Hasil untuk "stat.ME"

Brennan C Kahan, Bryan S Blette, Michael O Harhay et al.

Estimands can help clarify the interpretation of treatment effects and ensure that estimators are aligned with the study's objectives. Cluster-randomised trials require additional attributes to be defined within the estimand compared to individually randomised trials, including whether treatment effects are marginal or cluster-specific, and whether they are participant- or cluster-average. In this paper, we provide formal definitions of estimands encompassing both these attributes using potential outcomes notation and describe differences between them. We then provide an overview of estimators for each estimand, describe their assumptions, and show consistency (i.e. asymptotically unbiased estimation) for a series of analyses based on cluster-level summaries. Then, through a re-analysis of a published cluster-randomised trial, we demonstrate that the choice of both estimand and estimator can affect interpretation. For instance, the estimated odds ratio ranged from 1.38 ( p = 0.17) to 1.83 ( p = 0.03) depending on the target estimand, and for some estimands, the choice of estimator affected the conclusions by leading to smaller treatment effect estimates. We conclude that careful specification of the estimand, along with an appropriate choice of estimator, is essential to ensuring that cluster-randomised trials address the right question.

AG Lynch, MJ Dunning, M. Iddawela et al.

Illumina’s GoldenGate technology is a two-channel microarray platform that allows for the simultaneous interrogation of about 1 500 locations in the genome. GoldenGate has proved a flexible platform not only in the choice of those 1 500 locations, but also in the choice of the property being measured at them. It retains the desirable properties of Illumina’s BeadArrays in that the probes (in this case ‘beads’) are randomly arranged across the microarray, there are multiple instances of each probe and many samples can be processed simultaneously. As for other Illumina technologies, however, these properties are not exploited as they might be. Here we review the various common adaptations of the GoldenGate platform, review the analysis methods that are associated with each adaptation and then, with the aid of a number of example data sets we illustrate some of the improvements that can be made over the default analysis.

A. Ratuszna, A. Pietraszko, A. Chelkowski et al.

V. Kapustianik, I. Polovinko, Yu. Korchak et al.

V.M. Zainullina, V.P. Zhukov, V.M. Zhukovsky

I. H. Ismailzade, R. M. Ismailov, T. M. Stolpakova

G. Berg, J. Poźniak

J. Poźaniak, G. Berg

E. Dryzek, J. Dryzek

FA IJI

Michael A Lewis, Eri Noguchi

R. Joseph