Type I or Alpha error |
It is the probability of rejecting H0, when H0 is false in the
target population. Usually fixed as 5%. |
It is expressed by the p value. It is usually 5% (p<0.05). |
For sample size calculation, the confidence level may be adopted (usually
95%), calculated as 1-Alpha. |
The smaller the Alpha error (greater confidence level), the larger will be
the sample size. |
Statistical Power (1-Beta) |
It is the ability of the test to detect a difference in the
sample, when it exists in the target population. |
Calculated as 1-Beta. |
The greater the power, the larger the required
sample size will be. |
A value between 80%-90% is usually used. |
Relationship between non-exposed/exposed groups in the
sample |
It indicates the existing relationship between non-exposed and
exposed groups in the sample. |
For observational studies, the data are usually obtained from the
scientific literature. In intervention studies, the value 1:1 is frequently
adopted, indicating that half of the individuals will receive the
intervention and the other half will be the control or comparison group.
Some intervention studies may use a larger number of controls than of
individuals receiving the intervention. |
The more distant this ratio is from one, the larger will be the required
sample size. |
Prevalence of outcome in
the non-exposed group
(percentage of positive among the non-exposed) |
Proportion of individuals with the disease (outcome) among those
non-exposed to the risk factor (or that are part of the control group). |
Data usually obtained from the literature. When this information is not
available but there is information on general prevalence/incidence in the
population, this value may be used in sample size calculation (values
attributed to the control group in intervention studies) or estimated based
on the following formula: PONE=pO/(pNE+(pE*PR) ) |
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where pO = prevalence of outcome; pNE = percentage of non-exposed; pE =
percentage of exposed; PR = prevalence ratio (usually a value between 1.5 and 2.0). |
Expected prevalence ratio |
Relationship between the prevalence of disease in the exposed (intervention) group and the
prevalence of disease in
the non-exposed group, indicating how many times it is expected that the
prevalence will be
higher (or lower) in the exposed compared to non-exposed group. |
It is the value that the investigators intend to find as HA,
with the corresponding H0 equal to one (similar prevalence of the outcome in both
exposed and non-exposed groups). For the sample size estimates, the expected
outcome prevalence may be
used for the non-exposed group, or the expected difference in the
prevalence between the
exposed and the non-exposed groups. |
Usually, a value between 1.50 and 2.00 is used
(exposure as risk factor) or between 0.50 and 0.75 (protective factor). |
For intervention studies, the clinical relevance of this value should be
considered. |
The smaller the prevalence rate (the smaller the expected difference
between the groups), the larger the required sample size. |
Type of statistical test |
The test may be one-tailed or two-tailed, depending on the type of the
HA. |
Two-tailed tests require larger sample sizes |