(+) Likelihood ratio = sensitivity / 1-‐specificity = likelihood of having the disease given a positive result. This is different from PPV in that PPV is prevalence dependent.
(-‐) Likelihood ratio = 1-‐sensitivity/specificity = likelihood of not having the disease after a test result comes back negative. NPV, in contrast, is prevalence dependent.
PPV increases with increased specificity. NPV increases with increased sensitivity. Therefore a test with the highest PPV will have the highest specificity. A test with the highest NPV will have the highest sensitivity.
Higher prevalence increases PPV and decreases NPV. Lower prevalence decreases PPV and increases NPV.
Nominal data is dichotomous and only has two categories (e.g., male vs female).
Ordinal data has ranking but no numerical value (e.g., freshman, sophomore, junior, senior).
The median is a better indicator of central tendency (vs mean) in data with a highly skewed distribution.
Hazards Ratio:
Measure of how much effect something actually had.
Value of 1.00 means there is no difference between the two groups.
A ratio < 1 indicates a protective effect, and > 1 indicates a detrimental effect.
If the confidence interval of the hazard ratio includes 1.00 (null value), then the effect wasn’t statistically significant.
If the interval doesn’t include the value, the difference was significant.
