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We used a χ test and a Kruskal-Wallis test with one degree of freedom to assess the hypothesis that trials reporting more than one deviation from intention to treat had greater proportions of post-randomisation exclusions than trials reporting one or no deviation.
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Since exclusions seem to be the direct consequence of the modified intention to treat description, we tested the hypothesis that the number of deviations from intention to treat was positively associated with the proportion of occurrences of exclusions after randomisation.
The block element in this loop represents the sensitivity to deviations from intentions.
As noted in the opening of this section, the quality of the overall system performance will depend jointly on its ability to respond effectively to both the observer demands associated with detecting the signals in the noise and the control demands associated with the speed/accuracy constraints for correcting deviations from intentions (i.e. errors).
When the description of the modified intention to treat was examined in each trial, 192 (40%) reported one type of deviation from the intention to treat approach, 261 (55%) reported two or more types, and 22 (5%) did not describe any type.
Of the 475 trials, 192 (40%) reported one type of deviation from the intention to treat approach, 189 (40%) reported two, 67 (14%) reported three, five (1%) reported four, and 22 (5%) did not report any type.
The returned results are often unsatisfactory due to their deviation from user intentions, particularly for queries with heterogeneous concepts (such as "apple", "jaguar") or general (non-specific) concepts (such as "landscape", "hotel").
Main outcome measures Incidence of trials in which use of modified intention to treat was reported, and how the approach was described (classified according to the type and number of deviations from the intention to treat approach).
This chapter describes the incidents that occur because of deviations from the design intention, as expressed in the process flow diagrams.
This chapter explains the essential features of a HAZOP study including the need for a conceptual model and the process of generating and examining possible deviations from the design intention.
The acronym CASCADA describes a partial order of intermediate outcomes through conscious knowledge, attitudes, subjective norms and positive deviation from these, the intention to change, the agency (individual and collective) to make change, discussion of possible action and finally action to change (Andersson, 2011; Andersson & Ledogar, 2008).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com