Intention-to-treat analysis, Advanced Statistics

Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular treatment, whether or not they completed, or even received it. At this time the initial random allocation not only governs the allocated treatment, it governs there and then how the patient’s data will be further analyzed, whether or not the patient actually receives prescribed treatment. This technique is adopted to prevent disturbances to the prognostic balance attained by randomization and to prevent the possible bias from permitting compliance, a factor often related to results, to determine groups for comparison. 

Posted Date: 7/28/2012 9:15:38 AM | Location : United States







Related Discussions:- Intention-to-treat analysis, Assignment Help, Ask Question on Intention-to-treat analysis, Get Answer, Expert's Help, Intention-to-treat analysis Discussions

Write discussion on Intention-to-treat analysis
Your posts are moderated
Related Questions
The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.

A directed graph is simple if each ordered pair of vertices is the head and tail of at most one edge; one loop may be present at each vertex. For each n ≥ 1, prove or disprove the

difference between histogram and historigram

Difference between tretment design and experimental design

A term which covers the large number of techniques for the analysis of the multivariate data which have in common the aim to assess whether or not the set of variables distinguish

Write a c++ program to find the sum of 0.123 ? 103 and 0.456 ? 102 and write the result in three significant digits

Lorenz curve : Essentially the graphical representation of cumulative distribution of the variable, most often used for the income. If the risks of disease are not monotonically in

How to estimate MLE for statistical anslysis using Markov Model?

The method or technique for producing the sequence of parameter estimates that, under the mild regularity conditions, converges to maximum likelihood estimator. Of particular signi

Least significant difference test is an approach to comparing a set of means which controls the family wise error rate at some specific level, let's assume it to be α. The hypothe