CFA

Packages

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.2     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(haven)
library(janitor)

Attaching package: 'janitor'

The following objects are masked from 'package:stats':

    chisq.test, fisher.test

library(sjPlot)

Learn more about sjPlot with 'browseVignettes("sjPlot")'.

library(lavaan)

This is lavaan 0.6-19
lavaan is FREE software! Please report any bugs.

Read Data

library(haven)
df_mod <- read_sav("~/Downloads/df_mod.sav")
View(df_mod)

df_mod |>
  skimr::skim()

Data summary

Name	df_mod
Number of rows	576
Number of columns	45
_______________________
Column type frequency:
numeric	45
________________________
Group variables	None

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
age	0	1	40.79	13.50	19	30	38.5	50	80	▆▇▅▂▁
edu	0	1	3.55	1.05	1	3	4.0	4	6	▅▃▇▃▁
inc	0	1	3.46	1.57	1	2	3.0	5	7	▇▆▅▅▂
nfc_1	0	1	4.50	1.56	1	3	5.0	6	7	▃▃▅▇▇
nfc_2	0	1	4.73	1.53	1	4	5.0	6	7	▂▂▃▆▇
nfc_3r	0	1	5.14	1.61	1	4	6.0	6	7	▂▁▁▃▇
nfc_4r	0	1	4.80	1.57	1	4	5.0	6	7	▂▂▂▆▇
nfc_5	0	1	5.09	1.47	1	4	5.0	6	7	▁▂▂▅▇
nfc_6	0	1	4.75	1.52	1	4	5.0	6	7	▂▂▃▆▇
cc_1	0	1	5.39	1.26	1	5	5.0	6	7	▁▁▂▅▇
cc_2	0	1	5.27	1.20	1	5	5.0	6	7	▁▁▃▆▇
cc_3	0	1	5.16	1.28	1	4	5.0	6	7	▁▁▃▅▇
cc_4	0	1	5.19	1.28	1	4	5.0	6	7	▁▂▃▅▇
cc_5	0	1	5.41	1.10	1	5	5.0	6	7	▁▁▂▆▇
cc_6	0	1	5.17	1.27	1	4	5.0	6	7	▁▂▃▆▇
sce_1c	0	1	1.59	0.90	1	1	1.0	2	6	▇▁▁▁▁
sce_2c	0	1	2.83	1.25	1	2	3.0	4	6	▇▅▃▁▁
sce_3c	0	1	3.22	1.68	1	2	3.0	4	6	▇▃▅▂▃
sce_4c	0	1	2.63	0.99	1	2	2.0	3	6	▇▅▂▁▁
sce_5c	0	1	4.72	1.31	1	4	5.0	6	6	▂▂▅▆▇
sce_6c	0	1	3.09	1.43	1	2	3.0	4	6	▇▃▆▂▁
sce_7c	0	1	3.76	1.59	1	3	4.0	5	6	▇▅▇▅▆
sce_8c	0	1	4.01	1.37	1	3	4.0	5	6	▃▃▇▃▃
sce_9c	0	1	4.46	1.39	1	4	5.0	6	6	▃▃▇▆▇
sce_10c	0	1	3.41	1.30	1	3	3.0	4	6	▆▇▇▃▂
sce_11c	0	1	5.19	1.01	1	5	5.0	6	6	▁▁▂▅▇
atb_1	0	1	6.32	0.99	1	6	7.0	7	7	▁▁▁▁▇
atb_2	0	1	5.97	1.16	1	5	6.0	7	7	▁▁▂▂▇
atb_3	0	1	5.73	1.29	1	5	6.0	7	7	▁▁▂▂▇
atb_4	0	1	6.22	1.09	1	6	7.0	7	7	▁▁▁▁▇
atb_5	0	1	6.08	1.11	1	5	6.0	7	7	▁▁▁▂▇
atb_6	0	1	5.95	1.23	1	5	6.0	7	7	▁▁▁▂▇
atb_7	0	1	6.12	1.21	1	6	7.0	7	7	▁▁▁▁▇
sn1	0	1	4.41	1.33	1	4	4.0	5	7	▂▁▇▃▃
sn2	0	1	3.49	1.51	1	2	4.0	4	7	▇▃▇▂▂
sn3	0	1	4.28	1.28	1	4	4.0	5	7	▂▂▇▅▃
pbc_1	0	1	6.13	1.05	2	6	6.0	7	7	▁▁▃▅▇
pbc_2	0	1	5.78	1.16	1	5	6.0	7	7	▁▁▁▂▇
pbc_3	0	1	5.50	1.35	1	5	6.0	7	7	▁▁▂▃▇
pbc_4	0	1	6.06	1.04	2	5	6.0	7	7	▁▁▃▆▇
pbc_5	0	1	5.87	1.08	1	5	6.0	7	7	▁▁▁▃▇
pbc_6	0	1	5.59	1.29	1	5	6.0	7	7	▁▁▂▃▇
bi1	0	1	6.17	1.07	1	6	6.0	7	7	▁▁▁▁▇
bi2	0	1	4.97	1.42	1	4	5.0	6	7	▁▂▅▅▇
bi3	0	1	6.33	0.96	1	6	7.0	7	7	▁▁▁▁▇

df_mod |>
  view_df()

Data frame: df_mod

ID	Name	Label	Values	Value Labels
1	age		range: 19-80
2	edu	What is the highest level of education you have achieved? - Selected Choice	1 2 3 4 5 6	Less than high school degree High school degree (or equivalent including GED) Two-Year College Degree (Associates or Other Technical Degree) Four-Year College Degree (Bachelor’s Degree) Graduate School (Masters or Doctorate) Others (please specify)
3	inc	Information about income is very important to understand. Would you please give your best guess and indicate the answer that includes your entire household income (previous year) before taxes.	1 2 3 4 5 6 7	$24,999 or less $25,000 to $49,999 $50,000 to $74,999 $75,000 to $99,999 $100,000 to $149,999 $150,000 to $199,999 $200,000 or more
4	nfc_1	Please indicate how much you agree or disagree with the following statements. - I would prefer complex rather than simple problems.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
5	nfc_2	Please indicate how much you agree or disagree with the following statements. - I like to have the responsibility of handling a situation that requires a lot of thinking.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
6	nfc_3r		range: 1-7
7	nfc_4r		range: 1-7
8	nfc_5	Please indicate how much you agree or disagree with the following statements. - I really enjoy a task that involves coming up with new solutions to problems.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
9	nfc_6	Please indicate how much you agree or disagree with the following statements. - I would prefer a task that is intellectual, difficult, and important to one that is somewhat important but does not require much thought.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
10	cc_1	Here is another set of opinion statements. Rate how much you agree or disagree with the following statements. - I often think about how larger political and social issues affect my community.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
11	cc_2	Here is another set of opinion statements. Rate how much you agree or disagree with the following statements. - I believe that I should actively participate in civic activities that benefit society as a whole.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
12	cc_3	Here is another set of opinion statements. Rate how much you agree or disagree with the following statements. - I tend to engage in a democratic process for the benefit of my community.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
13	cc_4	Here is another set of opinion statements. Rate how much you agree or disagree with the following statements. - It would be wrong to pursue my self-interest when doing so may harm the interests of others in the community I live in.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
14	cc_5	Here is another set of opinion statements. Rate how much you agree or disagree with the following statements. - A single person’s action, no matter how insignificant it may seem, could affect the progress of the whole society.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
15	cc_6	Here is another set of opinion statements. Rate how much you agree or disagree with the following statements. - When I see someone suffering, I cannot pass by the person without extending my help.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
16	sce_1c	In today’s era of social media, social communities are often formed online. Some people choose to join online communities (e.g., a popular blog, TikTok accounts, Instagram accounts, Subreddit communities) to share viewpoints and get informed on current i	1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
17	sce_2c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
18	sce_3c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
19	sce_4c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
20	sce_5c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
21	sce_6c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
22	sce_7c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
23	sce_8c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
24	sce_9c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
25	sce_10c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
26	sce_11c		1 2 3 4 5 6	Never Couple of times a year Monthly Weekly At least once a day Multiple times a day
27	atb_1	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
28	atb_2	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
29	atb_3	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
30	atb_4	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
31	atb_5	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
32	atb_6	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
33	atb_7	The following questions relate to buying from razor brands that use realistic ads, similar to the way Billie Inc. featured their razor in their ad. Please complete the following sentence with the available options below: “Buying from razor brands that	1 2 3 4 5 6 7	1 2 3 4 5 6 7
34	sn1	Rate how much you agree or disagree with the following statements about the expectations of your behavior from other people in regards to buying from realistic brands similar to Billie Inc. - Most people who are important to me would think I should buy pro	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
35	sn2	Rate how much you agree or disagree with the following statements about the expectations of your behavior from other people in regards to buying from realistic brands similar to Billie Inc. - It is expected of me that I buy products from razor brands that	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
36	sn3	Rate how much you agree or disagree with the following statements about the expectations of your behavior from other people in regards to buying from realistic brands similar to Billie Inc. - Most people similar to me buy products from razor brands that us	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
37	pbc_1	You are doing a great job! In the next set of questions, please rate how much you agree or disagree with the following statements: - Buying from razor brands that use realistic portrayals of women with body hair in their ads is entirely up to me.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
38	pbc_2	You are doing a great job! In the next set of questions, please rate how much you agree or disagree with the following statements: - I am confident that I can buy from razor brands that use realistic portrayals of women with body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
39	pbc_3	You are doing a great job! In the next set of questions, please rate how much you agree or disagree with the following statements: - I have sufficient resources, time, and opportunities to obtain products from razor brands that use realistic portrayals of	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
40	pbc_4	You are doing a great job! In the next set of questions, please rate how much you agree or disagree with the following statements: - I have control over buying from razor brands that use realistic portrayals of women with body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
41	pbc_5	You are doing a great job! In the next set of questions, please rate how much you agree or disagree with the following statements: - I am able to buy from razor brands that use realistic portrayals of women with body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
42	pbc_6	You are doing a great job! In the next set of questions, please rate how much you agree or disagree with the following statements: - I can easily buy from razor brands that use realistic portrayals of women with body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
43	bi1	I would buy products from razor brands that use realistic portrayals of women with body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
44	bi2	I will exert effort toward buying products from razor brands that use realistic portrayals of women’s body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree
45	bi3	I am willing to buy products from razor brands that use realistic portrayals of women’s body hair in their ads.	1 2 3 4 5 6 7	Strongly disagree Disagree Somewhat disagree Neither agree nor disagree Somewhat agree Agree Strongly agree

• Ideal sample size needed to run CFA = # of observed variables * 20

• 45 * 20 = 900

• Okay sample size: # of observed variables * 10

• 45 * 10 = 450

Creating a List

models <- list()
fits <- list()
v <- list()
plots <- list()

Conceptual Model

Conceptual Model

M1

models$m1 <- "
nfc =~ nfc_1 + nfc_2 +nfc_3r +nfc_4r +nfc_5 + nfc_6
cc =~ cc_1 +cc_2 + cc_3 + cc_4 + cc_5 + cc+6
atb =~ atb_1 +atb_2 + atb_3 + atb_4 +  atb_5 +atb_6 + atb_7
sn =~ sn1 + sn2 + sn3
pbc =~ pbc_1 + pbc_2 + pbc_3 + pbc_4 + pbc_5 + pbc_6
bi =~ bi1 + bi2 +bi3
"
fits$m1 <- cfa(models$m1, data = df_mod)
summary(fits$m1, fit.measures = TRUE, standardized = TRUE)

lavaan 0.6-19 ended normally after 54 iterations

  Estimator                                         ML
  Optimization method                           NLMINB
  Number of model parameters                        70

  Number of observations                           576

Model Test User Model:
                                                      
  Test statistic                              1173.407
  Degrees of freedom                               395
  P-value (Chi-square)                           0.000

Model Test Baseline Model:

  Test statistic                             14590.056
  Degrees of freedom                               435
  P-value                                        0.000

User Model versus Baseline Model:

  Comparative Fit Index (CFI)                    0.945
  Tucker-Lewis Index (TLI)                       0.939

Loglikelihood and Information Criteria:

  Loglikelihood user model (H0)             -21700.734
  Loglikelihood unrestricted model (H1)             NA
                                                      
  Akaike (AIC)                               43541.468
  Bayesian (BIC)                             43846.395
  Sample-size adjusted Bayesian (SABIC)      43624.174

Root Mean Square Error of Approximation:

  RMSEA                                          0.058
  90 Percent confidence interval - lower         0.055
  90 Percent confidence interval - upper         0.062
  P-value H_0: RMSEA <= 0.050                    0.000
  P-value H_0: RMSEA >= 0.080                    0.000

Standardized Root Mean Square Residual:

  SRMR                                           0.102

Parameter Estimates:

  Standard errors                             Standard
  Information                                 Expected
  Information saturated (h1) model          Structured

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  nfc =~                                                                
    nfc_1             1.000                               1.408    0.902
    nfc_2             0.989    0.028   35.094    0.000    1.393    0.910
    nfc_3r            0.996    0.032   31.462    0.000    1.402    0.871
    nfc_4r            0.978    0.030   32.281    0.000    1.377    0.881
    nfc_5             0.903    0.029   30.944    0.000    1.272    0.865
    nfc_6             0.970    0.028   34.167    0.000    1.366    0.901
  cc =~                                                                 
    cc_1              1.000                               0.938    0.744
    cc_2              1.054    0.059   17.923    0.000    0.988    0.824
    cc_3              1.045    0.061   17.028    0.000    0.980    0.768
    cc_4              0.747    0.061   12.179    0.000    0.700    0.546
    cc_5              0.716    0.053   13.615    0.000    0.672    0.610
    cc                6.000                               6.000    6.000
  atb =~                                                                
    atb_1             1.000                               0.883    0.889
    atb_2             1.101    0.039   28.126    0.000    0.972    0.837
    atb_3             1.210    0.044   27.569    0.000    1.068    0.828
    atb_4             1.091    0.034   31.878    0.000    0.963    0.886
    atb_5             1.035    0.038   27.464    0.000    0.914    0.827
    atb_6             1.275    0.037   34.770    0.000    1.125    0.919
    atb_7             1.264    0.036   35.260    0.000    1.116    0.924
  sn =~                                                                 
    sn1               1.000                               1.094    0.823
    sn2               1.055    0.063   16.792    0.000    1.154    0.767
    sn3               0.830    0.052   15.918    0.000    0.908    0.709
  pbc =~                                                                
    pbc_1             1.000                               0.851    0.809
    pbc_2             1.216    0.047   26.044    0.000    1.035    0.893
    pbc_3             1.325    0.056   23.710    0.000    1.128    0.839
    pbc_4             1.014    0.043   23.350    0.000    0.863    0.830
    pbc_5             1.111    0.044   25.269    0.000    0.946    0.875
    pbc_6             1.310    0.053   24.821    0.000    1.115    0.865
  bi =~                                                                 
    bi1               1.000                               0.939    0.877
    bi2               1.079    0.057   19.017    0.000    1.013    0.712
    bi3               0.858    0.036   23.599    0.000    0.805    0.841

Covariances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
  nfc ~~                                                                
    atb               0.122    0.054    2.255    0.024    0.098    0.098
    sn                0.114    0.073    1.568    0.117    0.074    0.074
    pbc               0.043    0.053    0.809    0.419    0.035    0.035
    bi                0.195    0.061    3.192    0.001    0.147    0.147
  atb ~~                                                                
    sn                0.431    0.051    8.451    0.000    0.446    0.446
    pbc               0.131    0.034    3.900    0.000    0.175    0.175
    bi                0.577    0.048   12.131    0.000    0.697    0.697
  sn ~~                                                                 
    pbc               0.152    0.045    3.387    0.001    0.164    0.164
    bi                0.509    0.058    8.835    0.000    0.495    0.495
  pbc ~~                                                                
    bi                0.244    0.039    6.236    0.000    0.305    0.305

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)   Std.lv  Std.all
   .nfc_1             0.455    0.033   13.710    0.000    0.455    0.187
   .nfc_2             0.401    0.030   13.340    0.000    0.401    0.171
   .nfc_3r            0.624    0.043   14.621    0.000    0.624    0.241
   .nfc_4r            0.549    0.038   14.389    0.000    0.549    0.224
   .nfc_5             0.544    0.037   14.755    0.000    0.544    0.252
   .nfc_6             0.432    0.031   13.738    0.000    0.432    0.188
   .cc_1              0.710    0.054   13.158    0.000    0.710    0.447
   .cc_2              0.462    0.044   10.466    0.000    0.462    0.321
   .cc_3              0.670    0.053   12.516    0.000    0.670    0.411
   .cc_4              1.157    0.074   15.709    0.000    1.157    0.702
   .cc_5              0.763    0.050   15.200    0.000    0.763    0.628
   .atb_1             0.207    0.014   14.486    0.000    0.207    0.210
   .atb_2             0.405    0.026   15.442    0.000    0.405    0.300
   .atb_3             0.522    0.034   15.538    0.000    0.522    0.314
   .atb_4             0.253    0.017   14.555    0.000    0.253    0.214
   .atb_5             0.386    0.025   15.556    0.000    0.386    0.316
   .atb_6             0.234    0.017   13.391    0.000    0.234    0.156
   .atb_7             0.214    0.016   13.122    0.000    0.214    0.147
   .sn1               0.570    0.063    9.018    0.000    0.570    0.322
   .sn2               0.931    0.082   11.365    0.000    0.931    0.411
   .sn3               0.816    0.062   13.166    0.000    0.816    0.497
   .pbc_1             0.382    0.025   15.021    0.000    0.382    0.345
   .pbc_2             0.272    0.021   12.886    0.000    0.272    0.202
   .pbc_3             0.537    0.037   14.531    0.000    0.537    0.297
   .pbc_4             0.337    0.023   14.697    0.000    0.337    0.312
   .pbc_5             0.273    0.020   13.578    0.000    0.273    0.234
   .pbc_6             0.419    0.030   13.900    0.000    0.419    0.252
   .bi1               0.263    0.029    9.240    0.000    0.263    0.230
   .bi2               0.998    0.068   14.685    0.000    0.998    0.493
   .bi3               0.267    0.024   11.181    0.000    0.267    0.292
    nfc               1.982    0.142   13.914    0.000    1.000    1.000
   .cc                0.879    0.090    9.717    0.000    1.000    1.000
    atb               0.779    0.057   13.602    0.000    1.000    1.000
    sn                1.197    0.112   10.675    0.000    1.000    1.000
    pbc               0.725    0.062   11.629    0.000    1.000    1.000
    bi                0.881    0.070   12.614    0.000    1.000    1.000