Olivine in CV chondrite matrices: Structure, size-distribution, and morphology

Accepted versio

A rock fabric in chondrite matrix.

Accepted versio

Fabric analysis of allende matrix using EBSD

Accepted versio

Fayalitic olivine in Allende matrix: Evidence for a secondary origin

Published versio

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

Methodological bias in cluster randomised trials

Background: Cluster randomised trials can be susceptible to a range of methodological problems. These problems are not commonly recognised by many researchers. In this paper we discuss the issues that can lead to bias in cluster trials. Methods: We used a sample of cluster randomised trials from a recent review and from a systematic review of hip protectors. We compared the mean age of participants between intervention groups in a sample of 'good' cluster trials with a sample of potentially biased trials. We also compared the effect sizes, in a funnel plot, between hip protector trials that used individual randomisation compared with those that used cluster randomisation. Results: There is a tendency for cluster trials, with evidence methodological biases, to also show an age imbalance between treatment groups. In a funnel plot we show that all cluster trials show a large positive effect of hip protectors whilst individually randomised trials show a range of positive and negative effects, suggesting that cluster trials may be producing a biased estimate of effect. Conclusion: Methodological biases in the design and execution of cluster randomised trials is frequent. Some of these biases associated with the use of cluster designs can be avoided through careful attention to the design of cluster trials. Firstly, if possible, individual allocation should be used. Secondly, if cluster allocation is required, then ideally participants should be identified before random allocation of the clusters. Third, if prior identification is not possible, then an independent recruiter should be used to recruit participants

A multivariate hierarchical Bayesian approach to measuring agreement in repeated measurement method comparison studies

Background. Assessing agreement in method comparison studies depends on two fundamentally important components; validity (the between method agreement) and reproducibility (the within method agreement). The Bland-Altman limits of agreement technique is one of the favoured approaches in medical literature for assessing between method validity. However, few researchers have adopted this approach for the assessment of both validity and reproducibility. This may be partly due to a lack of a flexible, easily implemented and readily available statistical machinery to analyse repeated measurement method comparison data. Methods. Adopting the Bland-Altman framework, but using Bayesian methods, we present this statistical machinery. Two multivariate hierarchical Bayesian models are advocated, one which assumes that the underlying values for subjects remain static (exchangeable replicates) and one which assumes that the underlying values can change between repeated measurements (non-exchangeable replicates). Results. We illustrate the salient advantages of these models using two separate datasets that have been previously analysed and presented; (i) assuming static underlying values analysed using both multivariate hierarchical Bayesian models, and (ii) assuming each subject's underlying value is continually changing quantity and analysed using the non-exchangeable replicate multivariate hierarchical Bayesian model. Conclusion. These easily implemented models allow for full parameter uncertainty, simultaneous method comparison, handle unbalanced or missing data, and provide estimates and credible regions for all the parameters of interest. Computer code for the analyses in also presented, provided in the freely available and currently cost free software package WinBUGS

Evaluation of marking of peer marking in oral presentation.

BACKGROUND: Peer marking is an important skill for students, helping them to understand the process of learning and assessment. This method is increasingly used in medical education, particularly in formative assessment. However, the use of peer marking in summative assessment is not widely adopted because many teachers are concerned about biased marking by students of their peers. OBJECTIVE: The aim of this study was to investigate whether marking of summative peer assessment can improve the reliability of peer marking. METHODS: In a retrospective analysis, the peer-marking results of a summative assessment of oral presentations of two cohorts of students were compared. One group of students was told that their peer marks would be assessed against a benchmark consisting of the average of examiner marks and that these scores together with the peer and examiner marks would form their final exam results. The other group of students were just informed that their final exam results would be determined based on the examiner and peer marks. RESULTS: Based on examiner marks, both groups of students performed similarly in their summative assessment, agreement between student markers was less consistent and more polar than the examiners. When compared with the examiners, students who were told that their peer marking would be scored were more generous markers (their average peer mark was 2.4 % points higher than the average examiner mark) while students who were not being scored on their marking were rather harsh markers (their average peer mark was 4.2 % points lower than the average examiner mark), with scoring of the top-performing students most affected. CONCLUSIONS: Marking of peer marking had a small effect on the marking conduct of students in summative assessment of oral presentation but possibly indicated a more balanced marking performance