Random effect (A) and fix effect (B) pooled ORs for the dominant model.YaFeng, LiXiaoMing, ZhuFan, LiuChuanShi, XiaoYunFei, BianHong, LiJun, CaiRongShan, LiXinChun, Yang
The null model algorithm results heavily depend on the selection of the regional pool, within which randomization is implemented54. Thus, the algorithms randomizing taxa within each bin and across all bins were compared in iCAMP analysis for the simulated communities. No matter whether the ...
Whereas the BCR is a stochastic process, the deterministic aspects of the 5 statistics were tested with an increasing number of steps\(n_s\). The statistic associated with each realization of the model (a simulated path) is a random variable. If the distribution of these random variables has...
Robustly well-predicted metabolites.ATop 20 robustly well-predicted metabolites. Diamonds’ centers represent the random-effects model’s estimated mean effect size (mean predictability) and diamonds’ widths represent the mean’s 95% confidence interval. The numbers in square brackets represent the numbe...
V. (2023). Asymmetric effects of oil price shocks on EUR/USD exchange rate and structural shock decomposition in a BVAR model with sign restriction Appendix B. Supplementary data【数据+Matlab】 Bruns, S. B., et al. (2021). Estimating the economy-wide rebound effect using empirically ...
This is functionally equivalent to performing a paired t test (time with larger shoal versus time with smaller shoal), albeit with the inclusion of random effects. Here, the model contained the full complement of random effects outlined above (minus the random slope of time) but with a single...
Model development of networks Here, four different networks are modeled. Two of the networks belong to non-real world and two are from real-world: random and lattice, small-world and scale-free networks. Next, these network models are described. ...
exchanges, and stock, markets based on a heterogeneous market hypothesis and macroeconomic theory. They constructed a hybrid gray prediction model for fluctuations using a random walk model to conduct a multi-step prediction of the price of crude oil by combining a gray prediction model for ...
(I2 ≥ 30%), we used the DerSimonian and Laird method43,44for a random-effects model45. Funnel plots, which graph RR/OR on a log scale (effect) against standard error of log-RR/OR (precision), were generated and visually inspected for asymmetry to determine whether the included ...
Similar results were also found by conducting the meta-regression with the random effects model (Table 1). In an additional sensitivity analysis where we excluded those data sources for which we could not confirm that all flocks were kept exclusively indoors (multi-tier: HEE_15, NOR_18, VST_...