Here are links to some resources to help you understand intention-to-treat analysis.
Intention-to-treat concept: A review in Perspectives in Clinical Research.
Randomized controlled trials often suffer from two major complications, i.e., noncompliance and missing outcomes. One potential solution to this problem is a statistical concept called intention-to-treat (ITT) analysis. …
According to Fisher et al. (1990), the ITT analysis includes all randomized patients in the groups to which they were randomly assigned, regardless of their adherence with the entry criteria, regardless of the treatment they actually received, and regardless of subsequent withdrawal from treatment or deviation from the protocol.
In other words, ITT analysis includes every subject who is randomized according to randomized treatment assignment. It ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization.[2–5] ITT analysis is usually described as “once randomized, always analyzed”.[6,7]
ITT analysis avoids overoptimistic estimates of the efficacy of an intervention resulting from the removal of non-compliers by accepting that noncompliance and protocol deviations are likely to occur in actual clinical practice.
In the Journal of the American Medical Association, “The Intention-to-Treat PrincipleHow to Assess the True Effect of Choosing a Medical Treatment.”
Why Is ITT Analysis Used?
The effectiveness of a therapy is not simply determined by its pure biological effect but is also influenced by the physician’s ability to administer, or the patient’s ability to adhere to, the intended treatment. The true effect of selecting a treatment is a combination of biological effects, variations in compliance or adherence, and other patient characteristics that influence efficacy. Only by retaining all patients intended to receive a given treatment in their original treatment group can researchers and clinicians obtain an unbiased estimate of the effect of selecting one treatment over another.
Intention to treat gives a pragmatic estimate of the benefit of a change in treatment policy rather than of potential benefit in patients who receive treatment exactly as planned
Full application of intention to treat is possible only when complete outcome data are available for all randomised subjects
About half of all published reports of randomised controlled trials stated that intention to treat was used, but handling of deviations from randomised allocation varied widely
Many trials had some missing data on the primary outcome variable, and methods used to deal with this were generally inadequate, potentially leading to bias
Intention to treat analyses are often inadequately described and inadequately applied