Evidence Based Medicine
Statistics
Which of the following statistical tests is most appropriate for comparing means between two independent parametric variables:
Answer:
The unpaired student t-test would be most appropriate to compare the means of two independent groups of values.Statistical Tests
Evidence Based Medicine / Statistics
Last Updated: 21st April 2019
Significance tests are mathematical functions which compute an observed value of a test statistic from experimental data. The p value required to determine significance is derived from this test statistic.
The type (categorical or quantitative) and distribution (normal, non-normal) of data, the number of samples, and whether the data is paired or unpaired determines which significance test should be used. In practice, computer programs are used to do these calculations.
Unpaired data refers to data from two groups which have different members. Paired data refers to data from the same individuals taken at different time points.
Parametric and Non-Parametric Tests
Parametric tests are used to compare samples of normally distributed data. Non-parametric testing is used to compare samples of non-normally distributed data.
| Parametric tests (normal data) | Non-parametric tests (non-normal data) |
|---|---|
| Unpaired student t-test: used to compare the means of two independent groups of values | Mann Whitney U-test: used to compare the medians of two unpaired groups of values |
| Paired student t-test: used to compare the means of values obtained from a single group at two different points in time | Wilcoxon matched pairs: used to compare the medians of two paired groups of values |
| One-way Analysis of variance (ANOVA): used to compare the means of more than two unpaired groups of values | Kruskal-Wallis test: used to compare the medians of more than two unpaired groups of values |
| Repeated-measures ANOVA: used to compare the means of more than two paired groups of values | Friedman's test: used to compare the medians of more than two paired groups of values |
Tests for Categorical Data
The chi-squared test is used to compare the proportions of two or more unpaired groups with a particular attribute e.g. the proportion of people suffering a stroke in two groups receiving a statin or no statin to see if they are statistically different. An odds ratio of 1, or whose 95% CI includes the value of 1, implies that there is no difference between the two groups.
For small-sized samples (fewer than five observations in any variable), Fisher's exact test can be used.
The McNemar's test is used to compare proportions of two or more paired groups of values.
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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 |
