Random Error

P-values and Confidence Intervals

Role of P-values and Confidence Intervals within Epidemiologic Research Confidence intervals (CI ) and p-values are two different approaches in determining whether the result of an experiment is statistically significant or not . CI , which is sometimes called the acceptance region provides a statistical range with a specified probability that a given estimator lies within the range (Gujarati , 2003 . P-value , on the other hand , is defined as the lowest significance level at which a null hypothesis can be rejected

Part I

CI is very useful in epidemiological research

, both in study design and result interpretation (Macfarlane Silman , 2002 . Clinical experiments with small sample size tend to yield results with high statistical variability which the CI can easily express . Aside from setting sample sizes , CIs are also considered informative data summaries ' which can complement or even replace the role of p-values in reporting statistical results . Given the sample size and observed effect , it can isolate which results are statistically compatible with the data from those that are not . Moreover , CIs can put light to vague results of studies which try to rule out differences saying that these are function of the design not the results (McNeil , 1996 . CIs can distinguish between the differences that are statistically discarded based on what was actually observed and those that are not

P-value aids researcher in measuring the evidence against the null hypothesis or the hypothesis of no change or no effect (Gujarati , 2003 Instead of preselecting an arbitrary significance level , such as...