]> 2026-07-31T12:14:41+00:00 WBR0435 0 en Recruiting more hemodialysis patients to the study Recruiting more patients, who fit the inclusion criteria, can increase the statistical power of the study. Comparing peritoneal dialysis patients to hemodialysis patients Since the study does not involve peritoneal dialysis patients, adding those to the study is not appropriate and will most likely limit the study’s statistical power. Decreasing the p-value cut-off to <0.01 α (type 1 error) represents the likelihood of obtaining a significant difference when there actually is none. The p-value represents the α or type 1 error of a study. As a rule, for the same population size, as α decreases (p-value cut-off becomes more stringent), β increases. As power = (1-β), higher β values lower the power of a study. Therefore decreasing the p-value cut-off to <0.01 will decrease the statistical power of the study. Repeating all measurements of urea reduction rate (URR) for the 90 patients who are recruited Repeating measurements will test the precision of the study’s measurements. Since measurements were described as precise in the first place, the statistical power of the study is likely not to be affected. The statistical power of the study cannot be changed The statistical power of the study can be changed if the sample size is increased. Biostatistics/Epidemiology A researcher conducts a cross-sectional study to identify factors that are associated with hemodialysis adequacy among 90 patients undergoing hemodialysis. Following data collection, statistical analysis reveals that the urea reduction rate (URR) is associated with hemodialysis adequacy with a p-value of 0.12 (significant p-value <0.05). Which of the following modifications will most likely increase the statistical power of the study? A Renal 2020-10-28T00:33:03Z 2459150.5229514 WBR0435