**Sample Size Logistic Regression**. One concerns statistical power and the . This program computes power, sample size, or minimum detectable odds ratio (or) for logistic regression with a single binary covariate or two covariates and .

In fact, it is not a specific number to indicate which is the least or even the highest. This program computes power, sample size, or minimum detectable odds ratio (or) for logistic regression with a single binary covariate or two covariates and . In conclusion, for observational studies that involve logistic regression in the analysis, this study recommends a minimum sample size of 500 to .

Binary logistic regression finds plenteous usage throughout many scientific disciplines.

There is no minimum sample size. One concerns statistical power and the . Long (1997) suggests that sample sizes of less than 100 should be avoided and that 500 observations should be adequate for almost any situation. There are two issues that researchers should be concerned with when considering sample size for a logistic regression.