library(tidyverse)
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library(readxl)
load("NSDUH_2023.Rdata")
model1<-lm(CABINGFLG~IRMARIT,data=data)
summary(model1)
## 
## Call:
## lm(formula = CABINGFLG ~ IRMARIT, data = data)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -0.602 -0.597 -0.585 -0.044 84.956 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.6079489  0.0236906  25.662  < 2e-16 ***
## IRMARIT     -0.0056991  0.0007594  -7.505 6.22e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5.188 on 56703 degrees of freedom
## Multiple R-squared:  0.0009924,  Adjusted R-squared:  0.0009748 
## F-statistic: 56.33 on 1 and 56703 DF,  p-value: 6.225e-14

The model explains that there is significance between marital status and binge alcohol use. Marital status shows a significant relationship to binge alcohol use. I did not have another independent vairable to test.

model1<-lm(CABINGFLG~IRMARIT+SEXIDENT22+CATAGE,data=data)
summary(model1)
## 
## Call:
## lm(formula = CABINGFLG ~ IRMARIT + SEXIDENT22 + CATAGE, data = data)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -0.807 -0.647 -0.525 -0.042 84.958 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  0.4238792  0.0692232   6.123 9.22e-10 ***
## IRMARIT     -0.0044706  0.0008849  -5.052 4.38e-07 ***
## SEXIDENT22   0.0015625  0.0012176   1.283  0.19938    
## CATAGE       0.0586616  0.0215631   2.720  0.00652 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5.188 on 56701 degrees of freedom
## Multiple R-squared:  0.001153,   Adjusted R-squared:  0.0011 
## F-statistic: 21.81 on 3 and 56701 DF,  p-value: 4.144e-14

It shows that marital status and age have a significant relationship to binge alcohol use but not with sexual identity.

plot(model1, which=1)

The model meets linearity by visual inspection.