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Potential limitations such as missing data in a subset of studies could be overcome using imputation methods that account for clustering. Furthermore, Bayesian approaches facilitate sensitivity analyses through adjusting prior specification, and permit the the robustness of fitted models to be evaluated. This is particularly useful when few studies are available and estimated parameters of one- and two-stage models may be severely biased due to estimation difficulties. Future research is needed to evaluate the performance of the described methods, and to compare their accuracy and coverage with Bayesian alternatives.
I wondered if this was a reference to cryptocurrency. Contradictory. Reading about events in China, things often seem contradictory. For example, the South China Morning Post reported that when the government announced its last crackdown on the 4th of February, advertisements for cryptocurrency stopped appearing on Baidu and Weibo, Chinas biggest search engine and social media platform respectively. In other words, cryptocurrency was being actively advertised up until that point, despite most cryptocurrency-related activities being illegal since last year.
As for his tweaking, thats OK only if he tells us how and why, or gives original results as well, otherwise it just adds to the confusion. I have just ordered A-B and would be interested in any feedback from previous users as well as new users like me. Im using ADVFN to get my data (as recommended in the manual), and as Im not live trading, its all I should need for now. One is a Java generated graph and the other is an HTML graph. Im using ADVFN to get my data (as recommended in the manual), and as Im not live trading, its all I should need for now.