Different analysis sets

In a superiority trial the primary analysis will be based on the full analysis set with the per-protocol set being used as the basis for a supportive secondary analysis, and in this sense there will be no multiplicity issues. The form of the analysis, however, depends in addition on the methods to be used to account for missing data and these should clearly be pre-specified. It is also good practice to explore the robustness of the conclusions to both the choice of the per-protocol set and the methods to be used for missing data. These analyses again will be supportive (or not) of the main conclusions and no multiplicity aspects arise. 

In equivalence and non-inferiority trials (see Chapter 12), the full analysis set and the per-protocol set have equal status and are treated as co-primary. The requirement, therefore, is to show significance for each of these analyses. This is another case where significance is needed on all endpoints with both analyses being conducted at the usual 5 per cent significance level. 

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Using different analysis sets or different algorithms for missing data... 

Analysis of Variance (ANOVA) is a useful tool to compare the difference between sets of analytical results to determine if there is a statistically meaningful difference between a sample analyzed by different methods or performed at different locations by different analysts. The reader is referred to reference [1] and other basic books on statistical methods for discussions of the theory and applications of ANOVA examples of such texts are [2, 3],... 

Reductions are also discussed under the section on analysis. The reduction on Hg has been extensively studied in connection with analytical applications (see Section VI), and is complicated by adsorption, transmetallation with mercury and reoxidations of transient products. Some disagreement as to the details is apparent in the primary literature76. Comparisons between different experimental settings should be made with critical appraisal. 

Neither the quark matter EOS nor the hadronic EOS are very well known quantitatively at the densities relevant for compact objects. In order to get an idea on the uncertainties of our analysis we will consider four different hadronic EOS and two different parameter sets for the NJL description of quark matter. The hadronic EOS are ... 

However, quite complicated algorithms are needed for extracting the data Ifom texture patterns. The analysis of texture patterns must be performed in a different way compared to regular electron diffraction patterns, due to different geometrical settings. Firstly, the centre of the... 

KcsA crystals suitable for X-ray crystallographic analysis using synchrotron radiation were obtained and the data collected and analyzed for multiple crystals and six different data sets as described in the 1998 Science publication (reference 15). The final KcsA pore structure, including amino acid residues 23 to 119 of the K+ channel, refined to 3.2 A. The X-ray data were deposited in the Protein Data Bank with the accession number 1BL8. 

The bottleneck in utilizing Raman shifted rapidly from data acquisition to data interpretation. Visual differentiation works well when polymorph spectra are dramatically different or when reference samples are available for comparison, but is poorly suited for automation, for spectrally similar polymorphs, or when the form was previously unknown [231]. Spectral match techniques, such as are used in spectral libraries, help with automation, but can have trouble when the reference library is too small. Easily automated clustering techniques, such as hierarchical cluster analysis (HCA) or PCA, group similar spectra and provide information on the degree of similarity within each group [223,230]. The techniques operate best on large data sets. As an alternative, researchers at Pfizer tested several different analysis of variance (ANOVA) techniques, along with descriptive statistics, to identify different polymorphs from measurements of Raman... 

It is good statistical practice to evaluate the sensitivity of the conclusions to different choices of the analysis sets. 

In general, it is advantageous to demonstrate a lack of sensitivity of the principle trials results to alternative choices of the set of subjects analysed. In confirmatory trials it is usually appropriate to plan to conduct both an analysis of the full analysis set and a per-protocol analysis, so that any differences between them can be the subject of explicit discussion and interpretation. ... 

In a similar way it may be that the crd seen in the analysis based on the per-protocol set is larger than that seen in the full analysis set and this anticipated difference may also need to be factored in. 

In superiority trials, the full analysis set is the basis for the primary analysis. As discussed in Section 7.2, the regulators prefer this approach, in part, because it gives a conservative view of the new treatment. In equivalence/non-inferiority trials, however, it is not conservative and will tend to result in the treatments looking more similar than, in reality, they are. This is because the full analysis set will include the patients who have not complied with the medication schedules and who have not followed the study procedures and the inclusion of such patients will tend to weaken treatment differences. 

These particular points relate to each individual trial, but equally there will be similar considerations needed at the level of the development plan. In order for the overall, ordered programme of clinical trials to be scientifically sound there needs to be a substantial amount of commonality across the trials in terms of endpoints, definitions of analysis sets, recording of covariates and so on. This will facilitate the use of integrated summaries and meta-analysis for the evaluation and presentation of the complete programme or distinct parts of that programme, and outside of that, will allow a consistency of approach to the evaluation of the different trials. 

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