1 Correlation plot (Spearman, multiply imputed dataset)

2 Regression models (multiply imputed dataset)

2.1 Model fit measures

Stepwise BIC Model: Fit Measures
est lo 95 hi 95 fmi
R^2 0.221 0.205 0.238 0.046
Stepwise AIC Model: Fit Measures
est lo 95 hi 95 fmi
R^2 0.229 0.212 0.246 0.074
Theory-derived Model 1: Fit Measures
est lo 95 hi 95 fmi
R^2 0.066 0.055 0.077 0.04
Theory-derived Model 2: Fit Measures
est lo 95 hi 95 fmi
R^2 0.122 0.108 0.136 0.063
Theory-derived Model 3: Fit Measures
est lo 95 hi 95 fmi
R^2 0.13 0.116 0.144 0.042
Theory-derived Model 4: Fit Measures
est lo 95 hi 95 fmi
R^2 0.235 0.219 0.252 0.063

2.2 Model coefficients

Stepwise BIC Model: Coefficients
term estimate std.error statistic df 2.5 % 97.5 % p.adjusted
q47_self_reporting_healthvery_bad 9.520 0.800 11.90 6077.1 7.952 11.088 0.000
q47_self_reporting_healthbad 6.406 0.321 19.95 528.9 5.775 7.037 0.000
(Intercept) 5.833 0.275 21.20 2625.3 5.294 6.373 0.000
q47_self_reporting_healthneutral 3.984 0.182 21.83 835.3 3.626 4.342 0.000
q01_genderother 3.516 2.505 1.40 18.2 -1.744 8.776 0.177
q36_econ_worryvery_serious 2.509 0.146 17.20 6592.5 2.223 2.795 0.000
q47_self_reporting_healthgood 1.618 0.146 11.06 1718.6 1.331 1.905 0.000
q01_genderfemale 1.504 0.133 11.32 7060.6 1.244 1.765 0.000
q49_health_limitationslimits 1.363 0.245 5.57 1744.0 0.884 1.843 0.000
q36_econ_worryserious 1.094 0.123 8.87 7645.1 0.852 1.335 0.000
q18_02_soc_mediayes 0.594 0.115 5.17 6732.1 0.369 0.820 0.000
q49_health_limitationspartially_limits 0.489 0.150 3.26 474.2 0.194 0.784 0.004
q04_childrenno 0.359 0.118 3.05 7011.0 0.128 0.591 0.005
q02_age -0.089 0.004 -20.47 6983.2 -0.098 -0.081 0.000
Stepwise AIC Model: Coefficients
term estimate std.error statistic df 2.5 % 97.5 % p.adjusted
q47_self_reporting_healthvery_bad 9.258 0.799 11.592 6881.6 7.692 10.824 0.000
q47_self_reporting_healthbad 6.374 0.324 19.694 769.1 5.739 7.010 0.000
(Intercept) 5.330 0.313 17.037 3529.7 4.716 5.943 0.000
q47_self_reporting_healthneutral 3.944 0.186 21.186 1010.4 3.579 4.310 0.000
q01_genderother 3.694 2.524 1.463 17.3 -1.624 9.012 0.968
q36_econ_worryvery_serious 2.406 0.147 16.356 6873.0 2.117 2.694 0.000
q47_self_reporting_healthgood 1.630 0.146 11.130 1858.4 1.342 1.917 0.000
q01_genderfemale 1.507 0.133 11.334 7497.2 1.246 1.767 0.000
q49_health_limitationslimits 1.293 0.251 5.160 980.8 0.801 1.784 0.000
q36_econ_worryserious 1.043 0.124 8.424 7645.1 0.800 1.286 0.000
q20_public_infono 0.804 0.122 6.591 188.8 0.564 1.045 0.000
q03_relationship_typedivorced 0.793 0.215 3.694 2429.1 0.372 1.214 0.002
q18_02_soc_mediayes 0.537 0.115 4.679 6621.5 0.312 0.762 0.000
q49_health_limitationspartially_limits 0.460 0.164 2.813 213.0 0.138 0.783 0.054
q03_relationship_typesingle 0.363 0.176 2.062 4568.4 0.018 0.708 0.314
q03_relationship_typewidowed 0.299 0.451 0.663 3339.6 -0.586 1.184 1.000
q38_alcoholyes 0.262 0.115 2.275 7079.4 0.036 0.487 0.207
q04_childrenno 0.255 0.136 1.869 5461.9 -0.012 0.522 0.432
q03_relationship_typerelationship -0.196 0.151 -1.299 4175.5 -0.491 0.100 0.971
q40_smokingyes 0.132 0.133 0.996 1939.7 -0.128 0.393 1.000
q02_age -0.089 0.005 -18.682 7459.7 -0.099 -0.080 0.000
q34_02_face_maskno 0.058 0.120 0.483 2544.1 -0.177 0.293 1.000
q48_chronic_illnessyes 0.030 0.139 0.215 1468.9 -0.243 0.303 1.000
Theory-derived Model 1: Coefficients
term estimate std.error statistic df 2.5 % 97.5 % p.adjusted
(Intercept) 7.965 0.309 25.748 1418.5 7.359 8.572 0.000
q01_genderother 5.529 2.626 2.105 22.4 0.089 10.969 0.233
q01_genderfemale 1.867 0.148 12.610 3266.7 1.577 2.157 0.000
q03_relationship_typedivorced 1.060 0.234 4.536 3779.2 0.602 1.518 0.000
q03_relationship_typewidowed 0.802 0.497 1.614 3104.5 -0.172 1.777 0.426
q03_relationship_typesingle 0.707 0.191 3.696 7606.9 0.332 1.083 0.002
q11_educationlow 0.615 0.190 3.240 66.1 0.236 0.995 0.011
q11_educationmedium 0.236 0.162 1.459 48.2 -0.089 0.562 0.426
q04_childrenno 0.226 0.149 1.521 7171.7 -0.065 0.517 0.426
q03_relationship_typerelationship 0.107 0.163 0.652 6666.1 -0.214 0.427 0.514
q02_age -0.074 0.005 -14.459 6753.5 -0.084 -0.064 0.000
Theory-derived Model 2: Coefficients
term estimate std.error statistic df 2.5 % 97.5 % p.adjusted
(Intercept) 6.171 0.323 19.121 981.4 5.537 6.804 0.000
q01_genderother 5.280 2.613 2.020 19.7 -0.176 10.736 0.343
q36_econ_worryvery_serious 2.849 0.159 17.970 4645.4 2.538 3.160 0.000
q01_genderfemale 1.660 0.144 11.533 4963.3 1.378 1.942 0.000
q36_econ_worryserious 1.370 0.133 10.324 5868.8 1.110 1.630 0.000
q20_public_infono 1.082 0.134 8.048 98.2 0.815 1.348 0.000
q34_07_hand_washingno -0.878 0.341 -2.571 3648.8 -1.547 -0.208 0.082
q03_relationship_typedivorced 0.818 0.228 3.592 3042.7 0.371 1.264 0.003
q18_02_soc_mediayes 0.696 0.122 5.696 7844.1 0.456 0.935 0.000
q03_relationship_typesingle 0.609 0.186 3.271 7153.0 0.244 0.974 0.010
q03_relationship_typewidowed 0.490 0.482 1.016 3168.1 -0.456 1.436 1.000
q04_childrenno 0.347 0.145 2.400 6287.9 0.064 0.630 0.115
q11_educationlow 0.230 0.184 1.250 97.2 -0.135 0.596 1.000
q34_02_face_maskno 0.135 0.128 1.055 6230.8 -0.116 0.386 1.000
q11_educationmedium -0.132 0.165 -0.801 38.5 -0.466 0.201 1.000
q02_age -0.066 0.005 -13.192 7288.3 -0.076 -0.056 0.000
q03_relationship_typerelationship -0.055 0.160 -0.346 4857.0 -0.368 0.258 1.000
Theory-derived Model 3: Coefficients
term estimate std.error statistic df 2.5 % 97.5 % p.adjusted
(Intercept) 7.118 0.741 9.612 4577.2 5.666 8.569 0.000
q01_genderother 4.858 2.626 1.850 18.9 -0.639 10.355 0.799
q36_econ_worryvery_serious 2.730 0.159 17.208 5489.7 2.419 3.041 0.000
q01_genderfemale 1.612 0.145 11.156 4683.9 1.329 1.895 0.000
q36_econ_worryserious 1.305 0.132 9.855 6164.9 1.045 1.564 0.000
q35_03_contact_friendsas_before -1.091 0.698 -1.564 7540.7 -2.459 0.276 1.000
q20_public_infono 1.069 0.135 7.933 90.8 0.801 1.336 0.000
q35_01_contact_close_familyas_before -0.943 0.188 -5.027 3120.8 -1.311 -0.575 0.000
q03_relationship_typedivorced 0.755 0.230 3.285 1815.9 0.304 1.206 0.016
q34_07_hand_washingno -0.740 0.343 -2.159 3781.2 -1.412 -0.068 0.341
q18_02_soc_mediayes 0.698 0.122 5.728 7748.6 0.459 0.937 0.000
q03_relationship_typesingle 0.601 0.187 3.222 6953.9 0.235 0.966 0.018
q35_03_contact_friendsless_often -0.562 0.649 -0.866 7922.2 -1.835 0.711 1.000
q42_sportno 0.469 0.120 3.899 1294.3 0.233 0.704 0.002
q03_relationship_typewidowed 0.425 0.479 0.887 4533.9 -0.514 1.364 1.000
q04_childrenno 0.330 0.145 2.274 5777.1 0.046 0.615 0.299
q40_smokingyes 0.312 0.142 2.193 1998.3 0.033 0.591 0.341
q35_01_contact_close_familyless_often -0.211 0.194 -1.087 1396.1 -0.592 0.170 1.000
q11_educationmedium -0.177 0.169 -1.047 35.0 -0.519 0.166 1.000
q34_02_face_maskno 0.170 0.129 1.322 5802.3 -0.082 0.423 1.000
q11_educationlow 0.165 0.188 0.879 81.9 -0.209 0.540 1.000
q03_relationship_typerelationship -0.074 0.160 -0.464 5855.5 -0.387 0.239 1.000
q02_age -0.066 0.005 -13.030 6774.9 -0.076 -0.056 0.000
q38_alcoholyes -0.052 0.123 -0.426 7548.6 -0.293 0.188 1.000
Theory-derived Model 4: Coefficients
term estimate std.error statistic df 2.5 % 97.5 % p.adjusted
q47_self_reporting_healthvery_bad 9.292 0.797 11.653 6688.6 7.729 10.855 0.000
(Intercept) 6.584 0.702 9.375 3958.8 5.207 7.961 0.000
q47_self_reporting_healthbad 6.390 0.324 19.747 819.2 5.755 7.026 0.000
q47_self_reporting_healthneutral 3.916 0.187 20.959 1178.2 3.550 4.283 0.000
q01_genderother 3.313 2.515 1.317 17.4 -1.984 8.610 1.000
q36_econ_worryvery_serious 2.346 0.150 15.651 4005.2 2.052 2.640 0.000
q47_self_reporting_healthgood 1.603 0.147 10.911 1617.2 1.315 1.891 0.000
q01_genderfemale 1.432 0.136 10.533 3906.7 1.166 1.699 0.000
q49_health_limitationslimits 1.252 0.251 4.988 788.5 0.759 1.745 0.000
q35_03_contact_friendsas_before -1.118 0.656 -1.706 7173.6 -2.404 0.167 1.000
q36_econ_worryserious 1.013 0.125 8.137 6551.2 0.769 1.257 0.000
q20_public_infono 0.804 0.123 6.527 148.8 0.561 1.048 0.000
q35_01_contact_close_familyas_before -0.779 0.176 -4.420 2913.7 -1.124 -0.433 0.000
q03_relationship_typedivorced 0.745 0.216 3.455 1820.0 0.322 1.168 0.010
q34_07_hand_washingno -0.730 0.325 -2.245 1672.0 -1.368 -0.092 0.399
q35_03_contact_friendsless_often -0.576 0.610 -0.945 7904.9 -1.771 0.619 1.000
q18_02_soc_mediayes 0.563 0.114 4.915 7584.7 0.338 0.787 0.000
q49_health_limitationspartially_limits 0.461 0.163 2.827 213.7 0.140 0.783 0.087
q03_relationship_typesingle 0.369 0.176 2.100 5278.1 0.025 0.714 0.537
q03_relationship_typewidowed 0.274 0.452 0.606 3131.7 -0.612 1.159 1.000
q38_alcoholyes 0.210 0.116 1.817 6381.4 -0.017 0.437 0.970
q04_childrenno 0.197 0.137 1.435 4759.9 -0.072 0.465 1.000
q40_smokingyes 0.178 0.134 1.334 1870.3 -0.084 0.441 1.000
q03_relationship_typerelationship -0.166 0.150 -1.107 5479.9 -0.460 0.128 1.000
q11_educationlow 0.157 0.174 0.905 108.1 -0.187 0.502 1.000
q11_educationmedium -0.157 0.156 -1.005 38.7 -0.474 0.159 1.000
q34_02_face_maskno 0.124 0.122 1.017 5209.9 -0.115 0.362 1.000
q02_age -0.091 0.005 -18.659 5383.3 -0.101 -0.082 0.000
q35_01_contact_close_familyless_often -0.082 0.182 -0.452 1536.6 -0.440 0.275 1.000
q42_sportno -0.044 0.114 -0.382 1059.5 -0.268 0.181 1.000
q48_chronic_illnessyes 0.035 0.139 0.251 1419.8 -0.238 0.307 1.000

2.3 Omnibus ANOVA test

Stepwise BIC Model: ANOVA test
SSQ df1 df2 F value Pr(>F) eta2 partial.eta2
q02_age 9503 1 22089 404.8 0 0.040 0.049
q47_self_reporting_health 25875 4 673 265.0 0 0.109 0.123
q36_econ_worry 10486 2 8171 222.3 0 0.044 0.054
q01_gender 4246 2 4005 89.3 0 0.018 0.022
q18_02_soc_media 1072 1 91553 46.0 0 0.005 0.006
q49_health_limitations 869 2 818 17.6 0 0.004 0.005
q04_children 377 1 103489 16.1 0 0.002 0.002
Residual 184759 NA NA NA NA NA NA
Stepwise AIC Model: ANOVA test
SSQ df1 df2 F value Pr(>F) eta2 partial.eta2
q02_age 9503.34 1 18588 408.006 0.000 0.040 0.049
q47_self_reporting_health 25874.63 4 604 266.660 0.000 0.109 0.124
q36_econ_worry 10486.26 2 6967 223.990 0.000 0.044 0.054
q01_gender 4246.21 2 3533 89.943 0.000 0.018 0.023
q18_02_soc_media 1071.97 1 82074 46.374 0.000 0.005 0.006
q20_public_info 1143.97 1 217 42.881 0.000 0.005 0.006
q49_health_limitations 868.79 2 785 17.745 0.000 0.004 0.005
q04_children 376.57 1 99272 16.295 0.000 0.002 0.002
q03_relationship_type 589.98 4 2198 6.204 0.000 0.002 0.003
q38_alcohol 128.50 1 95452 5.553 0.018 0.001 0.001
q40_smoking 24.16 1 2709 0.954 0.329 0.000 0.000
q34_02_face_mask 12.64 1 5292 0.494 0.482 0.000 0.000
q48_chronic_illness 1.86 1 2205 0.014 0.907 0.000 0.000
Residual 182858.38 NA NA NA NA NA NA
Theory-derived Model 1: ANOVA test
SSQ df1 df2 F value Pr(>F) eta2 partial.eta2
q02_age 9503.3 1 45006.4 338.97 0.000 0.040 0.041
q01_gender 4246.2 2 6408.9 74.87 0.000 0.018 0.019
q03_relationship_type 1357.1 4 12247.6 12.05 0.000 0.006 0.006
q11_education 405.7 2 37.4 4.96 0.012 0.002 0.002
q04_children 68.5 1 79553.6 2.44 0.118 0.000 0.000
Residual 221606.4 NA NA NA NA NA NA
Theory-derived Model 2: ANOVA test
SSQ df1 df2 F value Pr(>F) eta2 partial.eta2
q02_age 9503.3 1 32039.5 359.642 0.000 0.040 0.044
q36_econ_worry 8744.3 2 5605.8 163.676 0.000 0.037 0.040
q20_public_info 3052.3 1 82.7 90.791 0.000 0.013 0.014
q01_gender 4246.2 2 5015.8 79.359 0.000 0.018 0.020
q18_02_soc_media 1320.2 1 310479.1 50.343 0.000 0.006 0.006
q03_relationship_type 1357.1 4 10390.1 12.798 0.000 0.006 0.006
q11_education 405.7 2 34.1 5.185 0.011 0.002 0.002
q34_07_hand_washing 127.1 1 5381.5 4.693 0.030 0.001 0.001
q04_children 68.5 1 69446.8 2.589 0.108 0.000 0.000
q34_02_face_mask 20.7 1 24915.7 0.762 0.383 0.000 0.000
Residual 208341.7 NA NA NA NA NA NA
Theory-derived Model 3: ANOVA test
SSQ df1 df2 F value Pr(>F) eta2 partial.eta2
q02_age 9503.34 1 33083.1 362.774 0.000 0.040 0.044
q36_econ_worry 8744.33 2 5254.8 164.950 0.000 0.037 0.041
q20_public_info 3052.33 1 82.5 91.536 0.000 0.013 0.015
q01_gender 4246.21 2 5220.0 80.073 0.000 0.018 0.020
q18_02_soc_media 1320.21 1 293131.9 50.767 0.000 0.006 0.006
q35_01_contact_close_family 1289.09 2 3340.6 24.138 0.000 0.005 0.006
q42_sport 381.22 1 1278.0 13.810 0.000 0.002 0.002
q03_relationship_type 1357.12 4 10274.1 12.906 0.000 0.006 0.007
q40_smoking 153.29 1 2735.9 5.634 0.018 0.001 0.001
q11_education 405.70 2 33.7 5.220 0.011 0.002 0.002
q34_07_hand_washing 127.14 1 5271.2 4.731 0.030 0.001 0.001
q04_children 68.47 1 69066.8 2.611 0.106 0.000 0.000
q35_03_contact_friends 118.51 2 1852.4 2.145 0.117 0.000 0.001
q34_02_face_mask 20.67 1 24398.6 0.768 0.381 0.000 0.000
q38_alcohol 0.45 1 122256.2 0.009 0.926 0.000 0.000
Residual 206399.15 NA NA NA NA NA NA
Theory-derived Model 4: ANOVA test
SSQ df1 df2 F value Pr(>F) eta2 partial.eta2
q02_age 9503.34 1 19079.2 410.962 0.000 0.040 0.050
q47_self_reporting_health 24247.04 4 1293.9 256.189 0.000 0.102 0.118
q36_econ_worry 8744.33 2 4604.9 187.230 0.000 0.037 0.046
q20_public_info 3052.33 1 66.0 100.597 0.000 0.013 0.017
q01_gender 4246.21 2 3783.7 90.664 0.000 0.018 0.023
q18_02_soc_media 1320.21 1 211780.2 57.676 0.000 0.006 0.007
q35_01_contact_close_family 1289.09 2 2545.1 27.325 0.000 0.005 0.007
q42_sport 381.22 1 1013.5 15.585 0.000 0.002 0.002
q03_relationship_type 1357.12 4 6950.9 14.629 0.000 0.006 0.007
q49_health_limitations 679.95 2 323.0 13.435 0.000 0.003 0.004
q40_smoking 153.29 1 2164.7 6.373 0.012 0.001 0.001
q11_education 405.70 2 28.1 5.713 0.008 0.002 0.002
q34_07_hand_washing 127.14 1 4039.7 5.357 0.021 0.001 0.001
q48_chronic_illness 76.45 1 95853.1 3.323 0.068 0.000 0.000
q04_children 68.47 1 54036.4 2.966 0.085 0.000 0.000
q35_03_contact_friends 118.51 2 1466.8 2.426 0.089 0.000 0.001
q34_02_face_mask 20.67 1 18810.9 0.872 0.350 0.000 0.000
q38_alcohol 0.45 1 95005.8 0.010 0.921 0.000 0.000
Residual 181395.71 NA NA NA NA NA NA
---
title: "Predictors of Depression During the Covid-19 Pandemic" 
subtitle: "Multiple Regression"
author: "Sarka Tesarova, Ondrej Pekacek, Alessandro Porrovecchio"
date: "Last edited `r format (Sys.time(),'%d. %m. %Y')`"
output:
  html_document: 
    toc: yes
    toc_depth: 2
    toc_float: true
    number_sections: true
    theme: readable
    code_folding: hide
    code_download: true
    includes:
      in_header: docs/header.html
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```

```{r loading packages and dataset, message=FALSE, include=FALSE}
# The following packages might need to be installed onto your version 
# of R prior to the running of the code below.

# Package names
packages <- c("corrplot", "dplyr", "mice", "car", "miceadds", "kableExtra")

# Install packages not yet installed
installed_packages <- packages %in% rownames(installed.packages())
if (any(installed_packages == FALSE)) {
  install.packages(packages[!installed_packages])
}

# Packages loading
invisible(lapply(packages, library, character.only = TRUE))

imputed_df <- readRDS("data/imputed_dataset.rds")
imputed_df_corr <- readRDS("data/imputed_dataset_corr.rds")

# We also try to limit the decimals to three significant figures
options(digits = 3, scipen = 999)

```

# Correlation plot (Spearman, multiply imputed dataset)

```{r echo=FALSE, fig.height=9, fig.width=9}
mi_corr <- micombine.cor(imputed_df_corr, 
              method = "spearman", 
              conf.level = 0.95)

# Add significance matrix
corrplot(attr(mi_corr,"r_matrix"), 
         method = "circle", 
             type = "lower", 
             # p.mat = res1$p, 
             # sig.level = .05, 
             mar = c(0,0,1,0))

```


# Regression models (multiply imputed dataset) {.tabset .tabset-pills}

```{r include=FALSE}
# outcome <- "PHQ8"
# predictors <- c("q01_gender", "q02_age", "q04_children", "q36_econ_worry", "q18_02_soc_media", "q47_self_reporting_health", "q49_health_limitations")
# 
# formula_bic <- as.formula(
#   paste(outcome,
#     paste(predictors, collapse = " + "),
#     sep = " ~ "
#   )
# )

# test_lm <- lm(formula_bic, mice::complete(imputed_df))
# test <- imputed_df %>% 
#    mice::complete("all") %>%
#   lapply(lm, formula = PHQ8 ~ q01_gender + q02_age + q04_children + q36_econ_worry + 
#     q18_02_soc_media + q47_self_reporting_health + q49_health_limitations) %>%
#   lapply(Anova) 
# car::durbinWatsonTest(stepwise_BIC_fit)
# car::vif(test_lm)
# car::Anova(test_lm, p.adjust.method = TRUE)
# 

# test_jmv <- jmv::linReg(
#     data = data_subset,
#     dep = "PHQ8",
#     covs = "q02_age",
#     factors = vars("q01_gender"),
#      blocks = list(
#         list(
#             "q01_gender",
#             "q02_age")),
#     refLevels = list(
#         list(
#             var = "q01_gender",
#             ref = "female")),
#     r2Adj = TRUE,
#     aic = TRUE,
#     bic = TRUE,
#     rmse = TRUE,
#     modelTest = TRUE,
#     anova = TRUE,
#     ci = TRUE,
#     stdEst = TRUE,
#     ciStdEst = TRUE,
#     durbin = TRUE,
#     collin = TRUE)

# Testing model chosen based by stepwise algorithm on its BIC score
stepwise_BIC_fit <- with(imputed_df, lm(PHQ8 ~ q01_gender +
  q02_age +
  q04_children +
  q36_econ_worry +
  q18_02_soc_media +
  q47_self_reporting_health +
  q49_health_limitations)) %>%
  pool()

stepwise_BIC_anova <- mi.anova(imputed_df, "PHQ8 ~ q01_gender +
  q02_age +
  q04_children +
  q36_econ_worry +
  q18_02_soc_media +
  q47_self_reporting_health +
  q49_health_limitations")

# Testing model chosen based by stepwise algoritm on its AIC score
stepwise_AIC_fit <- with(imputed_df, lm(PHQ8 ~ q01_gender +
  q02_age +
  q04_children +
  q36_econ_worry +
  q18_02_soc_media +
  q47_self_reporting_health +
  q49_health_limitations +
  q03_relationship_type +
  q20_public_info +
  q34_02_face_mask +
  q38_alcohol +
  q40_smoking +
  q48_chronic_illness)) %>%
  pool()

stepwise_AIC_anova <- mi.anova(imputed_df, "PHQ8 ~ q01_gender +
  q02_age +
  q04_children +
  q36_econ_worry +
  q18_02_soc_media +
  q47_self_reporting_health +
  q49_health_limitations +
  q03_relationship_type +
  q20_public_info +
  q34_02_face_mask +
  q38_alcohol +
  q40_smoking +
  q48_chronic_illness")


BIC_summ <- summary(stepwise_BIC_fit, conf.int = TRUE) %>%
  mutate(p.adjusted = round(p.adjust(p.value, method = "holm"), 3)) %>%
  select(-p.value) %>% 
  arrange(desc(abs(estimate)))

AIC_summ <- summary(stepwise_AIC_fit, conf.int = TRUE) %>%
  mutate(p.adjusted = round(p.adjust(p.value, method = "holm"), 3)) %>%
  select(-p.value) %>% 
  arrange(desc(abs(estimate)))

BIC_summ_anv <- stepwise_BIC_anova$anova.table %>% arrange(desc(`F value`))
AIC_summ_anv <- stepwise_AIC_anova$anova.table %>% arrange(desc(`F value`))


```

```{r include=FALSE}
th_1_fit <- with(imputed_df, lm(PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education)) %>%
  pool()

th_2_fit <- with(imputed_df, lm(PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education +
  q18_02_soc_media +
  q20_public_info +
  q34_02_face_mask +
  q34_07_hand_washing +
  q36_econ_worry)) %>%
  pool()

th_3_fit <- with(imputed_df, lm(PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education +
  q18_02_soc_media +
  q20_public_info +
  q34_02_face_mask +
  q34_07_hand_washing +
  q36_econ_worry +
  q40_smoking +
  q42_sport +
  q38_alcohol +
  q35_01_contact_close_family +
  q35_03_contact_friends)) %>%
  pool()

th_4_fit <- with(imputed_df, lm(PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education +
  q18_02_soc_media +
  q20_public_info +
  q34_02_face_mask +
  q34_07_hand_washing +
  q36_econ_worry +
  q40_smoking +
  q42_sport +
  q38_alcohol +
  q35_01_contact_close_family +
  q35_03_contact_friends + 
  q47_self_reporting_health +
  q48_chronic_illness +
  q49_health_limitations)) %>%
  pool()

th_1_anv <- mi.anova(imputed_df, "PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education")

th_2_anv <- mi.anova(imputed_df, "PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education +
  q18_02_soc_media +
  q20_public_info +
  q34_02_face_mask +
  q34_07_hand_washing +
  q36_econ_worry")

th_3_anv <- mi.anova(imputed_df, "PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education +
  q18_02_soc_media +
  q20_public_info +
  q34_02_face_mask +
  q34_07_hand_washing +
  q36_econ_worry +
  q40_smoking +
  q42_sport +
  q38_alcohol +
  q35_01_contact_close_family +
  q35_03_contact_friends")

th_4_anv <- mi.anova(imputed_df, "PHQ8 ~ q01_gender +
  q02_age +
  q03_relationship_type +  
  q04_children +
  q11_education +
  q18_02_soc_media +
  q20_public_info +
  q34_02_face_mask +
  q34_07_hand_washing +
  q36_econ_worry +
  q40_smoking +
  q42_sport +
  q38_alcohol +
  q35_01_contact_close_family +
  q35_03_contact_friends + 
  q47_self_reporting_health +
  q48_chronic_illness +
  q49_health_limitations")

th_1_summ <- summary(th_1_fit, conf.int = TRUE) %>%
  mutate(p.adjusted = round(p.adjust(p.value, method = "holm"), 3)) %>%
  select(-p.value) %>% 
  arrange(desc(abs(estimate)))

th_2_summ <- summary(th_2_fit, conf.int = TRUE) %>%
  mutate(p.adjusted = round(p.adjust(p.value, method = "holm"), 3)) %>%
  select(-p.value) %>% 
  arrange(desc(abs(estimate)))

th_3_summ <- summary(th_3_fit, conf.int = TRUE) %>%
  mutate(p.adjusted = round(p.adjust(p.value, method = "holm"), 3)) %>%
  select(-p.value) %>% 
  arrange(desc(abs(estimate)))

th_4_summ <- summary(th_4_fit, conf.int = TRUE) %>%
  mutate(p.adjusted = round(p.adjust(p.value, method = "holm"), 3)) %>%
  select(-p.value) %>% 
  arrange(desc(abs(estimate)))

th_1_summ_anv <- th_1_anv$anova.table %>% arrange(desc(`F value`))
th_2_summ_anv <- th_2_anv$anova.table %>% arrange(desc(`F value`))
th_3_summ_anv <- th_3_anv$anova.table %>% arrange(desc(`F value`))
th_4_summ_anv <- th_4_anv$anova.table %>% arrange(desc(`F value`))

```

## Model fit measures

```{r} 
kbl(pool.r.squared(stepwise_BIC_fit), caption = "Stepwise BIC Model: Fit Measures") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped"))

kbl(pool.r.squared(stepwise_AIC_fit), caption = "Stepwise AIC Model: Fit Measures") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped"))

kbl(pool.r.squared(th_1_fit), caption = "Theory-derived Model 1: Fit Measures") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped"))

kbl(pool.r.squared(th_2_fit), caption = "Theory-derived Model 2: Fit Measures") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped"))

kbl(pool.r.squared(th_3_fit), caption = "Theory-derived Model 3: Fit Measures") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped"))

kbl(pool.r.squared(th_4_fit), caption = "Theory-derived Model 4: Fit Measures") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped"))

```

## Model coefficients

```{r}
kbl(BIC_summ, caption = "Stepwise BIC Model: Coefficients") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(BIC_summ$p.adjusted < 0.05), bold = TRUE)

kbl(AIC_summ, caption = "Stepwise AIC Model: Coefficients") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(AIC_summ$p.adjusted < 0.05), bold = TRUE)

kbl(th_1_summ, caption = "Theory-derived Model 1: Coefficients") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_1_summ$p.adjusted < 0.05), bold = TRUE)

kbl(th_2_summ, caption = "Theory-derived Model 2: Coefficients") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_2_summ$p.adjusted < 0.05), bold = TRUE)

kbl(th_3_summ, caption = "Theory-derived Model 3: Coefficients") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_3_summ$p.adjusted < 0.05), bold = TRUE)

kbl(th_4_summ, caption = "Theory-derived Model 4: Coefficients") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_4_summ$p.adjusted < 0.05), bold = TRUE)

```

## Omnibus ANOVA test

```{r}
kbl(BIC_summ_anv, caption = "Stepwise BIC Model: ANOVA test") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(BIC_summ_anv$`Pr(>F)` < 0.05), bold = TRUE)

kbl(AIC_summ_anv, caption = "Stepwise AIC Model: ANOVA test") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(AIC_summ_anv$`Pr(>F)` < 0.05), bold = TRUE)

kbl(th_1_summ_anv, caption = "Theory-derived Model 1: ANOVA test") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_1_summ_anv$`Pr(>F)` < 0.05), bold = TRUE)

kbl(th_2_summ_anv, caption = "Theory-derived Model 2: ANOVA test") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_2_summ_anv$`Pr(>F)` < 0.05), bold = TRUE)

kbl(th_3_summ_anv, caption = "Theory-derived Model 3: ANOVA test") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_3_summ_anv$`Pr(>F)` < 0.05), bold = TRUE)

kbl(th_4_summ_anv, caption = "Theory-derived Model 4: ANOVA test") %>%
kable_classic(full_width = FALSE, lightable_options = c("striped")) %>%
                    row_spec(row = which(th_4_summ_anv$`Pr(>F)` < 0.05), bold = TRUE)

```


```{r eval=FALSE, include=FALSE}
# ggplot(complete(imputed_df), aes(q02_age, PHQ8, color = q11_education)) + geom_point(position = "jitter", alpha = 0.2) + geom_smooth()
# 
# # + geom_parallel_slopes(se = TRUE)
```

