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Tracking differences between IFC product models: A generic approach for fully-concurrent systems
Published in Manuel Martínez, Raimar Scherer, eWork and eBusiness in Architecture, Engineering and Construction, 2020
Famous tools like GNU diff compare two textual files and apply status to each line of both files: added, removed or changed. These utilities use mostly the Longest Common Subsequence (LCS) algorithm (Myers 1986). CVS uses this algorithm as well to detect differences between two versions of program sources. However Chatwathe noticed that the LCS algorithm is not adapted to structured data (Chawathe et al. 1996). So we need to investigate other techniques to compare two STEP product models.
Comparison of the effects of velocity-based vs. traditional resistance training methods on adaptations in strength, power, and sprint speed: A systematic review, meta-analysis, and quality of evidence appraisal
Published in Journal of Sports Sciences, 2022
Samuel T. Orange, Adam Hritz, Liam Pearson, Owen Jeffries, Thomas W. Jones, James Steele
We performed various sensitivity analyses on the main meta-analysis models to examine whether decisions made in the review process influenced the overall findings. Sensitivity analyses included: (1) computing test statistics and 95% CIs based on a normal (z) distribution rather than a t-distribution, (2) including quasi-experimental and crossover studies in the meta-analyses, and (3) using SDdiff to calculate effect estimates rather than the SD at baseline. We also examined meta-analyses for influential cases by calculating Cook’s distance and hat values (Viechtbauer & Cheung, 2010). Cook’s distance values of greater than or that values of more than were considered influential cases, where is the number of observations in the model. We then performed a Leave-One-Out sensitivity analysis to assess whether removing an individual effect estimate from a meta-analysis influenced the model parameters.