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Year : 2021  |  Volume : 4  |  Issue : 2  |  Page : 71-78

A magical journey into knowledge creation in emergency difficult airway access - Sample size calculation and choosing statistical tests with the ‘Research Genie’

Department of Otolaryngology Head and Neck Surgery, St. John's Medical College and Hospital, Bengaluru, Karnataka, India

Correspondence Address:
Dr. Arumugam Ramesh
Department of Otolaryngology Head and Neck Surgery, St. John's Medical College Hospital, Koramangala, Bengaluru - 560 034, Karnataka
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/arwy.arwy_39_21

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This article is the third of a four-article series intended to ignite the minds of readers and empower them to create new knowledge in the context of 'emergency difficult airway access'. This article describes sample size calculation, descriptive statistics and inferential statistics in simple and lucid language without using any formulae. The reader should have followed the steps of knowledge creation as described in the first two articles and framed objectives for a given challenging healthcare situation. The study design and variables to operationalise the objective should have been defined. With this information in the background, the article empowers the reader to calculate sample size for a given objective. The pathway to access this information on the 'Research Genie (RG)' app is described for every objective in all the nine relevant domains of healthcare, i.e. description, laboratory range estimation, incidence/prevalence estimation, evaluating therapies, measuring costs in healthcare, critically evaluating new tests, measuring risk, correlating variables and describing experiences, perceptions and beliefs. Mathematical and statistical jargon are deliberately kept at bay. This is followed by describing summary measures and tests of significance for each objective. The pathway to access this on RG is described. On reading and assimilating this article, healthcare personnel can communicate meaningfully with the biostatistician while explaining the data required to calculate the sample size for a given objective. The researcher learns to list the possible summary measures and tests of significance for a particular objective. With an intention to demystify all these complicated concepts, I may have erred on the side of oversimplification. I pray for forgiveness from the biostatisticians and sincerely recommend all these are discussed with the biostatistician and approval sought before putting them in print.

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