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Burns et al. [ 8] assume that the inconsistent effects over recent years might be explained by differences in trial contexts.
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Additionally, the interpretation of the results is complicated by differences in the trial duration and in the cohort studied.
Finally, the three training sessions were identical in terms of sequences and trial randomisation, ensuring that behavioural change could not be explained by differences in sequences or trial delivery.
We used a condition-specific baseline for ISPC in order to control for spurious results induced by differences in the number of trials for the different trial types.
A vague prior for the study specific baseline αs~ N 0,10) is used to ensure estimates of treatment effect are informed by within trial differences between treatment arms, and not by differences in absolute response between trials.
Meta-analyses are expected to produce generalizable evidence by adjusting inconsistent outcomes to differences in trial design (e.g. the size of trial subjects), outcome measures, or the statistical models used.
5 Besides confounding by indication, these differences might be explained not only by differences in drug use between trials and observational studies 29 but also by the quality of observational studies, which lead to high heterogeneity between studies and a possible underestimation of effects.
When analysed by induction agent, there were no differences in trial outcomes between parous OPC and parous IP. 93 of 101 women completed the satisfaction survey (Table 5).
We used the Higgins I coefficient to quantify the proportion of inconsistency in interventional effects across trials not explained by chance (i.e., reflecting true differences in trial results) alone [ 17].
The fixed study level 'baseline' term is a nuisance parameter, included to ensure that the treatment effect estimates are informed by within trial differences between treatment arms and not by differences in baseline event rates across trials.
The disadvantage is that differences between conditions might be explained by differences in the number of correct/incorrect trials.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com