April 10, 2014
Block diagonal R-structures in MCMCglmm

A new feature in MCMCglmm version 2.18 is block diagonal residual structures.

Block Diagonal R-structures are now allowed. For example imagine a bivariate model where pairs of observations are made on individuals of different sex. There may be a need to fit different 2x2 residual covariance matrices for the two sexes. rcov=~us(trait:sex):units would fit a 4x4 covariance matrix, but the between-sex residual covariances would be estimated despite not being identifiable (no individual can be both sexes). Now, models of the form rcov=~us(trait:at(sex, "M")):units+us(trait:at(sex, "F")):units can be fitted that allow the non-identified covariances to be effectively set to zero.

In other words, previously if you had 2 traits measured for females and males and you wanted to fit a sex specific residual with rcov=~us(trait:sex):units you would end up with a residual matrix like

for the variances (V) and covariances (cov) of females traits f1 and f2 and male traits m1 and m2. The bold components are estimable from the data while the red ones are not. However, because of the way the residual is set up MCMCglmm will try to estimate the red parameters as well.

With block diagonals, you are specifying a matrix like

where the gray cells are now ignored. This is accomplished by fitting two 2 × 2 matrices for the R structure then having separate terms in the rcov formula

March 27, 2014

"Tits of the World" Poster Process.

(via notrare)

March 26, 2014
Shrout & Fleiss’s ICC in mixed model form

Shrout & Fleiss give guidelines for calculating intraclass correlation coefficients for estimating interrater reliability and agreement. The original paper shows how to calculate them using ANOVA but they can also be estimated in a mixed model framework. Noting these down so I remember them

1. "Repeatability"
$y = a + e$
$ICC(1, k) = \frac{\sigma_a^2}{\sigma_a^2 + \frac{\sigma_e^2}{k}}$
2. "Agreement"
$y = a + r + \epsilon$
$ICC(2, k) = \frac{\sigma_a^2}{\sigma_a^2 + \frac{\sigma_r^2 + \sigma_\epsilon^2}{k}}$
3. "Consistency"
$y = a + r + \epsilon$
$ICC(3, k) = \frac{\sigma_a^2}{\sigma_a^2 + \frac{\sigma_\epsilon^2}{k}}$

March 7, 2014

Good book.

(Source: bbww, via unfinished-photography)

February 24, 2014

via Fat Birds

February 17, 2014

February 13, 2014
"Every speciality changes its classification of illnesses every few years, as we learn more about illnesses, but only psychiatry gets abuse for doing so."
February 6, 2014

Having done some research recently on collies, I like this.

(Source: scancity)

February 5, 2014
"Think of overfitting as memorizing as opposed to learning."

— James Faghmous , New to Machine Learning? Avoid these three mistakes

January 25, 2014
"Practically no experimental work has been done upon individual differences and family resemblances in animal behavior. In most cases the behaviorist has been content to study the mass reaction of a group of animals to external stimuli, and in the main, has not attempted to treat the variability of his group because of the relatively small number of animals tested."

— Halsey Bagg, 1920, Archives of Genetics Mono. Vol 43, p.1 (via Rosalind Arden)

2:46pm  |   URL: http://tmblr.co/Z23PQy15O3-iG
Filed under: genetics variation
January 24, 2014

Jose Vazquez
The tower and the park

The Arts Tower and Western Bank Library at the University of Sheffield.

January 23, 2014

"Hurrah then for confusion and mystery in medicine."

A mesmeric physician taking advantage of his female patient. Colour lithograph, 1852
Wellcome Images L0034922

January 21, 2014
"…the shy-animal mental model of experimentation. The effect is there; you just need to create the right circumstances to coax it out of its hiding place."
January 18, 2014

Never Trust Passerine Nomenclature by Albertonykus via @hylopsar.

January 15, 2014

March 25, 1984 — see The Complete Peanuts 1983-1986