Parameter Estimation and Determination of Sample Size in Logistic Regression

Abstract

The determination of Sample-Size is often an important step in planning a statistical study and it is usually a difficult task. Among the important hurdles to be surpassed, one must obtain an estimate of one or more error variances and specify an effective sample size of importance. The study was carried out to check for the estimation of parameter and sample sizes in logistic regression, although, there is the temptation to take some shortcuts. We to looked at two methods of obtaining sample sizes having obtain the parameter estimates by varying the response probability. The results from the real life data showed that when the response probabilities are small, an approximation of corrected term Equation 12 performs better than the approximation Equation 8, but it highly over estimates when the response probabilities are large.