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In this episode, we discuss election polls. The technology of how they are created, the aggregation of election polls, and of course, their trustworthiness.
How about you, do you trust election polls? Or their aggregates?
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In this episode, we discuss publication bias and its effect on meta-analyses.
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Manglende episoder?
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In this episode, we discuss different types of communication technology and their effects on our lives.
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In this episode we discuss the meaning and the interpretation of p-values, their use and their misuse in research.
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In this episode, we discuss what it means and the practical consequences of not rejecting the null hypothesis in clinical trials.
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In this episode, we explore the intricate relationships among three variables, delving into concepts like mediation, moderation, and confounding.
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In this episode, Cale and I are discussing what are target trial emulations and how they differ from classical clinical trials.
For more information, you can read a great paper by Hernán et al. that was published in JAMA in 2022. https://jamanetwork.com/journals/jama/fullarticle/2799678
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In this episode we discuss p-hacking as a statistical technique, its advantages and mainly disadvantages and how to avoid it.
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In this episode, we discuss what we think about pie charts and whether they should be used for reporting data or for portraying statistical results.
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In this episode, we share Martina's keynote lecture on novel advances in clinical trials, which she gave at the annual meeting for the American Society of Clinical Psychopharmacology at the end of May 2024 in Miami, Florida.
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In this episode, we discuss how we have successfully used artificial intelligence tools in our writing and coding work.
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In this episode, we talk about our different approaches to reading published scientific papers.
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In this episode we chat about how storing and managing research data has changed in the last three decades, discussing what has improved and what has stayed the same over time.
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In this episode, we discuss common issues we encounter when we help with grant applications, especially the pet peeves that really bother us.
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In this episode, we discuss our favorite movies that depict scientific research, statistics, or data analysis.
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Data science encompasses many different tools and statistical techniques. In this episode, we discuss data science and the differences between machine learning and traditional statistics.
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In this episode, we discuss how many measures to include when designing a study from our perspectives as data scientists -- how many questionnaires are too many?
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In this episode, Martina and Cale discuss the similarities and differences between SAS and R, two different statistical programming languages that are widely used in the health sciences.
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In this episode, we discuss the purpose of pilot studies in modern research: feasibility, acceptability, tolerability, and safety.
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In this episode, we introduce ourselves and discuss what brought us to pursue our respective careers in public health and data science, and what eventually led us to be part of the HIV Center.
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