install.packages(‘epitools’)

Code

library(epitools)

Data Generation

# create matrix for the Readable Survey
textextract <- c('OCR1', 'OCR2')
outcome <- c('Yes', 'No')
survey <- matrix(c(13, 5, 12, 7), nrow=2, ncol=2, byrow=TRUE)
dimnames(survey) <- list('textextract'=textextract, 'Outcome'=outcome)

#view matrix
survey
##            Outcome
## textextract Yes No
##        OCR1  13  5
##        OCR2  12  7

Odds Ratio

oddsratio(survey)
## $data
##            Outcome
## textextract Yes No Total
##       OCR1   13  5    18
##       OCR2   12  7    19
##       Total  25 12    37
## 
## $measure
##            odds ratio with 95% C.I.
## textextract estimate     lower    upper
##        OCR1 1.000000        NA       NA
##        OCR2 1.490704 0.3633389 6.501572
## 
## $p.value
##            two-sided
## textextract midp.exact fisher.exact chi.square
##        OCR1         NA           NA         NA
##        OCR2  0.5809157    0.7281063  0.5560672
## 
## $correction
## [1] FALSE
## 
## attr(,"method")
## [1] "median-unbiased estimate & mid-p exact CI"

Risk Ratio

riskratio.wald(survey)
## $data
##            Outcome
## textextract Yes No Total
##       OCR1   13  5    18
##       OCR2   12  7    19
##       Total  25 12    37
## 
## $measure
##            risk ratio with 95% C.I.
## textextract estimate     lower    upper
##        OCR1 1.000000        NA       NA
##        OCR2 1.326316 0.5132176 3.427618
## 
## $p.value
##            two-sided
## textextract midp.exact fisher.exact chi.square
##        OCR1         NA           NA         NA
##        OCR2  0.5809157    0.7281063  0.5560672
## 
## $correction
## [1] FALSE
## 
## attr(,"method")
## [1] "Unconditional MLE & normal approximation (Wald) CI"

χ2

chisq.test(survey)
## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  survey
## X-squared = 0.056347, df = 1, p-value = 0.8124