Sentence examples for multiple outcome comparisons from inspiring English sources

Therefore, the threshold of statistical significance should be related to the fraction of the pre-planned number of participants randomised and the number of tests conducted (see also Problems with multiplicity due to multiple outcome comparisons) [ 38- 40] — and a number of different methods have been developed for this purpose [ 41- 44].

One publication could provide multiple outcome comparisons.

Different statistical methods have been proposed to adjust confidence intervals and P-values when multiple outcome comparisons are used [ 12].

Most systematic reviews will include multiple outcome comparisons, and if review authors are free to choose and highlight single results among the many comparisons, there will be an increased risk of false declaration on the effectiveness of an assessed intervention.

How adjustment for multiplicity is done should depend on the design of the trial, i.e., the chosen outcomes and their relative importance, etc. — and different statistical methods have been proposed to adjust the observed confidence intervals and P-values to obtain strong control [ 47, 48] of this risk of type 1 error when multiple outcome comparisons are used.

The aim of this study is to determine patient preferences for the presentation of complex benefit/risk information describing the impact of treatment on multiple clinical outcomes over multiple time horizons, including preferences for graphic format,time horizons, multiple outcomes comparisons, and metrics.

Full Bayesian statistics may be able to account for problems of multiplicity due to interim analyses, multiple outcomes, or comparisons of the same outcome at multiple times [ 57- 59].

Each intervention group was compared with the control group using simple a priori contrasts; because this study had one primary hypothesis, adjustment was not made for multiple group, time, or outcome comparisons.

Other methodological problems include use of multiple outcome measures not adjusted for multiple comparisons (e.g., Colom et al. 2010), as well as use of cut-off points selected retrospectively with risk of false-positive findings (e.g., Swann et al. 1999).

We have presented methods for simultaneous comparison of multiple treatments across multiple outcome measures while preserving the internal randomisation of individual studies.

Our aim in this paper was to present methods for simultaneous comparison of multiple treatments across multiple outcome measures while preserving the internal randomisation of individual studies.