Chi-Square and T-tests for demographic variables and IPV status after matching for Age at baseline and Years of education

Chi-square for IPVstatus and Sex

tbl = table(output_Abusew01Neupsyw03Neupsy$IPVstatus, output_Abusew01Neupsyw03Neupsy$Sex)
tbl
##    
##     Women Men
##   0    22  20
##   1    12   9
chisq.test(tbl)
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tbl
## X-squared = 0.008, df = 1, p-value = 0.9288

Chi-square for IPVstatus and Race

tbl2 = table(output_Abusew01Neupsyw03Neupsy$IPVstatus, output_Abusew01Neupsyw03Neupsy$Race)
tbl2
##    
##     White AfrAm
##   0    15    27
##   1     8    13
chisq.test(tbl2)
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tbl2
## X-squared = 0, df = 1, p-value = 1

Chi-square for Race and Sex

tbl3 = table(output_Abusew01Neupsyw03Neupsy$Sex, output_Abusew01Neupsyw03Neupsy$Race)
tbl3
##        
##         White AfrAm
##   Women    12    22
##   Men      11    18
chisq.test(tbl3)
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  tbl3
## X-squared = 0, df = 1, p-value = 1

t-test for IPVgroup and Age

y = output_Abusew01Neupsyw03Neupsy$Age1
x = output_Abusew01Neupsyw03Neupsy$IPVstatus
t.test(y ~ x)
## 
##  Welch Two Sample t-test
## 
## data:  y by x
## t = -0.4857, df = 46.67, p-value = 0.6294
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -4.286  2.619
## sample estimates:
## mean in group 0 mean in group 1 
##           40.12           40.95

t-test for IPVgroup and Years of Education

y = output_Abusew01Neupsyw03Neupsy$Education
x = output_Abusew01Neupsyw03Neupsy$IPVstatus
t.test(y ~ x)
## 
##  Welch Two Sample t-test
## 
## data:  y by x
## t = 0.6654, df = 41.8, p-value = 0.5095
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.210  2.401
## sample estimates:
## mean in group 0 mean in group 1 
##           12.17           11.57