The column 1 relative risk is the ratio of the column 1 risk for row 1 to row 2. See Stokes, Davis, and Koch (2000) and Agresti (2007) for more information. Relative risk measures are also useful in cross-sectional studies, where two variables are observed simultaneously. The two samples are observed in future time for the binary (yes-no) response variable under study. These measures of relative risk are useful in cohort (prospective) study designs, where two samples are identified based on the presence or absence of an explanatory factor. If any of the four cell frequencies are zero, the estimates are not computed. The asymptotic % confidence limits for the odds ratio areĪnd is the th percentile of the standard normal distribution. is the gamma statistic, which PROC FREQ computes when you specify the MEASURES option. The transformation transforms the odds ratio to the range with when when and approaches 1 as approaches infinity. The strength of association increases with the deviation from 1. Values less than 1 indicate the odds of positive response are higher in row 2. An odds ratio greater than 1 indicates that the odds of a positive response are higher in row 1 than in row 2. When the row and column variables are independent, the true value of the odds ratio equals 1. The odds ratio can be any nonnegative number.
The odds ratio is formed as the ratio of the row 1 odds to the row 2 odds. Similarly, the odds of a positive response in row 2 is. The odds of a positive response (column 1) in row 1 is. See Stokes, Davis, and Koch (2000) and Agresti (2007). In a case-control study, two independent samples are identified based on a binary (yes-no) response variable, and the conditional distribution of a binary explanatory variable is examined, within fixed levels of the response variable. For a retrospective design called a case-control study, the odds ratio can be used to estimate the relative risk when the probability of positive response is small (Agresti 2002). The odds ratio is a useful measure of association for a variety of study designs.
0 kommentar(er)
