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Bias and confounding in research - with Peter Malliaras

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Konten disediakan oleh @MonashMRU. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh @MonashMRU atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

Associate Professor Peter Malliaras is a physiotherapist and leading researcher with expertise in tendinopathy. Peter has lead a number of clinical trials to assess the efficacy and effectiveness of interventions for people with musculoskeletal conditions.

In this episode, Luke and Pat interview Peter to learn more about bias and confounding in research and how to appreciate and understand uncertainty in science.

  • Examples of biases and confounding
  • Selection, performance, observation, detection and attrition bias in clinical trials
  • Other factors that can explain outcomes of treatment and clinical trials - specific and non-specific treatment effects
  • Why all of this matters to researchers, clinicians and patients

Follow us on Twitter:

@MonashMRU

@drpetemalliaras

@pat_vallance

@lukeperraton

Podcast cover, music and bumper by Kate Vallance, Content Creator, Freelance. E: hooroocreative@gmail.com

  continue reading

28 episode

Artwork
iconBagikan
 
Manage episode 426427954 series 3583541
Konten disediakan oleh @MonashMRU. Semua konten podcast termasuk episode, grafik, dan deskripsi podcast diunggah dan disediakan langsung oleh @MonashMRU atau mitra platform podcast mereka. Jika Anda yakin seseorang menggunakan karya berhak cipta Anda tanpa izin, Anda dapat mengikuti proses yang diuraikan di sini https://id.player.fm/legal.

Associate Professor Peter Malliaras is a physiotherapist and leading researcher with expertise in tendinopathy. Peter has lead a number of clinical trials to assess the efficacy and effectiveness of interventions for people with musculoskeletal conditions.

In this episode, Luke and Pat interview Peter to learn more about bias and confounding in research and how to appreciate and understand uncertainty in science.

  • Examples of biases and confounding
  • Selection, performance, observation, detection and attrition bias in clinical trials
  • Other factors that can explain outcomes of treatment and clinical trials - specific and non-specific treatment effects
  • Why all of this matters to researchers, clinicians and patients

Follow us on Twitter:

@MonashMRU

@drpetemalliaras

@pat_vallance

@lukeperraton

Podcast cover, music and bumper by Kate Vallance, Content Creator, Freelance. E: hooroocreative@gmail.com

  continue reading

28 episode

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