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Each patient undergoing a non-clinical transfer (case) was matched on the basis of absolute propensity (nearest-neighbour match) with two patients who were not transferred, but who had a length of stay at least as long as the time point at which the non-clinical transfer took place (controls).
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If these confounding parameters also apply to rhomboid proteolysis, accurately predicting absolute propensities of natural TM segments from sequence alone may present challenges.
The absolute acceptable propensity score caliper width was 0.01.
Matching was performed using a 1 2 ratio, an optimised matching algorithm and an absolute difference in propensity score of 0.1.
By setting a caliper of 0.5 we pre-specify the largest allowable absolute difference in propensity scores for matched participants, thus ensuring closer balance.
In most cases, these predictions will not be absolute but mathematical propensities.
To assess whether potential imbalances remained after propensity score matching, absolute standardized differences were calculated for covariates included in the propensity score model [ 17, 18]; variables with an absolute standardized difference >0.1 after propensity score matching were identified as potential confounders for inclusion in multivariable outcome models.
Balance between mTIH group and non-mTIH group for each variable was evaluated by propensity score distributions and absolute standardized differences (ASD) before and after matching were calculated (Fig. 1).
After propensity score matching, the absolute difference between surgical patients with and without diabetes was insignificant.
Adjustment for baseline covariates using a propensity model suggested greater absolute benefit in patients at advanced age.
As such, using the 'turn propensity' scale as an absolute value to predict rhomboid substrates from natural transmembrane sequences could prove to be challenging.
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