Unbiased Analysis of Today's Healthcare Issues
Many research questions require healthcare economists to measure the effect of various patient, physician or market-level characteristics on specific health events. Oftentimes, these events are discrete in nature. For instance, doctor’s visits, ER visits, and hospitalizations are all discrete events. To properly estimate the effect of certain characteristics on a discrete event, count models are needed. The…
How do you measure whether a quality measure is reliable? What does the term “reliable” even mean? In the world of quality measurement, reliability is the ability to confidently tell the difference between a high-performing individual (or physician or hospital) and a low-performing individual. One can think of reliability as a signal-to-noise measure; if the…
If you are evaluating the treatment effect of a policy or medical intervention, does it matter if some of your subjects leave the sample? In many cases, the answer is ‘yes’. The Problem As outlined in Grasdal (2001), the effect of the treatment is simply: Δ = E(Y|X, T=1) − E(Y|X, T=0) However, in some…
Suppose you look at health care spending in two different regions and observe a significant difference. You may want to know what the cause of this difference is. Is it because one region has a mix of people who are sicker; or is because the reason treat patients with a given disease more intensively? One…
All economists are familiar with the problem of selection bias. In non-randomized samples, patients may choose to be in either the treatment or control group based on factors which are also related to the outcome of interest. Even if researchers can design a study that fully controls for selection bias, robust studies must also account…
Understanding quantiles is fairly intuitive. A physician would rank in the τth quantile of in terms of quality of care if he performs better than the proportion τ of the reference group of physicians and worse than the proportion (1–τ). For physicians at the median, half of physicians will perform worse than this doctor and…
How can you estimate an individual’s total lifetime cost of medical care? For people who die in your sample, this is simple. In most data sets, however, not all individuals will die during the period of observation. Thus, the data set is censored for those who do not die. In addition, many standard hazard models…
The Problem Many times, researchers wish to transform the dependent variable of a regression in order to estimate parameter values. Performing the transformation, however, complicates the calculation of the expected value of the dependent variable on the untransformed scale. Assume, the Yi is the dependent variable. Assume the function g is used to transform the…
Asymptotic theory has played a large role in the development of many recent econometric methods. For instance, the central limit theorem states that distribution of the mean drawn from any large samples is approximately normally distributed. Asymptotic theory, however, generally assumes that sampling occurs infinitely and with replacement. In the real world, populations are not…
Oftentimes, people use the following rule of thumb: if the dependent variable is continuous, use OLS; if binary use a logit or probit. But what should you do if your dependent variable is fraction between 0 and 1. To use a logit or probit one would have to unnecessarily transform the dependent variable into binary…