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Assessing the robustness of results from clinical trials and meta ...
...The fragility index has been increasingly used to assess the robustness of the results of clinical trials since 2014. It aims at finding the smallest number of event changes that could alter originally statistically significant results. Despite its popularity, some researchers have expressed several ?...
https://pubmed.ncbi.nlm.nih.gov/36084702/
Ludwig ? Find your English sentence
...To further examine the robustness of the association between "Western-type" diet and ideal aging, we performed subsidiary analyses for each component characterizing the ideal aging phenotype....
https://ludwig.guru/s/to+further+examine+the+robustness
Quantifying the robustness of primary analysis ... - Wiley Online Library
...Conducting sensitivity analyses is an integral part of the systematic review process to explore the robustness of results derived from the primary analysis. When the primary analysis results can be s......
https://onlinelibrary.wiley.com/doi/full/10.1002/jrsm.1478
[2309.07273] Real Effect or Bias? Best Practices for Evaluating the ...
...The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is likely in part due to complexity of implementation and often specific and restrictive data requirements required for application of each method. With the ......
https://arxiv.org/abs/2309.07273
Sensitivity analysis in clinical trials: three criteria for a valid ...
...Randomized clinical trials are a tool to generate high-quality evidence of efficacy and safety for new interventions. The statistical analysis plan (SAP) of a trial is generally pre-specified and ......
https://www.nature.com/articles/s41433-022-02108-0
A tutorial on sensitivity analyses in clinical trials: the what, why ...
...Background Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations?such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers?on the overall ......
https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/1471-2288-13-92
(PDF) Quantifying the robustness of primary analysis results: A case ...
...Conducting sensitivity analyses is an integral part of the systematic review process to explore the robustness of results derived from the primary analysis. When the primary analysis results can ......
https://www.researchgate.net/publication/349076914_Quantifying_the_robustness_of_primary_analysis_results_A_case_study_on_missing_outcome_data_in_pairwise_and_network_meta-analysis
Sensitivity and Subgroup Analysis | SpringerLink
...Sensitivity and subgroup analysis are one of the important analyses in meta-analysis. A sensitivity analysis is a critical component of a meta-analysis since it tries to establish the robustness of the reported outcomes, whereas subgroup analysis provides a clear......
https://link.springer.com/chapter/10.1007/978-981-99-2370-0_8
Quantifying the robustness of causal inferences: Sensitivity analysis ...
...Social scientists seeking to inform policy or public action must carefully consider how to identify effects and express inferences because actions based on invalid inferences may not yield the intended results. Recognizing the complexities and uncertainties of social science, we seek to inform inevitable debates about causal inferences by quantifying the conditions necessary to change an ......
https://www.sciencedirect.com/science/article/pii/S0049089X22001260
Quantifying the robustness of primary analysis results: A case study on ...
...Conducting sensitivity analyses is an integral part of the systematic review process to explore the robustness of results derived from the primary analysis. When the primary analysis results can be sensitive to assumptions concerning a model's parameters (e.g., missingness mechanism to be missing at ?...
https://pubmed.ncbi.nlm.nih.gov/33543587/
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