A log-likelihood contingency test with Williams correction was used to examine the association between the binary variables joint condemnations (yes 1/no 0) in the whole pig and gait remark (yes 1/no 0).
Since the lexical decision task required subjects to distinguish between words and pseudowords, the binary variable Lexicality was also investigated using a factorial design.
Logistic regression analysis was conducted to calculate OR and 95% CIs for the association between AUDIT scores and the binary variable of BMD (T-score ≥−1: normal, T-score <−1: low BMD) at TF and FN.
Multiple logistic regressions were used to assess the relationships between two clonal complexes, the binary variables, and explanatory variables: host characteristics and bacterial determinants.
The sensitivity, specificity, positive and negative predictive value, and agreement rate were calculated between the two methods using the binary variables; receiver operating characteristics (ROC) curve were generated to estimate the area under the curve [ 18].
The relationship between the observed binary variable, y, and the unobservable λ is (1) y i = { 0 i f λ i ≤ τ 1 i f λ i > τ where τ is a fixed threshold and y i = 1 and 0 correspond to the presence or absence of mastitis for observation i, respectively.
Because we assumed no interactive effect on the outcome measure between the unobserved binary variable and treatment, the leftmost and rightmost points of the plots on the right side of the Figure are constrained to be equal.
To make progress we assume no interactive effect on probability of outcome between the unobserved binary variable and treatment.
In other words, to fulfill the condition of no interaction between the treatment and the unobserved binary variable, the outcome measure comparing treatment groups, whether DIF, RR or OR, has the same value at the leftmost and rightmost points on the horizontal axis.
