Development↦Statistic Methodology↦Sample Size↦Justification
Was betrifft es? Warum ist das wichtig?
When planning a study, it is important to justify the defined sample size of the study (i.e. number of participants included in the study).
The sample size will have a direct effect on the precision and accuracy of study results, including the ability to detect a real effect.
Was muss ich befolgen?
As a SP-INV, based on the aim of your study explain how the sample size and its subsequent collected data are expected to provide valuable scientific information.
Aspects to consider include:
- The outcome/endpoint of your study (e.g. cholesterol concentration)
- The method you use for the sample size estimation
- The statistical framework, which can either be:
- Hypothesis testing (e.g. you want to test the difference in cholesterol concentration between two patient groups). Define the null and alternative hypothesis
- Precision-based (e.g. you want to estimate the mean in cholesterol concentration of a certain group of patients). Define the type I error and power
- The assumption/previous knowledge which were used as a basis for the sample size calculation (e.g. we expect a mean value of 5.2 mmol/L and a standard deviation of 1.5)
Wo kann ich Hilfe anfordern?
Your local Research Support Centre↧ can assist you with experienced staff regarding this topic
Basel, Departement Klinische Forschung (DKF), dkf.unibas.ch
Lugano, Clinical Trials Unit (CTU-EOC), ctueoc.ch
Bern, Department of Clinical Research (DCR), dcr.unibe.ch
Geneva, Clinical Research Center (CRC), crc.hug.ch
Lausanne, Clinical Research Center (CRC), chuv.ch
St. Gallen, Clinical Trials Unit (CTU), h-och.ch
Zürich, Clinical Trials Center (CTC), usz.ch
References
ICH Topic E9 – see in particular
- 3.5 Sample Size