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The R, quantifying the proportion of outcome variation explained, was used for model reduction.
A very small proportion of outcome data were missing and this is unlikely to have been systematically biased.
Considering the large proportion of outcome variation that remains unexplained, the models need to be refined [ 5].
This 40% absolute difference represents the difference between the assumed 50% proportion of outcome incidence in the surgery group and 10% incidence in the clinical treatment group.
For each trial we calculated results in terms of absolute difference (mean or proportion of outcome in intervention group minus control at study completion) and relative percentage difference (absolute difference divided by post-intervention score in the control group).
We use an elbow plot a plot of the proportion of outcome variation explained by the lasso fit (the R value) against number of variables selected at each stage in the LARS procedure.
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Higher proportion of outcomes in treatment experienced cohort is due to longer follow-up.
Calibration plots for each model based on these groups were produced showing the mean predicted probability of outcome against the observed proportion of outcomes.
Unfortunately, the proportion of outcomes that went unreported could not be assessed here, owing to a lack of information on trial protocol.
These include COPD; cardiovascular, central nervous system, renal and liver disorders; diabetes; immunosuppressive conditions or stroke There was marked variability between seasons in terms of the proportion of outcomes attributed to RSV versus those attributed to influenza.
This could also contribute to the stronger RD-ozone association observed for ED visits, which may have included a higher proportion of outcomes with a stronger association with ozone.
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