Related Experiment Video
Updated: Jun 27, 2026
Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Population-based versus hospital-based controls: are they comparable?
Alberto Ruano-Ravina1, Mónica Pérez-Ríos, Juan Miguel Barros-Dios
1Department of Preventive Medicine and Public Health, University of Santiago de Compostela, Spain. alberto.ruano@usc.es
Objective:
To compare whether there are differences among hospital and population controls.
Methods:
Two case-control studies were conducted on lung cancer risk factors in the Santiago de Compostela Public Health District. Whereas one used randomly chosen census-based population controls, the other used consecutive hospital controls that went to the reference hospital for non-smoking-related trivial interventions. The differences were analyzed using logistic regression. The dependent variable was type of control (hospital or population).
Results:
Hospital controls had a similar tobacco habit than population controls, but consumed more alcohol. For those consuming more than 50 ml daily, the risk of being a hospital control was 4.83 (95%CI: 2.55-9.14).
Conclusions:
There may be some differences between hospital and population-based controls, which must be taken into account in the design of case-control studies. It is necessary to ascertain whether such differences are reproduced at other geographic locations and whether they can affect estimation of exposure-disease.
Related Concept Videos
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
01:28Introduction to Nonparametric Statistics
One of...
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...
01:28Hospitals-I
00:59Hospitals-II
Nurses that work in hospitals have...
01:24Kaplan-Meier Approach