Search results for "Sequential method"
showing 3 items of 3 documents
Performance of adaptive sample size adjustment with respect to stopping criteria and time of interim analysis
2006
The benefit of adjusting the sample size in clinical trials on the basis of treatment effects observed in interim analysis has been the subject of several recent papers. Different conclusions were drawn about the usefulness of this approach for gaining power or saving sample size, because of differences in trial design and setting. We examined the benefit of sample size adjustment in relation to trial design parameters such as 'time of interim analysis' and 'choice of stopping criteria'. We compared the adaptive weighted inverse normal method with classical group sequential methods for the most common and for optimal stopping criteria in early, half-time and late interim analyses. We found …
Recent developments in flow-analysis vibrational spectroscopy
2007
Abstract This review deals with developments in the new century on the use of vibrational spectroscopy techniques for detection in flow-injection analysis (FIA) systems. To provide a picture of the evolution, highlights and future developments in this field, we revisited Fourier transform infrared (FTIR), in the mid-IR and near-IR ranges, and FT-Raman spectrometry applications using different approaches, from classical FIA to modern (sequential injection analysis (SIA) or multicommutation). We used the analytical abstracts database for 2000–06 for the literature search, but we based this review very much on the experience of our team in this field.
Likelihood Inference for Gibbs Processes in the Analysis of Spatial Point Patterns
2001
Plusieurs auteurs ont propose des approximations stochastiques et non-stochastiques au MLE pour les processus de Gibbs utilises pour decrire les interactions entre deux points dans une distribution spatiale de points. Cettes approximations sont necessaires a cause de la difficulte en l'evaluation de la constante qui normalise la f.d.p., Cet article present une comparaison, parmi d'un model de Strauss, des methodes qui utilisent des approximations directes aux MLE et des methodes qui utilisent techniques de Monte Carlo de chaine de Markov. Les techniques de simulation utilisees sont le Gibbs sampler et l'algorithm de Metropolis-Hastings.