Analysis of residues resulting from mafic silicate impacts into aluminium 1100

Accepted versio

Survivability of meteorite projectiles – results from impact experiments.

Published versio

Cluster randomised trials in the medical literature: two bibliometric surveys

Background: Several reviews of published cluster randomised trials have reported that about half did not take clustering into account in the analysis, which was thus incorrect and potentially misleading. In this paper I ask whether cluster randomised trials are increasing in both number and quality of reporting. Methods: Computer search for papers on cluster randomised trials since 1980, hand search of trial reports published in selected volumes of the British Medical Journal over 20 years. Results: There has been a large increase in the numbers of methodological papers and of trial reports using the term 'cluster random' in recent years, with about equal numbers of each type of paper. The British Medical Journal contained more such reports than any other journal. In this journal there was a corresponding increase over time in the number of trials where subjects were randomised in clusters. In 2003 all reports showed awareness of the need to allow for clustering in the analysis. In 1993 and before clustering was ignored in most such trials. Conclusion: Cluster trials are becoming more frequent and reporting is of higher quality. Perhaps statistician pressure works

Performance status and trial site-level factors are associated with missing data in palliative care trials: An individual participant-level data analysis of 10 phase 3 trials

BACKGROUND: Missing data compromise the internal and external validity of trial findings, however there is limited evidence on how best to reduce missing data in palliative care trials. AIM: To assess the association between participant and site level factors and missing data in palliative care trials. DESIGN AND SETTING: Individual participant-level data analysis of 10 phase 3 palliative care trials using multi-level cross-classified models. RESULTS: Participants with missing data at the previous time-point and poorer performance status were more likely to have missing data for the primary outcome and quality of life outcomes, at the primary follow-up point and end of follow-up. At the end of follow-up, the number of site randomisations and number of study site personnel were significantly associated with missing data. Trial duration and the number of research personnel explained most of the variance at the trial and site-level respectively, except for the primary outcome where the amount of data requested was most important at the trial-level. Variance at the trial level was more substantial than at the site level across models and considerable variance remained unexplained for all models except quality of life at the end of follow-up. CONCLUSION: Participants with a poorer performance status are at higher risk of missing data in palliative care trials and require additional support to provide complete data. Performance status is a potential auxiliary variable for missing data imputation models. Reducing trial variability should be prioritised and further factors need to be identified and explored to explain the residual variance

Performance status and trial site-level factors are associated with missing data in palliative care trials: An individual participant-level data analysis of 10 phase 3 trials.

BACKGROUND: Missing data compromise the internal and external validity of trial findings, however there is limited evidence on how best to reduce missing data in palliative care trials. AIM: To assess the association between participant and site level factors and missing data in palliative care trials. DESIGN AND SETTING: Individual participant-level data analysis of 10 phase 3 palliative care trials using multi-level cross-classified models. RESULTS: Participants with missing data at the previous time-point and poorer performance status were more likely to have missing data for the primary outcome and quality of life outcomes, at the primary follow-up point and end of follow-up. At the end of follow-up, the number of site randomisations and number of study site personnel were significantly associated with missing data. Trial duration and the number of research personnel explained most of the variance at the trial and site-level respectively, except for the primary outcome where the amount of data requested was most important at the trial-level. Variance at the trial level was more substantial than at the site level across models and considerable variance remained unexplained for all models except quality of life at the end of follow-up. CONCLUSION: Participants with a poorer performance status are at higher risk of missing data in palliative care trials and require additional support to provide complete data. Performance status is a potential auxiliary variable for missing data imputation models. Reducing trial variability should be prioritised and further factors need to be identified and explored to explain the residual variance

Comparisons against baseline within randomised groups are often used and can be highly misleading

<p>Abstract</p> <p>Background</p> <p>In randomised trials, rather than comparing randomised groups directly some researchers carry out a significance test comparing a baseline with a final measurement separately in each group.</p> <p>Methods</p> <p>We give several examples where this has been done. We use simulation to demonstrate that the procedure is invalid and also show this algebraically.</p> <p>Results</p> <p>This approach is biased and invalid, producing conclusions which are, potentially, highly misleading. The actual alpha level of this procedure can be as high as 0.50 for two groups and 0.75 for three.</p> <p>Conclusions</p> <p>Randomised groups should be compared directly by two-sample methods and separate tests against baseline are highly misleading.</p

The distribution of meteorite finds in the Namibian desert and recovery of a highly shocked meteorite pairing group.

Published versio

Galaxy and Mass Assembly (GAMA): the effect of close interactions on star formation in galaxies

The modification of star formation (SF) in galaxy interactions is a complex process, with SF observed to be both enhanced in major mergers and suppressed in minor pair interactions. Such changes likely to arise on short time-scales and be directly related to the galaxy–galaxy interaction time. Here we investigate the link between dynamical phase and direct measures of SF on different time-scales for pair galaxies, targeting numerous star- formation rate (SFR) indicators and comparing to pair separation, individual galaxy mass and pair mass ratio. We split our sample into the higher (primary) and lower (secondary) mass galaxies in each pair and find that SF is indeed enhanced in all primary galaxies but suppressed in secondaries of minor mergers. We find that changes in SF of primaries are consistent in both major and minor mergers, suggesting that SF in the more massive galaxy is agnostic to pair mass ratio. We also find that SF is enhanced/suppressed more strongly for short-duration SFR indicators (e.g. Hα), highlighting recent changes to SF in these galaxies, which are likely to be induced by the interaction. We propose a scenario where the lower mass galaxy has its SF suppressed by gas heating or stripping, while the higher mass galaxy has its SF enhanced, potentially by tidal gas turbulence and shocks. This is consistent with the seemingly contradictory observations for both SF suppression and enhancement in close pairs