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.

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Convenience sample

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.

Immortal Time Bias

What the hell is an Immortal Time Bias?

 

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:

841.full

492.full

13u_asn08_immortal_time_bias

 

Evaluation of Scientific Publications

Image via Wikipedia

In his blog named “OH-world” John Cherrie from Edinburgh, United Kingdom, signaled us an interesting series of seventeen articles freely available in full text on PubMedCentral. The first of the series is entitled Critical Appraisal of Scientific Articles; Part 1 of a Series on Evaluation of Scientific Publications.

The title of the following ones are listed below:

1. Critical Appraisal of Scientific Articles

2. Study Design in Medical Research

3. Types of Study in Medical Research

4. Confidence Interval or P-Value?

5. Requirements and Assessment of Laboratory Tests: Inpatient Admission Screening

6. Systematic Literature Reviews and Meta-Analyses

7. The Specification of Statistical Measures and Their Presentation in Tables and Graphs

8. Avoiding Bias in Observational Studies

9. Interpreting Results in 2×2 Tables

10. Judging a Plethora of p-Values: How to Contend With the Problem of Multiple Testing

11. Data Analysis of Epidemiological Studies

12. Choosing statistical tests

13. Sample size calculation in clinical trials

14. Linear regression analysis

15. Survival analysis

16. Concordance analysis

17. Randomized controlled trials

An other way to be able to evaluate a scientific article in medicine is to read the fourteen articles constituting the Clinical Chemistry Guide to Scientific Writing. The first article is entitled The Title Says It All.
The following articles are listed below:
Part 1. The Title Says It All

Part 2. The Abstract and the Elevator Talk: A Tale of Two Summaries

Part 3. “It was a cold and rainy night”: Set the Scene with a Good Introduction

Part 4. Who, What, When, Where, How, and Why: The Ingredients in the Recipe for a Successful Methods Section

Part 5. Show Your Cards: The Results Section and the Poker Game

Part 6. If an IRDAM Journal Is What You Choose, Then Sequential Results Are What You Use

Part 7. Put Your Best Figure Forward: Line Graphs and Scattergrams

Part 8. Bars and Pies Make Better Desserts than Figures

Part 9. Bring Your Best to the Table

Part 10. The Discussion Section: Your Closing Argument

Part 11. Giving Credit: Citations and References

Part 12. How to Write a Rave Review

Part 13. Top 10 Tips for Responding to Reviewer and Editor Comments

Part 14. Passing the Paternité Test

We thank Hervé Maisonneuve for having signaled this Guide in his blog.

Alma Consulting Group analyses the absenteeism

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.

methods of the study

http://www.laprovence.com/article/a-la-une/tire-au-flanc-les-provencaux

The Hygie database

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

cross over intervention study by Céline

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

why subgroup analyses may be misleading

50 tests and one p<0,05   SIGNIFICANT !!!!

but subgoup analyses warrants a high degree of scepticism,

see why:  http://xkcd.com/882/

how to classify your environmental variables

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)

2) http://www.ined.fr/

add systematic review to your tool box

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:

http://jech.bmj.com/content/65/1/14.full