Asset Details
Do you wish to reserve the book?
Bias reduction in repeated-measures observational studies by the use of propensity score: The case of enteral sedation for critically ill patients
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Bias reduction in repeated-measures observational studies by the use of propensity score: The case of enteral sedation for critically ill patients
Do you wish to request the book?
Bias reduction in repeated-measures observational studies by the use of propensity score: The case of enteral sedation for critically ill patients
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Bias reduction in repeated-measures observational studies by the use of propensity score: The case of enteral sedation for critically ill patients
2012
Overview
Within the evidence-based medicine paradigm, randomized controlled trials represent the “gold standard” to produce reliable evidence. Indeed, planning and implementing randomized controlled trials in critical care medicine presents limitations because of intrinsic and structural problems. As a consequence, observational studies still occur frequently. In these cases, propensity score (PS) (probability of receiving a treatment conditional on observed covariates) is an increasingly used technique to adjust the results. Few studies addressed the specific issue of a PS correction of repeated-measures designs.
Three techniques for correcting the analysis of nonrandomized designs (matching, stratification, regression adjustment) are presented in a tutorial form and applied to a real case study: the comparison between intravenous and enteral sedative therapy in the intensive care unit setting.
After showing the results before and after the use of PS, we suggest that such a tool allows to partially overcoming the bias associated with the observational nature of the study. It permits to correct the estimates for any observed covariate, while unobserved confounders cannot be controlled for.
Propensity score represents a useful additional tool to estimate the effects of treatments in nonrandomized studies. In the case study, an enteral sedation approach was equally effective to an intravenous regime, allowing for a lower level of sedation and spare of resources.
Publisher
Elsevier Inc,Elsevier Limited
