Editing 2755: Effect Size

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A meta-analysis, true to its name, is a statistical analysis of statistical analyses, usually those attempting to answer a single question. Meta-analyses are intended to account for possible individual error within each study, summarizing the general results of all of its studies in order to potentially draw a useful conclusion. For a meta-analysis to be possible, there must be some measured variable in common across the included studies.
 
A meta-analysis, true to its name, is a statistical analysis of statistical analyses, usually those attempting to answer a single question. Meta-analyses are intended to account for possible individual error within each study, summarizing the general results of all of its studies in order to potentially draw a useful conclusion. For a meta-analysis to be possible, there must be some measured variable in common across the included studies.
  
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Here, the meta-analysis consists of a graph of {{w|effect sizes}} for what is allegedly every single study ever conducted. Accordingly, even page 53,589 of the meta-analysis is only about 1/4 of the total graph, as the scroll bar on the right is only about 1/4 of the way down; this makes the total included in the meta-analysis approximately 210,000 pages, or around 2.3 million studies. Below the graph is an estimate of the "average effect" across all of these variables, the effect normally being the relationship being analyzed by the studies within a meta-analysis, though here it seems again to be just a conglomerate of all known effects, along with a (likely) 95% {{w|confidence interval}} for the findings of the meta-analysis. It's absurd to analyze all studies this way, as the variables that all of those studies measure are wildly different and it makes no sense whatsoever to average (or otherwise analyze) them together. In addition, 2.3 million scientific studies is much too small a number; a [https://www.stm-assoc.org/about-stm/ recent estimate] is that about 3 million papers are published ''each year'', and while not all of them would have a numerical hypothesis test, many others would have several such tests.
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Here, the meta-analysis consists of a graph of {{w|effect sizes}} for what is allegedly every single study ever conducted. Accordingly, even page 53,589 of the meta-analysis is only about 1/4 of the total graph, as the scroll bar on the right is only about 1/4 of the way down; this makes the total included in the meta-analysis approximately 210,000 pages. Below the graph is an estimate of the "average effect" across all of these variables, the effect normally being the relationship being analyzed by the studies within a meta-analysis, though here it seems again to be just a conglomerate of all known effects, along with a (likely) 95% {{w|confidence interval}} for the findings of the meta-analysis. It's absurd to analyze all studies this way, as the variables that all of those studies measure are wildly different and it makes no sense whatsoever to average (or otherwise analyze) them together. [In addition, 210,000 scientific studies is much too small a number; a [https://www.stm-assoc.org/about-stm/ recent estimate] is that about 3 million papers are published ''each year'', and while not all of them would have a numerical hypothesis test, many others would have several such tests.]
  
 
Statistical studies are produced by generating hypotheses and then testing those hypotheses. A meta-analysis of all studies would therefore include both studies where the original hypothesis turns out to be false, as well as studies where the original hypothesis is confirmed. Hypotheses that fail to be confirmed by studies are often discarded; however, these studies would still be included in this meta-analysis.
 
Statistical studies are produced by generating hypotheses and then testing those hypotheses. A meta-analysis of all studies would therefore include both studies where the original hypothesis turns out to be false, as well as studies where the original hypothesis is confirmed. Hypotheses that fail to be confirmed by studies are often discarded; however, these studies would still be included in this meta-analysis.

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