Statistical analysis

A clinical trial should be planned in accordance with recognized standards and legal regulations. Trial design should include the purpose of the trial, endpoints, subject inclusion and exclusion criteria, trial sample size along with its scientific justification and the trial assumptions. The design should also refer to data collection and processing methodology, as well as to statistical methods used.

Appropriate statistical analysis is the key element of a properly designed clinical trial. Fundamental statistical terms used in clinical trials include: population, parameter, confidence interval, hypothesis, statistical test, test power, type I and type II error. If properly matched to the requirements of clinical trials, statistical tools allow to evaluate medical therapy effectiveness in a reliable (statistically significant) manner. 

Pure Clinical provides support for manufacturers throughout the entire in vitro diagnostics medical device performance evaluation process. Based on an appropriate statistical analysis, we are able to plan a reliable trial and summarize its results.


Why is statistics used in a clinical trial?

If a clinical trial provides data that may disclose differences between the effects of two or more factors, statistical analyses are used to establish whether the observed differences are accidental or not. Moreover, appropriately selected statistical methods allow to estimate the trial sample size.

What is a statistical error?

A statistical error is a difference between the expected value and the actual value. It is a deviation between those two values.

What is statistical significance?

Statistical significance is an assessment of whether the obtained result is accidental. A statistically significant result means that it is unlikely to appear accidentally – by chance.