Posts Tagged ‘why0mg’

Low-density parity-check code – Wikipedia

February 17, 2020

https://en.wikipedia.org/wiki/Low-density_parity-check_code

turbo codes

QT:{{”
2G cell phones used “soft decoding” (i.e., probabilities) but not belief propagation. 3G cell phones used Berrou’s turbo codes, and 4G phones used Gallager’s turbo-like codes.
“}}
[from book!]

Paternity Index – Wikipedia

February 16, 2020

https://en.wikipedia.org/wiki/Paternity_Index

Hidden Data and Surviving a Sinking Ship: Simpson’s Paradox – Select Statistical Consultants

April 26, 2019

https://select-statistics.co.uk/blog/hidden-data-and-surviving-a-sinking-ship-simpsons-paradox/

continuous version of the paradox

Genetic susceptibility to lung cancer and co-morbidities

April 26, 2019

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804872/

QT:[[”
Genome-wide association studies (GWAS) have enabled significant progress in the past 5 years in investigating genetic susceptibility to lung cancer. Large scale, multi-cohort GWAS of mainly Caucasian, smoking, populations have identified strong associations for lung cancer mapped to chromosomal regions 15q [nicotinic acetylcholine receptor (nAChR) subunits: CHRNA3, CHRNA5], 5p (TERT-CLPTM1L locus) and 6p (BAT3-MSH5). Some studies in Asian populations of smokers have found similar risk loci, whereas GWAS in never smoking Asian females have identified associations in other chromosomal regions, e.g., 3q (TP63), that are distinct from smoking-related lung cancer risk loci. GWAS of smoking behaviour have identified risk loci for smoking quantity at 15q (similar genes to lung cancer susceptibility: CHRNA3, CHRNA5) and 19q (CYP2A6).
“]]

Monty Hall problem – Wikipedia

April 26, 2019

https://en.wikipedia.org/wiki/Monty_Hall_problem

collider bias

Policy-relevant proportions for direct effects

March 31, 2019

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3523303/

discusses NDE & NIE

A Decade of GWAS Results in Lung Cancer | Cancer Epidemiology, Biomarkers & Prevention

March 31, 2019

http://cebp.aacrjournals.org/content/27/4/363.long

QT:[[”
The first GWAS on lung cancer were reported in 2008. Three independent studies identified a susceptibility locus on chromosome 15q. Hung and colleagues (14) found two SNPs strongly associated with lung cancer on chromosome 15q25. Further genotyping in this region revealed many SNPs in tight linkage disequilibrium (LD) showing evidence of association. Six genes are located in this region including three nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, and CHRNB4). Interestingly, no appreciable variation in the risk was found across smoking categories or histologic subtypes of lung cancer. In a second GWAS, a SNP within the CHRNA3gene was strongly associated with smoking quantity and nicotine dependence (15). The same SNP was also strongly associated with lung cancer. The results suggest that the variant on chromosome 15q25 confers risk of lung cancer through its effect on tobacco addiction.
“]]

Equivalence of the Mediation, Confounding and Suppression Effect

March 31, 2019

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2819361/

Mediation (statistics) – Wikipedia

March 31, 2019

Cites the classic paper:

Baron, R. M. and Kenny, D. A. (1986) “The Moderator-Mediator Variable Distinction in Social Psychological Research – Conceptual, Strategic, and Statistical Considerations”, Journal of Personality and Social Psychology, Vol. 51(6), pp. 1173–1182.

https://en.wikipedia.org/wiki/Mediation_(statistics)

Introduction to Mediation Analysis | University of Virginia Library Research Data Services + Sciences

March 31, 2019

https://data.library.virginia.edu/introduction-to-mediation-analysis/

QT:[[”
To analyze mediation:
1. Follow Baron & Kenny’s steps
2. Use either the Sobel test or bootstrapping for significance testing. “]]