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After the propensity score was constructed, we matched the propensity score of each patient with diabetes and without diabetes (a 1 1 match).
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This was done by matching the propensity scores.
A total analytic sample consisted of 7,098 hepatitis B patients and compared group (35,490 general populations) came from similar characteristics after matching the propensity score.
We were able to match 32 757 public deliveries with private deliveries and from figure 2 it is evident that after matching, the propensity scores for the public and private births revealed a high degree of overlap and similarity in shape.
We will then match the propensity score of each case who received the intervention to the nearest propensity scores (up to 3) available among control patients whose propensity scores lie within a caliper window of 0.2σ of the case index, where σ is a measure of variation in the propensity score distributions of cases and controls as given in Rosenbaum and Rubin [ 35].
In addition, the 108 untreated patients are also candidates for rhAPC therapy in the sense that they have propensities to receive rhAPC that match the propensities of those 108 patients actually receiving rhAPC.
Fifty-five patinnts in each group (NIV or oxygen only) were matched according the propensity score.
Ninety patients in each group (HFNC or oxygen only) were matched according the propensity score.
In the first, propensity for treatment with liposomal bupivacaine was estimated using pretreatment variables and the patients were matched on the propensity score.
T1D patients are matched using the propensity score to individuals in a control group of those without diabetes.
The patients who were matched in the propensity score did not differ substantially from the unmatched excluded patients in any of the covariates included in the propensity score.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com