Özet:

Objective: In the present study, we aimed to evaluate the effects of sample size on results of study by using frequentist and Bayesian approaches. Material and Methods: The small sample consisted of 32 patients with ischemic heart disease (IHD) and 37 control subjects. In order to compare the statistical differences between small and large sample sizes, two samples were constituted. All the patients included in the study were male and between 40-50 years old. The large sample consisted of 355 IHD patients and 545 controls. Patients’ biochemical variables including glucose, triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), urea, creatinine, hemoglobin, hematocrit, (HCT), red cell distribution width (RDW), White blood cell (WBC), platelet (PLT), mean platelet volume (MPV), neutrophil (NEUT), lymphocyte (LYM) were recorded. Patients in the small and large samples were compared with both frequentist and Bayesian approaches. Results: Except for glucose levels there were no statistical differences with respect to the biochemical variables of two groups in a small sample size when the variables were analyzed by the frequentist approach. Similarly, we did not find any differences between biochemical variables when the data were analyzed by the Bayesian approach. When the large sample size data were analyzed by the frequentist approach, glucose, TG, TC, HDL, LDL, urea, creatinine, hemoglobin, HCT, WBC, NEUT, LYMP levels were found to be statistically significantly different between patients who had IHD and the controls. Similarly, there were significant differences between two groups with respect to glucose, TG, TC, HDL, LDL, urea, creatinine, hemoglobin, HCT, WBC, NEUT, LYMP levels when the data analyzed by Bayesian approach. Conclusion: Our study results suggested that there were no differences between the frequentist and Bayesian approach results when the sample size is large and the power of the study is high.

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