This is known as Type II error that detects false negative results, exactly opposite to mentioned above where we find false positive results when actually there was no difference. Sometimes we may commit another type of error where we may fail to detect the difference when actually there is the difference. Every individual in the chosen population should have an equal chance to be included in the sample. The sample size is, simply put, the number of patients or experimental units in a sample. Hence, the sample is a set of participants (lesser in number) which adequately represents the population from which it is drawn so that true inferences about the population can be made from the results obtained.
#Statistical calculations for trials trial#
Hence in this article, we will discuss the importance of sample size estimation for a clinical trial and different parameters that impact sample size along with basic rules for these parameters.Īs we know, it is naturally neither practical nor feasible to study the whole population in any study. One of the pivotal aspects of planning a clinical study is the calculation of the sample size.
Understanding the basic concepts will help the anesthesiologist to interact with him in a more meaningful way.
While designing a study, we need to interact with a statistician. To plan a research project and to understand the contents of a research paper, we need to be familiar with the fundamental concepts of medical statistics. Complex appearance of mathematical expression which are used for this.
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