Evidence Based Medicine
Statistics
Regarding the power of a study, which of the following statements is INCORRECT:
Answer:
A study should only be undertaken if the power is at least 80%; a study power set at 80% accepts a likelihood of 1 in 5 (20%) of missing a statistically significant difference where one exists. The determinants of power are:- the sample size (the power increases with sample size)
- the variability of the observations (the power increases as the variability decreases)
- the effect size of interest (the power is greater for a larger expected effect size)
- and the significance level, α (the power is greater if the significance level is larger); therefore the probability of a type I error increases as the probability of a type II error decreases.
Sample Size and Power
Evidence Based Medicine / Statistics
Last Updated: 24th February 2023
The sample size for a study is not chosen at random. Ideally a clinical trial should be large enough to reliably detect the smallest possible difference in the outcome measure, with treatment, that is considered clinically worthwhile.
The power of a study is the probability of correctly rejecting the null hypothesis when it is false. It is the probability that the study would detect a statistically significant difference if a true difference exists. As the power increases, the chance of making a type II error decreases.
The power of a study = 1 - β. Typically β is arbitrarily set at 0.2, meaning that a study has 80% power (0.8 of a chance) to detect a specified degree of difference at a specified degree of significance.
A power of 0.8 is generally accepted as being adequate in most research studies: a study power set at 80% accepts a likelihood of 1 in 5 (20%) of missing a statistically significant difference where one exists.
The determinants of power are:
- the sample size (the power increases with sample size)
- the variability of the observations (the power increases as the variability decreases)
- the effect size of interest (the power is greater for a larger expected effect size)
- and the significance level, α (the power is greater if the significance level is larger); therefore the probability of a type I error increases as the probability of a type II error decreases.
Inspection of the confidence intervals for the effect of interest gives an indication of whether the power of the test was adequate; a wide confidence interval suggests low power. The most common reason for type II error is that the study is too small.
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- Biochemistry
- Blood Gases
- Haematology
| Biochemistry | Normal Value |
|---|---|
| Sodium | 135 – 145 mmol/l |
| Potassium | 3.0 – 4.5 mmol/l |
| Urea | 2.5 – 7.5 mmol/l |
| Glucose | 3.5 – 5.0 mmol/l |
| Creatinine | 35 – 135 μmol/l |
| Alanine Aminotransferase (ALT) | 5 – 35 U/l |
| Gamma-glutamyl Transferase (GGT) | < 65 U/l |
| Alkaline Phosphatase (ALP) | 30 – 135 U/l |
| Aspartate Aminotransferase (AST) | < 40 U/l |
| Total Protein | 60 – 80 g/l |
| Albumin | 35 – 50 g/l |
| Globulin | 2.4 – 3.5 g/dl |
| Amylase | < 70 U/l |
| Total Bilirubin | 3 – 17 μmol/l |
| Calcium | 2.1 – 2.5 mmol/l |
| Chloride | 95 – 105 mmol/l |
| Phosphate | 0.8 – 1.4 mmol/l |
| Haematology | Normal Value |
|---|---|
| Haemoglobin | 11.5 – 16.6 g/dl |
| White Blood Cells | 4.0 – 11.0 x 109/l |
| Platelets | 150 – 450 x 109/l |
| MCV | 80 – 96 fl |
| MCHC | 32 – 36 g/dl |
| Neutrophils | 2.0 – 7.5 x 109/l |
| Lymphocytes | 1.5 – 4.0 x 109/l |
| Monocytes | 0.3 – 1.0 x 109/l |
| Eosinophils | 0.1 – 0.5 x 109/l |
| Basophils | < 0.2 x 109/l |
| Reticulocytes | < 2% |
| Haematocrit | 0.35 – 0.49 |
| Red Cell Distribution Width | 11 – 15% |
| Blood Gases | Normal Value |
|---|---|
| pH | 7.35 – 7.45 |
| pO2 | 11 – 14 kPa |
| pCO2 | 4.5 – 6.0 kPa |
| Base Excess | -2 – +2 mmol/l |
| Bicarbonate | 24 – 30 mmol/l |
| Lactate | < 2 mmol/l |
