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Observational and retrospective research

Real-world data

Design and analysis for retrospective cohorts, database studies and observational research, with explicit attention to confounding, bias and cautious interpretation.

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ServiceWhat you get
Real-world dataRetrospective and observational research with explicit handling of confounding, bias and the limits of what routinely collected data can support.

Frequently asked questions

Can observational data prove causation?

Rarely on its own. Causal language should be used only where the design, assumptions and analysis support it, and we will say when they do not.

Related reading

  1. 01Propensity scores: matching, weighting and what they cannot fixA propensity score balances the variables you measured. It does nothing about the ones you did not, which in observational research are usually the ones that mattered.
  2. 02Immortal time bias, and how to avoid building it into your studyA period during which the outcome could not have happened, assigned to one group by the way the study defines exposure. It reliably makes treatments look protective.
  3. 03What is real-world evidence, and what can it actually answer?Real-world data is data collected for a purpose other than your study. That single fact explains most of both its value and its limits.

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