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Estimation statistics is a data analysis framework that uses a combination of effect sizes, confidence intervals, precision planning and meta-analysis to plan experiments, analyze data and interpret results.〔(【引用サイトリンク】first=Paul )〕 It is distinct from null hypothesis significance testing (NHST), which is considered to be less informative.〔(【引用サイトリンク】first=Jacob )〕〔 Estimation statistics, or simply estimation, is also known as the new statistics,〔 a distinction introduced in the fields of psychology, medical research, life sciences and a wide range of other experimental sciences where NHST still remains prevalent,〔 despite estimation statistics having been recommended as preferable for several decades. The primary aim of estimation methods is to estimate the size of an effect and report an effect size along with its confidence intervals, the latter of which is related to the precision of the estimate.〔 Estimation at its core involves analyzing data to obtain a point estimate (an effect size calculated from data used as estimate of the population effect size) and an interval estimate that summarizes a range of likely values of the underlying population effect. Proponents of estimation see reporting a p-value as either a secondary task or an unhelpful distraction from the important business of reporting an effect size with its confidence intervals. ==History== Physics has for long employed a weighted averages method that is similar to meta-analysis. Estimation statistics in the modern era started with the development of the standardized effect size by Jacob Cohen in the 1960s. Research synthesis using estimation statistics was pioneered by Gene V. Glass with the development of the method of meta-analysis in the 1970s. Estimation methods have been refined since by Larry Hedges, Michael Borenstein, Doug Altman, Martin Gardner, Geoff Cumming and others. The systematic review, in conjunction with meta-analysis, is a related technique with widespread use in medical research. There are now over 60,000 citations to "meta-analysis" in PubMed. Despite the widespread adoption of meta-analysis, the estimation framework is still not routinely used in primary biomedical research. In the 1990s, editor (Kenneth Rothman ) banned the use of p-values from the journal Epidemiology; compliance was high among authors but this did not substantially change their analytical thinking.〔(【引用サイトリンク】first=Fiona )〕 More recently, estimation methods are being adopted in fields such as neuroscience and psychology.〔(【引用サイトリンク】first=Geoff )〕 The Publication Manual of the American Psychological Association recommends estimation over hypothesis testing.〔(【引用サイトリンク】url=http://www.apastyle.org/manual/index.aspx )〕 The Uniform Requirements for Manuscripts Submitted to Biomedical Journals document makes a similar recommendation: "Avoid relying solely on statistical hypothesis testing, such as P values, which fail to convey important information about effect size."〔(【引用サイトリンク】url=http://www.icmje.org/manuscript_1prepare.html )〕 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「estimation statistics」の詳細全文を読む スポンサード リンク
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