x_liveanalysis

Block Frequencies

Block Assignment Frequency Table
Block1	Block2	Block3	Block4	Block5
122	130	121	122	126

Demographic Information

Frequency Table by Category
Category	Type	Count
Ethnicity	asian	92
Ethnicity	black	105
Ethnicity	mixed	60
Ethnicity	other	8
Ethnicity	white	356
Gender	female	301
Gender	male	313
Gender	non_binary	1
Gender	other	1
Gender	prefer_not_to_say	1
Gender	trans_gender	4
Age	11	202
Age	12	91
Age	13	55
Age	14	56
Age	15	75
Age	16	56
Age	17	70
Age	prefer_not_say	16

Best-Worst Frequency Table

kable(round(sum(mr_scores, "level"), 3), caption = "Best-Worst Frequency Table")

Best-Worst Frequency Table
	B	W	BW	stdBW
tired_1	473	64	409	0.329
tired_2	391	60	331	0.267
tired_3	156	145	11	0.009
tired_4	74	234	-160	-0.129
tired_5	52	348	-296	-0.238
walking_1	419	85	334	0.269
walking_2	250	86	164	0.132
walking_3	94	126	-32	-0.026
walking_4	71	162	-91	-0.073
walking_5	68	251	-183	-0.147
sports_1	394	101	293	0.236
sports_2	259	89	170	0.137
sports_3	129	132	-3	-0.002
sports_4	89	194	-105	-0.085
sports_5	98	233	-135	-0.109
concentration_1	420	94	326	0.262
concentration_2	269	98	171	0.138
concentration_3	91	194	-103	-0.083
concentration_4	78	265	-187	-0.151
concentration_5	73	358	-285	-0.229
embarrassed_1	355	93	262	0.211
embarrassed_2	178	135	43	0.035
embarrassed_3	75	165	-90	-0.072
embarrassed_4	71	206	-135	-0.109
embarrassed_5	42	241	-199	-0.160
unhappiness_1	399	97	302	0.243
unhappiness_2	227	115	112	0.090
unhappiness_3	78	216	-138	-0.111
unhappiness_4	66	310	-244	-0.196
unhappiness_5	74	383	-309	-0.249
treated_1	316	69	247	0.199
treated_2	205	116	89	0.072
treated_3	74	165	-91	-0.073
treated_4	51	248	-197	-0.159
treated_5	51	332	-281	-0.226

MNL Model Results

source("3_MNL.R")
mr_out %>%
  tidy() %>%
  kable( 
    caption = "Coefficient-Level Estimates for a MNL Model",
    col.names = c("Parameter", "B", "SE", "t", "p"),
    digits = c(0, 3, 3, 3, 3))

Coefficient-Level Estimates for a MNL Model
Parameter	B	SE	t	p
tired_2	1.003	0.052	19.252	0.000
tired_3	-0.179	0.055	-3.267	0.001
tired_4	-0.812	0.053	-15.419	0.000
tired_5	-1.248	0.051	-24.523	0.000
walking_2	0.516	0.055	9.459	0.000
walking_3	-0.272	0.055	-4.908	0.000
walking_4	-0.498	0.054	-9.144	0.000
walking_5	-0.827	0.053	-15.596	0.000
sports_2	0.531	0.055	9.699	0.000
sports_3	-0.188	0.056	-3.370	0.001
sports_4	-0.580	0.054	-10.692	0.000
sports_5	-0.688	0.054	-12.831	0.000
concentration_2	0.737	0.054	13.767	0.000
concentration_3	-0.328	0.055	-5.991	0.000
concentration_4	-0.650	0.054	-12.135	0.000
concentration_5	-0.971	0.052	-18.646	0.000
embarrassed_2	0.318	0.055	5.746	0.000
embarrassed_3	-0.262	0.056	-4.703	0.000
embarrassed_4	-0.426	0.055	-7.795	0.000
embarrassed_5	-0.671	0.054	-12.467	0.000
unhappiness_2	0.676	0.054	12.561	0.000
unhappiness_3	-0.312	0.055	-5.705	0.000
unhappiness_4	-0.715	0.053	-13.372	0.000
unhappiness_5	-0.920	0.052	-17.616	0.000
treated_2	0.546	0.054	10.048	0.000
treated_3	-0.167	0.055	-3.015	0.003
treated_4	-0.585	0.054	-10.784	0.000
treated_5	-0.871	0.053	-16.508	0.000

Relative Attribute Scores

Relative Attribute Score Table
	RAI
Tired	0.177
Unhappiness	0.156
Concentration	0.156
Treated_Differently	0.139
Walking	0.136
Embarrassed	0.122
Sports	0.115

Valueset results

kable(round(anchored_coefs, 3))

	Tired	Walking	Sports	Concentration	Embarrassed	Unhappiness	Treated
Never	0.000	0.000	0.000	0.000	0.000	0.000	0.000
Almost never	0.012	0.029	0.020	0.024	0.037	0.030	0.027
Sometimes	0.072	0.069	0.057	0.079	0.067	0.081	0.064
Often	0.105	0.081	0.077	0.095	0.075	0.102	0.085
Always	0.127	0.098	0.082	0.112	0.088	0.112	0.100

BWS Adolescent: analysis (n=621)

Block Frequencies

Demographic Information

Best-Worst Frequency Table

MNL Model Results

Relative Attribute Scores

Valueset results