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Published byElfreda Hawkins Modified about 1 year ago

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Dealing with bias Boyce Sigweni Martin Shepperd NB no cats were harmed in the making of this presentation!

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What is bias? “[L]et us define bias as the combination of various design, data, analysis, and presentation factors that tend to produce research findings when they should not be produced.” John Ioannidis (2005)

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What is (the) scientific method? Guidelines, methods, procedures and evaluation criteria to reduce bias – reduce subjectivity, promote objectivity Other issues but bias is central

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Blinding Withholding information to reduce bias, e.g., – blind reviewing – blind treatments to participants (placebo) – blind treatments to experimenters (double blind) – blind analysis

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Blinding Hierarchy Open Single blind Double blind Complete blind (including the analyst)

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Some work on blind analysis Over to Boyce …

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Bias harms randomisation Random implies selection cannot be predicted in advance beyond the natural odds. Sample selection to estimate population parameters Assignment of experimental units / participants to treatments Choosing data sets

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Cats and survival odds A study shows the odds slightly improve the further a cat falls. Used data supplied by vets in NY. Why? What's the problem?

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Do Finches help novices learn to code? Analysis by cohort What's the problem? Solutions?

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Predicting software defects Same old … But inference into all software? Some data sets may favour some learners

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Random doesn't mean unusual things can't happen! Consider stratified randomisation (reduce confounding) Type I and II errors can, and do, occur! Measurement error (random or biased?) Meta-analysis

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Meta-analysis and bias Publication bias – file drawer problem – selective reporting of results – refereeing bias against 'negative' results

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Problems with blinding Impractical Unethical Sometimes can address by a crossover design

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