Acceptance and Understanding of Paul Hawkins Ideologies - amazonia.fiocruz.br

Just one: Acceptance and Understanding of Paul Hawkins Ideologies

Acceptance and Understanding of Paul Hawkins Ideologies Video

Correlation is never evidence for causation — but, unfortunately, many scientific articles imply that it is. While paying lip service to the correlation-causation mantra, some possibly many authors end up arguing that their data is evidence for an effect based solely on the correlations they observe.

This is one of the reasons for the replication crisis in science where contradictory results are being reported. Career prospects, institutional pressure and the need for public recognition will encourage scientists to publish poor quality work that they then use to claim that have found an effect. The problem is that the public, the news media and even many scientists simply do not properly scrutinise continue reading published papers.

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There is nothing wrong with doing statistical analyses and producing correlations. They can all get you into the BMJ and the Friday papers.

However, researchers will continue to publish correlations and make great claims for them because they face powerful incentives to promote even unreliable research results. Scientific culture and institutional pressures provide expectations demanding academic researchers produce publishable results. This pressure is so great they will often clutch at straws to produce correlations even when the initial statistical analyst produces none. These days epidemiological researchers use large databases and powerful statistical software in their search Axceptance correlations. Unfortunately, this leads to data mining which, by suitable selection of variables, makes the discovery of statistically significant correlations easy. The data mining approach also means that the often cite p-values are meaningless.

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Consider these correlations below — two data sets are taken from a published paper — the other four use random data provided by Jim Jones in his book Regression Analysis: An Intuitive Guide. You can probably guess which correlations were from real data J and M because there are so many more data points All of these have correlations low p values — but click the following article Acceptance and Understanding of Paul Hawkins Ideologies, those selected from random data sets resulted from data mining and the p-values are therefore meaningless because they are just a few of the many checked. The other two correlations are taken from Bashash et al They do not give details of how many other variables were checked in the dataset used but it is inevitable that some degree of data mining occurred.

So, again, the low p-values are probably meaningless. The paper has been heavily promoted by anti-fluoride scientists and activists. None of the promoters have made a critical, objective, analysis of the correlations reported. In an effort to make their correlations look better these authors imposed confidence intervals on the graphs see below. This Xkcd cartoon on curve fitting gives a cynical take on that. The grey areas in the graphs may impress some people but it does not hide the wide scatter of the data points.

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In fact, the estimated slopes in these graphs are meaningless when it comes to predictions. Correlations reported by Bashash et al The regressions explain very little of the variance in the data and connect be used to make meaningful predictions.

In critiquing the Bashash et al paper I must concede that at least they made their data available — the data points in the two figures. Unfortunately, many authors simply cite p-values and possible confidence intervals for the estimate of the regression coefficient without providing any data or images. This is frustrating for the intelligent scientific reader attempting to critically evaluate their claims. We should never forget that Ideoologies, no matter how impressive, do not mean causation. It is very poor science to suggest they do.

Nevertheless, many research resort to correlations they have managed to glean from databases, usually resorting to some extent of data mining, to claim they have found an effect and to get published. The drive to publish means that even very poor correlations get promoted and are used by ideologically or career-minded scientists, and source activists, to attempt to convince policymakers of their cause. Image credit: Xkcd — Correlation. You are commenting using your WordPress. You are commenting using your Google account. You are commenting using your Twitter account.]