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On Sequential Treatment Allocations in Clinical Trials

Carl-Fredrik Burman (Institutionen för matematik)
Göteborg : Chalmers University of Technology, 1996.

This dissertation treats baseline-dependent sequential designs of two-treatment parallel-group clinical trials. The treatment assignments are chosen in order to minimize the variance, in a linear model, of the treatment effect. This is done for each new allocation using a generalized biased coin design, or a non-randomized minimization' method.

For the minimization' method, the balance process is shown to be tight. It follows that the loss, defined roughly as the number of patients lost d ue to imbalance, is of order N 1 (where N is the trial size).

The ANCOVA statistic is used in both parametric and randomization tests when the design is randomized. Deficiency (or second-order efficiency), of design and analysis combin ed, is defined in terms of expected p-value. The asymptotic deficiency of the randomization analysis following a biased coin design is obtained when prognostic factors are ignored. It can be arbitrarily close to zero re lative the balanced t-test when assuming a normal model. Similar results, when prognostic variables are used, are indicated by simulations.

As a comparison, the expected loss and asymptotic expected p-value deficiency, relative a balanced parametric test, equal the number of prognostic variables when using independent randomizations.

AMS 1991 subject classification: 62L05, 60K30, 62G10, 62P10

Nyckelord: treatment assignment, clinical trial, biased coin designs, balance of prognostic factors, sequential design, randomization test, expected p-value, deficiency, efficiency

Denna post skapades 2006-08-25.
CPL Pubid: 1117


Institutioner (Chalmers)

Institutionen för matematik (1987-2001)



Chalmers infrastruktur