SUMMARY / RELATED TOPICS

Meta-analysis

A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analysis can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error; the aim is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. Existing methods for meta-analysis yield a weighted average from the results of the individual studies, what differs is the manner in which these weights are allocated and the manner in which the uncertainty is computed around the point estimate thus generated. In addition to providing an estimate of the unknown common truth, meta-analysis has the capacity to contrast results from different studies and identify patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies.

A key benefit of this approach is the aggregation of information leading to a higher statistical power and more robust point estimate than is possible from the measure derived from any individual study. However, in performing a meta-analysis, an investigator must make choices which can affect the results, including deciding how to search for studies, selecting studies based on a set of objective criteria, dealing with incomplete data, analyzing the data, accounting for or choosing not to account for publication bias. Judgment calls made in completing a meta-analysis may affect the results. For example and colleagues examined four pairs of meta-analyses on the four topics of job performance and satisfaction relationship, realistic job previews, correlates of role conflict and ambiguity, the job satisfaction and absenteeism relationship, illustrated how various judgement calls made by the researchers produced different results. Meta-analyses are but not always, important components of a systematic review procedure.

For instance, a meta-analysis may be conducted on several clinical trials of a medical treatment, in an effort to obtain a better understanding of how well the treatment works. Here it is convenient to follow the terminology used by the Cochrane Collaboration, use "meta-analysis" to refer to statistical methods of combining evidence, leaving other aspects of'research synthesis' or'evidence synthesis', such as combining information from qualitative studies, for the more general context of systematic reviews. A meta-analysis is a secondary source; the historical roots of meta-analysis can be traced back to 17th century studies of astronomy, while a paper published in 1904 by the statistician Karl Pearson in the British Medical Journal which collated data from several studies of typhoid inoculation is seen as the first time a meta-analytic approach was used to aggregate the outcomes of multiple clinical studies. The first meta-analysis of all conceptually identical experiments concerning a particular research issue, conducted by independent researchers, has been identified as the 1940 book-length publication Extrasensory Perception After Sixty Years, authored by Duke University psychologists J. G. Pratt, J. B.

Rhine, associates. This encompassed a review of 145 reports on ESP experiments published from 1882 to 1939, included an estimate of the influence of unpublished papers on the overall effect. Although meta-analysis is used in epidemiology and evidence-based medicine today, a meta-analysis of a medical treatment was not published until 1955. In the 1970s, more sophisticated analytical techniques were introduced in educational research, starting with the work of Gene V. Glass, Frank L. Schmidt and John E. Hunter; the term "meta-analysis" was coined in 1976 by the statistician Gene V. Glass, who stated "my major interest is in what we have come to call...the meta-analysis of research. The term is a bit grand, but it is precise and apt... Meta-analysis refers to the analysis of analyses". Although this led to him being recognized as the modern founder of the method, the methodology behind what he termed "meta-analysis" predates his work by several decades; the statistical theory surrounding meta-analysis was advanced by the work of Nambury S. Raju, Larry V. Hedges, Harris Cooper, Ingram Olkin, John E. Hunter, Jacob Cohen, Thomas C.

Chalmers, Robert Rosenthal, Frank L. Schmidt, Douglas G. Bonett. Conceptually, a meta-analysis uses a statistical approach to combine the results from multiple studies in an effort to increase power, improve estimates of the size of the effect and/or to resolve uncertainty when reports disagree. A meta-analysis is a statistical overview of the results from one or more systematic reviews, it produces a weighted average of the included study results and this approach has several advantages: Results can be generalized to a larger population The precision and accuracy of estimates can be improved as more data is used. This, in turn, may increase the statistical power to detect an effect Inconsistency of results across studies can be quantified and analyzed. For instance, inconsistency may arise from sampling error, or study results influenced by differences between study protocols Hypothesis testing can be applied on summary estimates Moderators can be included to explain variation between studies The presence of publication bias can be investigated A meta-analysis is preceded by a systematic review, as this allows identification and critical appraisal of all the relevant evidence.

The general steps are as follows: Formulation of the research question, e.g. using the PICO model (Population, I

Serguei Kouchnerov

Serguei Kouchnerov - artist, director, story artist and screenwriter. He started his career as an director in Kiev, Ukraine. In 1992, he was hired by Walt Disney Feature Animation as a character animator and came to the United States of America, where he lives and works at Illumination Entertainment. Serguei Kouchnerov worked for Kyivnaukfilm Studio in Kyiv, Ukraine on the animated feature film Treasure Island and on many other animated short films; when in the United States he worked for Walt Disney Feature Animation on Fantasia 2000 before joining DreamWorks Animation for such animated feature films as The Prince of Egypt, The Road to El Dorado, Shrek 2, Bee Movie, Over the Hedge, Madagascar 2. One of his current works; as Director The Hybrid Union The Log A Vicious Circle, Hopeless Wombat As Supervising animator / Character animator Madagascar 2 - DreamWorks Animation Bee Movie - DreamWorks Animation Over the Hedge - DreamWorks Animation Madagascar - DreamWorks Animation Shrek 2 - DreamWorks Animation Sinbad: Legend of the Seven Seas - DreamWorks Animation Spirit: Stallion of the Cimarron - DreamWorks Animation The Road to El Dorado - DreamWorks Animation The Prince of Egypt - DreamWorks Animation Fantasia 2000 - Walt Disney Animation The Lion King - Walt Disney Animation Treasure Island - Kievnauchfilm Kiev, Ukraine As Storyboard Artist Sinbad: Legend of the Seven Seas - DreamWorks Animation Bob's Burgers - As Story Artist Chicken Run - DreamWorks Animation / Aardman Official website Serguei Kouchnerov at the Internet Movie Database Serguei Kouchnerov at Hollywood.com at Archive.today

Glorious: The Singles 97–07

Glorious: The Singles 97–07 is a compilation album by Australian singer-songwriter Natalie Imbruglia, celebrating ten years since the release of her first album, Left of the Middle. It was released on 10 September 2007 on 22 September 2007 in Australia; the album consists of all nine singles released from Imbruglia's past three studio albums as well as five new songs including the single "Glorious". A limited edition version includes a bonus DVD of Imbruglia's music videos; the album peaked at number 5 on the UK Albums Chart. It was certified Gold in the UK on 12 October 2007; the lead single "Glorious" was digitally released in the United States on 26 June 2012, but the album itself has yet to receive a release in the country. ^ signifies a co-producer