Frontiers in Massive Data Analysis, from the National Research Council, nails some of the challenges of big data. But the challenges for massive data go beyond
via Big data challenges.
Frontiers in Massive Data Analysis, from the National Research Council, nails some of the challenges of big data. But the challenges for massive data go beyond
via Big data challenges.
Convenience samples allow the researchers to easily have a first approach of what happens in a given population. But researcher has always to keep in mind that such a sampling method in addition of being easy is also always exposed to bias. Once a first approach have been made, it is mandatory that the results obtained by mean of a convenience sample be confirmed with a random sample or a clustered sample or a stratified sample. The two YouTube videos here bellows are indeed very helpful to apprehend the concept.
The appellation is very poetic indeed. What is hidden behind?
I searched on the internet and found three papers which unveiled the mystery.
An immortal time bias occurs when individuals of one of the two groups that are compared (e.g.treated patients and control patients) are guaranteed for one period (called immortal time) to be alive if the outcome of interest is all cause mortality (or not to incur the condition of interest if the outcome is a disease). The period of immortal time must be situated after the cohort entry and before the end point (i.e. during the follow up time).
For example if date of birth is the date of cohort entry and death is the outcome of interest, Popes or Oscar Winners live longer than others. The explanation of this life time discrepancy is only the immortal time bias. You have to be alive long enough (and thus not to die) to become Pope or to win Oscars!
Below are the full text of the three papers I found on the internet treating of the immortal time bias scope:
Alma Consulting Group is a consultant which implement expertises for cost reduction in the private enterprises. Its social department measured the average number of lost days from work for disease in the french private enterprises across industry sectors and geographical areas . Health sector workers presents two fold more days away from work than the construction sector workers. South counts more days away from work in average than north of France. The causes are the ageing of workers and reduction of staff. These data concern the public and private sector. Because data on absenteeism in the public sector are not easily available until now in France this study is relevant.
http://www.laprovence.com/article/a-la-une/tire-au-flanc-les-provencaux
The Hygie database links a health care insurance fund database with a retirement insurance fund database, both databases being the property of the national french mandatory general scheme for the salaried workers. This aims to produce studies comparing diseases across industry sectors for salaried workers in activity or retired.
http://www.irdes.fr/EspaceRecherche/Partenariats/Hygie/Presentation.html
a paper writen by Mohamed Ali Ben Halima (IRDES) – Thierry Debrand (IRDES) and Camille Regaert (IRDES) using the Hygie database:
http://www.ces-asso.org/docs/textes_JESF_2010/BenAlima_debrand_2010.pdf
An example of cross over intervention study: when Semelweiss exchanged medical students for midwives in two maternity services of Vienna Hospital the exceeding puerperal fever mortality rates followed the students (who have made dissections of corpses a few time before and didn’t wash their hands). A great epidemiology study 50 years before Pasteur. Semelweiss published his article “aetiology of puerperal fever” in 1861 which is considered as the seminal work for antiseptie.
But his colleagues rejected his findings making thousands of unnecessary death of young womens across Europe with terrible sufferings. The remorse of being rejected and the sorrow of staying powerless facing his coleagues’ rejection of his findings and ignorance caused the death from madness of Semelweiss in a asylum.
Céline wrote:”Nothing is free here on earth. Everything must be punished in return, the good actions as the evil ones, sooner or later. In case of good action the punishment is more severe necessarily”
A very great book, all health services searchers should read:
http://www.atlaspress.co.uk/index.cgi?action=view_eclectic&number=9
http://www.compulsivereader.com/html/index.php?name=News&file=article&sid=2443
50 tests and one p<0,05 SIGNIFICANT !!!!
but subgoup analyses warrants a high degree of scepticism,
see why: http://xkcd.com/882/
These are two web sites very useful if you want to classify or encode environmental variables such as living territories, department of residence, density of health professionals, rate of unemployment, rate of chronic disease, income per inhabitant and so on:
1) http://www.sirsepaca.org/index.php (datas availables only for the region Provence-Alpes-Côte d’Azur)
For public health researchers sytematic reviews are increasingly used to evaluate the efficacy of public health policy interventions. On an other hand searchers are encouraged more and more to conduct a sytematic review before embarking on primary research. A pragmatic method is demonstrated below to conduct a systematic review in a shorter and a smarter way: