## 
## --------Summary descriptives table by 'ZaritBurdenClinicalSignificance'---------
## 
## ______________________________________________________________________ 
##                                           0           1      p.overall 
##                                         N=107       N=149              
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
## EducationGroup:                                                0.882   
##     0                                37 (34.6%)  49 (32.9%)            
##     1                                70 (65.4%)  100 (67.1%)           
## demo_age                             34.4 (13.6) 32.5 (11.8)   0.250   
## demo_gender:                                                   0.739   
##     Female                           79 (73.8%)  106 (71.1%)           
##     Male                             28 (26.2%)  43 (28.9%)            
## covid_affected_anger_bio:                                      0.014   
##     Not Increased                    74 (69.2%)  79 (53.0%)            
##     Increased                        33 (30.8%)  70 (47.0%)            
## covid_affected_anxiety_bio:                                    0.004   
##     Not Increased                    48 (44.9%)  40 (26.8%)            
##     Increased                        59 (55.1%)  109 (73.2%)           
## covid_affected_sense_control_bio:                              0.001   
##     Not Increased                    72 (67.3%)  69 (46.3%)            
##     Decreased                        35 (32.7%)  80 (53.7%)            
## covid_affected_social_isolation_bio:                           0.111   
##     Not Increased                    51 (47.7%)  55 (36.9%)            
##     Increased                        56 (52.3%)  94 (63.1%)            
## covid_affected_stress_bio:                                     0.148   
##     Not Increased                    44 (41.1%)  47 (31.5%)            
##     Increased                        63 (58.9%)  102 (68.5%)           
## covid_affected_use_healthcare_bio:                             0.240   
##     Not Increased                    69 (64.5%)  84 (56.4%)            
##     Decreased                        38 (35.5%)  65 (43.6%)            
## PCS                                  46.1 (9.27) 42.3 (9.08)   0.001   
## MCS                                  40.7 (11.8) 34.0 (10.4)  <0.001   
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## 
## --------Summary descriptives table by 'ZaritBurdenClinicalSignificance'---------
## 
## __________________________________________________________________________________________________________________________________ 
##                                                                                                        0          1      p.overall 
##                                                                                                      N=107      N=149              
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
## household_financial:                                                                                                       0.923   
##     After paying the bills, you still have enough money for special things that you want.          18 (16.8%) 27 (18.1%)           
##     You are having difficulty paying the bills, no matter what you do.                             27 (25.2%) 36 (24.2%)           
##     You have enough money to pay the bills, but little spare money to buy extra or special things. 38 (35.5%) 57 (38.3%)           
##     You have money to pay the bills, but only because you have to cut back on things.              24 (22.4%) 29 (19.5%)           
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯

Crude Model

fit1 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_anger_bio, data= LEEP,   family = binomial(link = "logit"))

fit2 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_anger_bio+EducationGroup+demo_age+household_financial+demo_gender, data= LEEP,   family = binomial(link = "logit"))

tab_model(fit1, fit2)
  ZaritBurdenClinicalSignificance ZaritBurdenClinicalSignificance
Predictors Odds Ratios CI p Odds Ratios CI p
(Intercept) 1.07 0.78 – 1.47 0.686 1.60 0.63 – 4.13 0.328
covid affected anger
bioIncreased 		1.99 1.19 – 3.37 0.010 2.14 1.26 – 3.70 0.006
EducationGroup [1] 1.14 0.65 – 2.00 0.649
demo age 0.99 0.96 – 1.01 0.172
household financial [You
are having difficulty
paying the bills, no
matter what you do ] 		0.79 0.35 – 1.78 0.572
household financial [You
have enough money to pay
the bills, but little
spare money to buy extra
or special things ] 		1.01 0.48 – 2.11 0.977
household financial [You
have money to pay the
bills, but only because
you have to cut back on
things ] 		0.79 0.34 – 1.81 0.580
demo gender [Male] 1.33 0.74 – 2.41 0.339
Observations 256 256
R2 Tjur 0.026 0.041 
fit1 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_anxiety_bio, data= LEEP, family = binomial(link = "logit"))
fit2 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_anxiety_bio+EducationGroup+demo_age+household_financial+demo_gender, data= LEEP,   family = binomial(link = "logit"))
tab_model(fit1, fit2)
  ZaritBurdenClinicalSignificance ZaritBurdenClinicalSignificance
Predictors Odds Ratios CI p Odds Ratios CI p
(Intercept) 0.83 0.55 – 1.27 0.394 1.33 0.51 – 3.51 0.559
covid affected anxiety
bioIncreased 		2.22 1.31 – 3.77 0.003 2.44 1.41 – 4.24 0.001
EducationGroup [1] 1.09 0.62 – 1.92 0.764
demo age 0.99 0.96 – 1.01 0.172
household financial [You
are having difficulty
paying the bills, no
matter what you do ] 		0.76 0.33 – 1.72 0.513
household financial [You
have enough money to pay
the bills, but little
spare money to buy extra
or special things ] 		0.94 0.44 – 1.98 0.872
household financial [You
have money to pay the
bills, but only because
you have to cut back on
things ] 		0.68 0.29 – 1.58 0.369
demo gender [Male] 1.34 0.74 – 2.43 0.336
Observations 256 256
R2 Tjur 0.035 0.050 
fit1 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_sense_control_bio, data= LEEP, family = binomial(link = "logit"))

fit2 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_sense_control_bio+EducationGroup+demo_age+household_financial+demo_gender, data= LEEP,   family = binomial(link = "logit"))
tab_model(fit1, fit2)
  ZaritBurdenClinicalSignificance ZaritBurdenClinicalSignificance
Predictors Odds Ratios CI p Odds Ratios CI p
(Intercept) 0.96 0.69 – 1.33 0.801 1.45 0.57 – 3.77 0.436
covid affected sense
control bioDecreased 		2.39 1.43 – 4.03 0.001 2.50 1.46 – 4.35 0.001
EducationGroup [1] 1.19 0.67 – 2.10 0.550
demo age 0.99 0.97 – 1.01 0.338
household financial [You
are having difficulty
paying the bills, no
matter what you do ] 		0.67 0.29 – 1.54 0.354
household financial [You
have enough money to pay
the bills, but little
spare money to buy extra
or special things ] 		0.77 0.35 – 1.63 0.495
household financial [You
have money to pay the
bills, but only because
you have to cut back on
things ] 		0.78 0.34 – 1.78 0.553
demo gender [Male] 1.18 0.66 – 2.15 0.571
Observations 256 256
R2 Tjur 0.043 0.052 
fit1 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_social_isolation_bio, data= LEEP, family = binomial(link = "logit"))
fit2 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_social_isolation_bio+EducationGroup+demo_age+household_financial+demo_gender, data= LEEP,   family = binomial(link = "logit"))
tab_model(fit1, fit2)
  ZaritBurdenClinicalSignificance ZaritBurdenClinicalSignificance
Predictors Odds Ratios CI p Odds Ratios CI p
(Intercept) 1.08 0.74 – 1.58 0.698 1.64 0.64 – 4.24 0.303
covid affected social
isolation bioIncreased 		1.56 0.94 – 2.58 0.086 1.57 0.94 – 2.62 0.086
EducationGroup [1] 1.14 0.65 – 1.99 0.648
demo age 0.99 0.96 – 1.01 0.164
household financial [You
are having difficulty
paying the bills, no
matter what you do ] 		0.91 0.41 – 2.01 0.808
household financial [You
have enough money to pay
the bills, but little
spare money to buy extra
or special things ] 		0.96 0.46 – 2.00 0.919
household financial [You
have money to pay the
bills, but only because
you have to cut back on
things ] 		0.86 0.38 – 1.95 0.714
demo gender [Male] 1.25 0.70 – 2.25 0.454
Observations 256 256
R2 Tjur 0.012 0.021 
fit1 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_stress_bio, data= LEEP, family = binomial(link = "logit"))
fit2 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_stress_bio+EducationGroup+demo_age+household_financial+demo_gender, data= LEEP,   family = binomial(link = "logit"))
tab_model(fit1, fit2)
  ZaritBurdenClinicalSignificance ZaritBurdenClinicalSignificance
Predictors Odds Ratios CI p Odds Ratios CI p
(Intercept) 1.07 0.71 – 1.62 0.753 1.45 0.54 – 3.94 0.463
covid affected stress
bioIncreased 		1.52 0.90 – 2.55 0.115 1.56 0.91 – 2.68 0.103
EducationGroup [1] 1.17 0.67 – 2.04 0.587
demo age 0.99 0.97 – 1.01 0.248
household financial [You
are having difficulty
paying the bills, no
matter what you do ] 		0.87 0.38 – 1.93 0.727
household financial [You
have enough money to pay
the bills, but little
spare money to buy extra
or special things ] 		1.00 0.47 – 2.07 0.992
household financial [You
have money to pay the
bills, but only because
you have to cut back on
things ] 		0.79 0.35 – 1.81 0.585
demo gender [Male] 1.31 0.73 – 2.36 0.368
Observations 256 256
R2 Tjur 0.010 0.021 
fit1 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_use_healthcare_bio, data= LEEP,family = binomial(link = "logit"))
fit2 <- glm(ZaritBurdenClinicalSignificance ~covid_affected_use_healthcare_bio+EducationGroup+demo_age+household_financial+demo_gender, data= LEEP,   family = binomial(link = "logit"))
tab_model(fit1, fit2)
  ZaritBurdenClinicalSignificance ZaritBurdenClinicalSignificance
Predictors Odds Ratios CI p Odds Ratios CI p
(Intercept) 1.22 0.89 – 1.68 0.226 1.80 0.72 – 4.59 0.213
covid affected use
healthcare bioDecreased 		1.41 0.84 – 2.35 0.192 1.43 0.84 – 2.43 0.188
EducationGroup [1] 1.15 0.66 – 2.01 0.617
demo age 0.99 0.97 – 1.01 0.207
household financial [You
are having difficulty
paying the bills, no
matter what you do ] 		0.84 0.37 – 1.90 0.676
household financial [You
have enough money to pay
the bills, but little
spare money to buy extra
or special things ] 		0.98 0.47 – 2.03 0.956
household financial [You
have money to pay the
bills, but only because
you have to cut back on
things ] 		0.81 0.35 – 1.85 0.618
demo gender [Male] 1.22 0.69 – 2.19 0.502
Observations 256 256
R2 Tjur 0.007 0.017