Chance, bias and confounding - The INCLEN Trust

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Matching • It includes elements of both design and analysis • Mostly applicable to case-control study design • It is expensive, difficult and time consuming • By design, the effect of risk factor which has been matched can not be studied • Confounding is avoided not just by matching but by special method of matched table analysis
Analysis • Stratified analyses: Stratum specific estimates of association are calculated, and the differences amongst the strata are assessed by eyeballing, or performing appropriate tests of statistical significance • Summary statistic for the pooled data is calculated as per the method of Mantel and Haenszel • The magnitude of confounding is assessed by looking at the discrepancy between the crude and adjusted estimates (without applying any tests of statistical significance)
Page 1 and 2: Chance, bias and confounding • Th
Page 3 and 4: Confounding • A confounder is a t
Page 5 and 6: Confounder • This third factor sh
Page 7 and 8: An example of confounding • A num
Page 9 and 10: How to avoid confounding • If a c
Page 11 and 12: Common confounders • Age and sex
Page 13 and 14: Positive and negative confounding
Page 15: Restriction • Reduces the number
Page 19 and 20: Bias • The study must be designed
Page 21 and 22: Selection bias • Differential sur

Chance, bias and confounding - The INCLEN Trust

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