Medical Statistics

Unfortunately, the findings of confirmatory trials are often misinterpreted. There is no guarantee that a hypothesis is true just because it passes a statistically significant test. The significance level, typically 5%, represents nothing more than the likelihood of a false positive result. Hence, systematic reviews and meta-analyses, which lessen the uncertainty by integrating the findings from multiple trials of the same endpoint, play a significant role in the pursuit of truth. Conversely, c...

Medical research is primarily performed using samples of humans, laboratory animals, or cells, but the studied phenomena are rarely limited to what can be observed in samples of these. On the contrary, the aim is almost always to learn about the population from which the sample was drawn. However, this leads to generalisation problems. Sampling variability makes the results from sample studies uncertain, and the consequences of non-random sampling may induce an uncertain amount of bias. The un...

The term 'incidence' may seem straightforward, but it can refer to three distinct metrics: the total number of new cases, cumulative incidence (risk), and incidence density. The calculations of these metrics can vary in difficulty (1). As demonstrated by Havers-Borgersen et al. (2) mistakes are often published, and numerous errors probably remain undetected as a result of unclear methodological descriptions. 1. Incident numbers In the most basic form, incidence begins with the number of new ca...

Misuse of statistical terminology is very common in medical research reports. The misuse not only indicate methodological ignorance, it also threatens the consistency of the statistical terminology. For example, Nahoui et al. (1) state that in their sample of patients, those "in 3rd and 4th quartiles of median PES [esophageal pressure] had increased mortality risk compared to 1st quartile". Given that only three quartiles exist, this statement is remarkable. A quartile is defined (2) like this:...

Using the correct terminology helps to ensure that the same words are used for the same concepts, which is crucial for a clear communication and for avoiding misunderstandings. The term 'nonparametric data' appears often in the statistics section of research reports. For example, Dugan et al. (1) state that the "data from patients in the two groups were compared using Mann-Whitney U tests for nonparametric data." However, statistical tests are used to evaluate sampling uncertainty, to test a hy...

Medical science is one of the youngest sciences, at least as we define science today. From 1665, when the first scientific journals were established, to the mid-20th century, when modern medical research emerged, medical research publications were primarily descriptive (case reports) or presenting subjective comments (expert opinions). It lasted until the mid-20th century, until medical research focused on empirical evidence collected from samples of patients and evaluating the uncertainty of th...

While the risk (or incidence) in absolute numbers is an important measure from an individual and a public health perspective and for planning health care resources, the biological effect of a beneficial or harmful exposure is always measured and medically interpreted in terms of relative risk. With some prospective study designs, the relative risk (RR) can be measured directly from risks or indirectly from incidence density rates. Other statistical methods produce other effect measures, such a...

The terms univariate, multivariate, univariable, and multivariable often appear in scientific medical publications. For example, Kanbaş et al., claim that they have evaluated factors prognostic for cervical cancer using multivariate Cox regression. However, Cox regression is a semi-parametric technique that they use to evaluate how a single response variable (survival time) is associated to one or more explanatory (potentially prognostic) variables. That is not a multivariate analysis. Univar...