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Statistical Models and the Theory of Hypothesis Testing in Medicine

Gazaryan V.A., Guryanova I.E. and Melekhina T.L.

International Journal of Economics & Business Administration (IJEBA), 2019, vol. VII, issue Special 2, 334-342

Abstract: Purpose: The purpose of this work is to develop statistical approaches for treatment efficiency analysis on a medical case. These methods include the effect evaluation method performed with various preparations in regards to several factors such as the patient‘s blood state and his/her biochemical values. Design/Methodology/Approach: The results of this survey were divided into three groups: the first included the blood biochemistry values before the test, the second — an hour after the test, the the third — two hours after the test. When visually comparing the results of the analyses of the three groups, it was possible to assume that the load of FLC did not significantly affect the biochemistry of the patients' blood. To test this medical assumption, various statistical criteria of the theory of testing statistical hypotheses have been applied. Findings: Statistical analysis of changes in the level of lipase and triglycerides in the biochemical analysis of the blood of patients with chronic pancreatitis after ingestion of food containing medium-chain fatty acids showed that there is no overall disruption in the functioning of the pancreas. Practical implications: Clinical practice has shown that more than 85% of patients tolerated testing with medium chain fatty acids, not experiencing a painful abdominal symptom and other negative consequences of a violation of external secretion of the pancreas. Originality/Value: In clinical practice, the Russian Academy of Medical Sciences for the first time took into account the results of a statistical analysis.

Keywords: Mathematical statistics; theory of statistical hypothesis testing; statistical criterion. (search for similar items in EconPapers)
JEL-codes: C12 C15 I10 I12 (search for similar items in EconPapers)
Date: 2019
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Handle: RePEc:ers:ijebaa:v:vii:y:2019:i:special2:p:334-342