Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘Figure 1. Making statistical inferences about a population from a sample by means of a significance testand confidence intervals.SampleStatistical inference:significance testingconfidence intervalsPopulationrepresenting a theory that has been put forward as a basis for argument [2–4].The hypothesis test is a means to assess the strength of evidence against this nullhypothesis of no difference.The alternative hypothesis, usually written as H a, is that the mean SBP for thestudy population is not equal to the specified value, ie, μ≠μ 0. Note that under thealternative hypothesis, the 2005 population mean could be higher or lower thanthe reference mean. The statistical test for the above hypotheses is usuallyreferred to as a two-sided test.Step 2: Choose an appropriate statistical method and calculatea test statisticOnce the null hypothesis has been chosen we need to calculate the probabilitythat, if the null hypothesis is true, the observed data (or data that were moreextreme) could have been obtained [2,3]. To reach this probability, we need tocalculate a test statistic from the sample data (eg, X, S, and n for quantitativeoutcomes) using an appropriate statistical method. This test statistic is thencompared to the distribution (eg, the normal distribution) implied by the nullhypothesis to obtain the probability of observing our data or more extreme data.For the SBP data, given the relatively large sample size, we can use the Z-test tocalculate the value of the test statistic Z. The Z-test is expressed by the followingformula [2,3]:Z = X – μ 0S / √n187