Unbiased Analysis of Today's Healthcare Issues

Confirmation Bias

HT: Incidental Economist.

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What are cure fraction models?

Many people are familiar with survival models. Survival models measure the probability of survival to a given time period. The “problem” addressed by these models is that some people are “censored”, in other words, the do not die in the sample time period. Although longer survival is good in practice, for statisticians it is problematic […]

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What is attribute non-attendance?

In discrete choice experiments (DCEs), respondents are asked to choose amoung different options which vary across different attributes. For instance, a DCE on mobile phone preferences could have processor speed, battery life, screen size and cost as attributes. A DCE looking at different treatments could have expected survival, anticipated side effects and cost as attributes. […]

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Rankings and Kendall’s W

How can you compare how similar two rankings are.  For instance, US News and Consumer Reports may both rate hospitals.  If they have identical ratings, then they are obviously the same.  However, what if the rankings differ for 2 hospitals?  For 4 hospitals?  How can one quantify the similar of rankings? One method for doing so […]

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Longer trials or larger sample size?

Developing drugs is expensive. Some estimates have estimated that the cost of bringing a drug to market is $1 billion. In addition, payers are now reimbursing based on the perceived value of a treatment. That is, treatments that provide more health benefits receive higher reimbursements. In this world of value-based pricing (VBP), pharmaceutical companies have […]

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Type I and Type II Errors for Dummies

In previous posts, I have describe in detail what constitutes Type I and Type II errors.  This figure, however, conveys the concept much more succinctly. HT: Marginal Revolution.

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Guidelines for indirect treatment comparisons

Is treatment A better than treatment B?  This questions is often difficult to answer, especially if there is not head-to-head evidence comparing the two treatments.  In other cases, however, one can use indirect evidence.  For instance, one randomized controlled trial (RCT) may compare treatment A to C (e.g., a placebo) and another trial can compare […]

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Increasing Generalizability of RCTs

Is your randomized controlled trial (RCT) generalizable to the general population?  This question is known as external validity and is a major issue for a number of treatments.  Sometimes, a treatment is very effective in an RCT, but less so in the real world. One reason why this may be the case is that the […]

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Measuring cause-specific mortality?

This question is not so easy to answer, even when using data from a randomized trial.  Further, many studies do not have the statistical power to identify cause-specific mortality.  Consider the following example from Kim and Thompson: Consider a trial of an intervention only influencing a single cause of death, or a few specific causes […]

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Beta Binomial Regression

Oftentimes, one will observe data cluster around two different points.  This distribution is known as a bimodal distribution.  A bimodal distribution could arise, for instance, when patients have two choices of health care providers, and the data measure the share of times patients use one of the providers. To model the effect of different covariates on variable […]

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