In practice, both testable and untestable assumptions are generally required to draw inference about the mean outcome measured at the final scheduled visit in a repeated measures study with drop-out. Scharfstein et al. (2014) proposed a sensitivity analysis methodology to determine the robustness of conclusions within a class of untestable assumptions. In their approach, the untestable and testable assumptions were guaranteed to be compatible; their testable assumptions were based on a fully parametric model for the distribution of the observable data. While convenient, these parametric assumptions have proven especially restrictive in empirical research. Here, we relax their distributional assumptions and provide a more flexible, semi-parametric approach. We illustrate our proposal in the context of a randomized trial for evaluating a treatment of schizoaffective disorder.
Scharfstein, D., Mcdermott, A., Díaz, I., Carone, M., Lunardon, N., & Turkoz, I. (2018). Global sensitivity analysis for repeated measures studies with informative drop-out: A semi-parametric approach. BIOMETRICS, 74(1), 207-219.
Citazione: | Scharfstein, D., Mcdermott, A., Díaz, I., Carone, M., Lunardon, N., & Turkoz, I. (2018). Global sensitivity analysis for repeated measures studies with informative drop-out: A semi-parametric approach. BIOMETRICS, 74(1), 207-219. |
Tipo: | Articolo in rivista - Articolo scientifico |
Carattere della pubblicazione: | Scientifica |
Presenza di un coautore afferente ad Istituzioni straniere: | Si |
Titolo: | Global sensitivity analysis for repeated measures studies with informative drop-out: A semi-parametric approach |
Autori: | Scharfstein, D; Mcdermott, A; Díaz, I; Carone, M; Lunardon, N; Turkoz, I |
Autori: | |
Data di pubblicazione: | 2018 |
Lingua: | English |
Rivista: | BIOMETRICS |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1111/biom.12729 |
Appare nelle tipologie: | 01 - Articolo su rivista |