0.16475Iteration: 6, Log-Lik: -62943.892, Max-Change: 0.09410Iteration: 7, Log-Lik: -62927.998, Max-Change: 0.09155Iteration: 8, Log-Lik: -62918.087, Max-Change: 0.06230Iteration: 9, Log-Lik: -62909.410, Max-Change: 0.07379Iteration: 10, Log-Lik: -62903.635, Max-Change: 0.03878Iteration: 11, Log-Lik: -62897.856, Max-Change: 0.04867Iteration: 12, Log-Lik: -62894.520, Max-Change: 0.03401Iteration: 13, Log-Lik: -62891.429, Max-Change: 0.04175Iteration: 14, Log-Lik: -62888.600, Max-Change: 0.03112Iteration: 15, Log-Lik: -62886.490, Max-Change: 0.03307Iteration: 16, Log-Lik: -62884.727, Max-Change: 0.03773Iteration: 17, Log-Lik: -62883.350, Max-Change: 0.01951Iteration: 18, Log-Lik: -62881.582, Max-Change: 0.02199Iteration: 19, 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Max-Change: 0.00012Iteration: 731, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 732, Log-Lik: -62873.162, Max-Change: 0.00023Iteration: 733, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 734, Log-Lik: -62873.162, Max-Change: 0.00017Iteration: 735, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 736, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 737, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 738, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 739, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 740, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 741, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 742, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 743, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 744, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 745, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 746, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 747, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 748, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 749, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 750, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 751, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 752, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 753, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 754, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 755, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 756, Log-Lik: -62873.162, Max-Change: 0.00022Iteration: 757, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 758, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 759, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 760, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 761, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 762, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 763, Log-Lik: -62873.162, Max-Change: 0.00011Iteration: 764, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 765, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 766, Log-Lik: -62873.162, Max-Change: 0.00012Iteration: 767, Log-Lik: -62873.162, Max-Change: 0.00015Iteration: 768, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 769, Log-Lik: -62873.162, Max-Change: 0.00011Iteration: 770, Log-Lik: -62873.162, Max-Change: 0.00016Iteration: 771, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 772, Log-Lik: -62873.162, Max-Change: 0.00011Iteration: 773, Log-Lik: -62873.162, Max-Change: 0.00015Iteration: 774, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 775, Log-Lik: -62873.162, Max-Change: 0.00011Iteration: 776, Log-Lik: -62873.162, Max-Change: 0.00015Iteration: 777, Log-Lik: -62873.162, Max-Change: 0.00021Iteration: 778, Log-Lik: -62873.162, Max-Change: 0.00011Iteration: 779, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 780, Log-Lik: -62873.161, Max-Change: 0.00021Iteration: 781, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 782, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 783, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 784, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 785, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 786, Log-Lik: -62873.161, Max-Change: 0.00021Iteration: 787, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 788, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 789, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 790, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 791, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 792, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 793, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 794, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 795, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 796, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 797, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 798, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 799, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 800, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 801, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 802, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 803, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 804, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 805, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 806, Log-Lik: -62873.161, Max-Change: 0.00015Iteration: 807, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 808, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 809, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 810, Log-Lik: -62873.161, Max-Change: 0.00020Iteration: 811, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 812, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 813, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 814, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 815, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 816, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 817, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 818, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 819, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 820, Log-Lik: -62873.161, Max-Change: 0.00011Iteration: 821, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 822, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 823, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 824, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 825, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 826, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 827, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 828, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 829, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 830, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 831, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 832, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 833, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 834, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 835, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 836, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 837, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 838, Log-Lik: -62873.161, Max-Change: 0.00010Iteration: 839, Log-Lik: -62873.161, Max-Change: 0.00014Iteration: 840, Log-Lik: -62873.161, Max-Change: 0.00019Iteration: 841, Log-Lik: -62873.161, Max-Change: 0.00010
irt_pol_all_rev
##
## Call:
## mirt(data = pol_vars_num_rev, model = 1, itemtype = pol_vars_options$itemtype,
## technical = list(NCYCLES = 5000))
##
## Full-information item factor analysis with 1 factor(s).
## Converged within 1e-04 tolerance after 841 EM iterations.
## mirt version: 1.44.0
## M-step optimizer: BFGS
## EM acceleration: Ramsay
## Number of rectangular quadrature: 61
## Latent density type: Gaussian
##
## Log-likelihood = -62873
## Estimated parameters: 287
## AIC = 126320
## BIC = 127722; SABIC = 126811
## G2 (1e+10) = 112278, p = 1
## RMSEA = 0, CFI = NaN, TLI = NaN
irt_pol_all_rev %>% summary()
## F1
## There_are_objective_measures_of_beauty_How_much_do_you_agree_with_the_following_statements 0.292
## The_label_overweight_is_offensive_How_much_do_you_agree_with_the_following_statements 0.107
## Beauty_standards_are_oppressive_How_much_do_you_agree_with_the_following_statements 0.507
## Body_positivity_is_harmful_How_much_do_you_agree_with_the_following_statements 0.282
## I_support_the_LGBT_community_How_much_do_you_agree_with_the_following_statements 0.888
## Homosexual_behavior_is_fine_when_it_is_private_and_chaste_How_much_do_you_agree_with_the_following_statements 0.106
## There_is_nothing_wrong_with_public_depictions_of_homosexual_relationships_How_much_do_you_agree_with_the_following_statements 0.868
## I_support_gay_marriage_How_much_do_you_agree_with_the_following_statements 0.870
## There_is_nothing_wrong_with_attending_a_gay_orgy_How_much_do_you_agree_with_the_following_statements 0.763
## Children_should_be_taught_about_gay_sex_in_sex_education_classes_How_much_do_you_agree_with_the_following_statements 0.776
## There_are_only_two_genders_How_much_do_you_agree_with_the_following_statements 0.846
## Everyone_be_addressed_by_their_desired_pronouns_How_much_do_you_agree_with_the_following_statements 0.850
## I_support_feminism_How_much_do_you_agree_with_the_following_statements 0.835
## The_country_would_be_better_if_women_couldn_t_vote_How_much_do_you_agree_with_the_following_statements 0.516
## Women_should_try_to_be_married_by_the_age_of_25_How_much_do_you_agree_with_the_following_statements 0.501
## The_government_should_help_ensure_sexual_equality_by_making_sure_women_are_not_discriminated_against_in_private_hiring_How_much_do_you_agree_with_the_following_statements 0.693
## Women_should_hold_the_majority_of_the_positions_of_power_in_society_How_much_do_you_agree_with_the_following_statements 0.542
## Marriage_is_oppressive_for_women_and_monogamy_should_be_moved_away_from_How_much_do_you_agree_with_the_following_statements 0.420
## Men_should_be_masculine_and_women_should_be_feminine_How_much_do_you_agree_with_the_following_statements 0.760
## Politics_suffers_from_male_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.806
## Abortion_should_be_available_to_women_for_use_for_any_reason_How_much_do_you_agree_with_the_following_statements 0.816
## I_support_sending_more_aid_to_Ukraine_How_much_do_you_agree_with_the_following_statements 0.664
## The_Western_response_to_the_Russian_invasion_of_Ukraine_went_too_far_How_much_do_you_agree_with_the_following_statements 0.511
## Progressive_taxation_where_the_rich_are_taxed_at_a_higher_rate_is_the_best_way_to_structure_a_tax_system_How_much_do_you_agree_with_the_following_statements 0.694
## Reducing_taxes_for_businesses_can_stimulate_economic_growth_How_much_do_you_agree_with_the_following_statements 0.553
## I_support_Israel_against_Hamas_How_much_do_you_agree_with_the_following_statements 0.504
## Israel_is_commiting_genocide_in_Gaza_How_much_do_you_agree_with_the_following_statements 0.647
## Black_Lives_Matter_is_a_virtuous_organization_How_much_do_you_agree_with_the_following_statements 0.708
## Europe_would_be_best_if_it_remained_all_white_How_much_do_you_agree_with_the_following_statements 0.604
## Immigration_policy_should_be_strict_and_heavily_meritorious_How_much_do_you_agree_with_the_following_statements 0.730
## The_government_should_ensure_racial_equality_by_prohibiting_racial_discrimination_in_private_business_dealings_such_as_hiring_How_much_do_you_agree_with_the_following_statements 0.641
## Black_people_deserve_reparations_for_the_legacy_of_slavery_How_much_do_you_agree_with_the_following_statements 0.621
## I_support_open_borders_How_much_do_you_agree_with_the_following_statements 0.615
## Politics_suffers_from_white_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.822
## Affirmative_action_is_discrimination_How_much_do_you_agree_with_the_following_statements 0.627
## Compared_to_other_civilizations_Western_civilization_is_uniquely_evil_How_much_do_you_agree_with_the_following_statements 0.248
## Racial_diversity_is_more_important_than_viewpoint_diversity_How_much_do_you_agree_with_the_following_statements 0.434
## The_world_is_suffering_from_overpopulation_How_much_do_you_agree_with_the_following_statements 0.379
## I_feel_overwhelmed_or_anxious_by_climate_change_How_much_do_you_agree_with_the_following_statements 0.650
## Public_policy_changes_do_not_need_to_be_made_to_deal_with_climate_change_How_much_do_you_agree_with_the_following_statements 0.670
## Are_you_politically_left_wing_or_right_wing 0.767
## h2
## There_are_objective_measures_of_beauty_How_much_do_you_agree_with_the_following_statements 0.0853
## The_label_overweight_is_offensive_How_much_do_you_agree_with_the_following_statements 0.0115
## Beauty_standards_are_oppressive_How_much_do_you_agree_with_the_following_statements 0.2573
## Body_positivity_is_harmful_How_much_do_you_agree_with_the_following_statements 0.0798
## I_support_the_LGBT_community_How_much_do_you_agree_with_the_following_statements 0.7893
## Homosexual_behavior_is_fine_when_it_is_private_and_chaste_How_much_do_you_agree_with_the_following_statements 0.0113
## There_is_nothing_wrong_with_public_depictions_of_homosexual_relationships_How_much_do_you_agree_with_the_following_statements 0.7531
## I_support_gay_marriage_How_much_do_you_agree_with_the_following_statements 0.7569
## There_is_nothing_wrong_with_attending_a_gay_orgy_How_much_do_you_agree_with_the_following_statements 0.5824
## Children_should_be_taught_about_gay_sex_in_sex_education_classes_How_much_do_you_agree_with_the_following_statements 0.6016
## There_are_only_two_genders_How_much_do_you_agree_with_the_following_statements 0.7153
## Everyone_be_addressed_by_their_desired_pronouns_How_much_do_you_agree_with_the_following_statements 0.7223
## I_support_feminism_How_much_do_you_agree_with_the_following_statements 0.6978
## The_country_would_be_better_if_women_couldn_t_vote_How_much_do_you_agree_with_the_following_statements 0.2663
## Women_should_try_to_be_married_by_the_age_of_25_How_much_do_you_agree_with_the_following_statements 0.2507
## The_government_should_help_ensure_sexual_equality_by_making_sure_women_are_not_discriminated_against_in_private_hiring_How_much_do_you_agree_with_the_following_statements 0.4808
## Women_should_hold_the_majority_of_the_positions_of_power_in_society_How_much_do_you_agree_with_the_following_statements 0.2939
## Marriage_is_oppressive_for_women_and_monogamy_should_be_moved_away_from_How_much_do_you_agree_with_the_following_statements 0.1763
## Men_should_be_masculine_and_women_should_be_feminine_How_much_do_you_agree_with_the_following_statements 0.5780
## Politics_suffers_from_male_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.6493
## Abortion_should_be_available_to_women_for_use_for_any_reason_How_much_do_you_agree_with_the_following_statements 0.6663
## I_support_sending_more_aid_to_Ukraine_How_much_do_you_agree_with_the_following_statements 0.4403
## The_Western_response_to_the_Russian_invasion_of_Ukraine_went_too_far_How_much_do_you_agree_with_the_following_statements 0.2607
## Progressive_taxation_where_the_rich_are_taxed_at_a_higher_rate_is_the_best_way_to_structure_a_tax_system_How_much_do_you_agree_with_the_following_statements 0.4817
## Reducing_taxes_for_businesses_can_stimulate_economic_growth_How_much_do_you_agree_with_the_following_statements 0.3053
## I_support_Israel_against_Hamas_How_much_do_you_agree_with_the_following_statements 0.2538
## Israel_is_commiting_genocide_in_Gaza_How_much_do_you_agree_with_the_following_statements 0.4188
## Black_Lives_Matter_is_a_virtuous_organization_How_much_do_you_agree_with_the_following_statements 0.5014
## Europe_would_be_best_if_it_remained_all_white_How_much_do_you_agree_with_the_following_statements 0.3647
## Immigration_policy_should_be_strict_and_heavily_meritorious_How_much_do_you_agree_with_the_following_statements 0.5325
## The_government_should_ensure_racial_equality_by_prohibiting_racial_discrimination_in_private_business_dealings_such_as_hiring_How_much_do_you_agree_with_the_following_statements 0.4105
## Black_people_deserve_reparations_for_the_legacy_of_slavery_How_much_do_you_agree_with_the_following_statements 0.3862
## I_support_open_borders_How_much_do_you_agree_with_the_following_statements 0.3784
## Politics_suffers_from_white_overrepresentation_How_much_do_you_agree_with_the_following_statements 0.6757
## Affirmative_action_is_discrimination_How_much_do_you_agree_with_the_following_statements 0.3928
## Compared_to_other_civilizations_Western_civilization_is_uniquely_evil_How_much_do_you_agree_with_the_following_statements 0.0616
## Racial_diversity_is_more_important_than_viewpoint_diversity_How_much_do_you_agree_with_the_following_statements 0.1885
## The_world_is_suffering_from_overpopulation_How_much_do_you_agree_with_the_following_statements 0.1440
## I_feel_overwhelmed_or_anxious_by_climate_change_How_much_do_you_agree_with_the_following_statements 0.4231
## Public_policy_changes_do_not_need_to_be_made_to_deal_with_climate_change_How_much_do_you_agree_with_the_following_statements 0.4485
## Are_you_politically_left_wing_or_right_wing 0.5878
##
## SS loadings: 17.1
## Proportion Var: 0.417
##
## Factor correlations:
##
## F1
## F1 1
#item stats
irt_pol_all_rev_item_stats = get_mirt_stats(irt_pol_all_rev)
irt_pol_all_rev_item_stats$loading %>% describe2()
#scores
irt_pol_all_rev_scores = fscores(irt_pol_all_rev, full.scores = T, full.scores.SE = T)
d$leftism_rev = irt_pol_all_rev_scores[, 1] %>% standardize()
#reliability
empirical_rxx(irt_pol_all_rev_scores)
## F1
## 0.968
marginal_rxx(irt_pol_all_rev)
## [1] 0.969
get_reliabilities(irt_pol_all_rev) %>%
ggplot(aes(z, rel)) +
geom_line()

#plot
d %>%
GG_denhist("leftism_rev")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

#compare
GG_scatter(d, "leftism", "leftism_rev") +
geom_smooth()
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'
