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Evaluating non-randomised intervention studies - NIHR Health ...

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Empirical evaluation of the ability of case-mix adjustment methodologies to control for selection biasTABLE 29 Comparison of methods of case-mix adjustment applied to results of concurrently controlled <strong>studies</strong> with results of RCTsresampled from eight regions within the ECSTPercentage of <strong>studies</strong> withstatistically significantAverageVariability of results results (p < 0.05)OR SD of log OR Ratio with RCT Benefit Harm TotalRCT 1.08 0.69 3 5 9Concurrently controlled <strong>studies</strong>Unadjusted 1.08 0.69 1.01 3 6 9Stratification 1.09 0.74 1.08 3 6 9Logistic regressionFull model a 1.20 1.43 2.10 4 6 10Stepwise p r = 0.05 b 1.06 0.82 1.21 5 7 12Stepwise p r = 0.15 c 1.07 0.91 1.34 5 8 13Propensity scoreMatched d 1.05 0.87 1.27 2 6 8Stratified 1.06 0.82 1.20 5 3 8Regression 1.06 0.80 1.17 5 3 8a Full model includes eight covariates.b Mean number of covariates included: 1.90.c Mean number of covariates included: 3.06.d Mean number of patients matched: 40/80.1005020105Odds ratio210.50.20.10.050.020.01RCTs CCs LR(F) LR(5%) LR(15%) MH PS(M) PS(S) PS(R)FIGURE 16 Comparison of methods of case-mix adjustment applied to results of concurrently controlled <strong>studies</strong> resampled from 14regions within the IST. RCT: results from corresponding <strong>randomised</strong> controlled trials; CCs: unadjusted concurrent controls withoutadjustment, LR(F): adjustment using full logistic regression analysis; LR(5%): adjustment with stepwise logistic regression withp r = 0.05; LR(15%): adjustment with stepwise logistic regression with p r = 0.15; MH: adjustment by Mantel–Haenszel stratification;PS(M): adjustment by matching on propensity score; PS(S): adjustment by stratification on propensity score; PS(R): regressionadjustment based on propensity score.76

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