دانلود رایگان مقاله سیستم های اطلاعات جغرافیایی برای ارزیابی اعتبار خارجی در آزمایشات تصادفی

Introduction

To support claims that RCTs can reduce health disparities (i.e., are translational), it is imperative that methodologies exist to evaluate the tenability of external validity in RCTs when probabilistic sampling of participants is not employed. Typically, attempts at establishing post hoc external validity are limited to a few comparisons across convenience variables, which must be available in both sample and population. A Type 2 diabetes RCT was used as an example of a method that uses a geographic information system to assess external validity in the absence of a priori probabilistic community-wide diabetes risk sampling strategy.

CONCLUSIONS

The use of GIS offers a practical and straightforward alternative to common techniques that quantify representativeness by using limited measures available for both the sample and population. True representativeness can only be assumed if recruitment and enrollment procedures were defined using some form of probabilistic sampling. It should be understood that without random sampling, there is no correct answer to the question of external validity. Therefore, establishing representativeness after the fact in non-randomized samples must involve some degree of subjective probability using a more graphical and Bayesian heuristic and not traditional hypothesis testing with its NeymanPearson accept/reject concepts.40,41 Through graphical analysis, assumption of location as a highly reliable principal variable, and simple statistical modeling, this method offers an effective approach to improve assessments of the external validity of community-based RCTs.