@article {808,
	title = {Ironing out the statistical wrinkles in "ten ironic rules".},
	journal = {Neuroimage},
	volume = {81},
	year = {2013},
	month = {2013 Nov 1},
	pages = {499-502},
	abstract = {<p>The article "Ten ironic rules for non-statistical reviewers" (Friston, 2012) shares some commonly heard frustrations about the peer-review process that all researchers can identify with. Though we found the article amusing, we have some concerns about its description of a number of statistical issues. In this commentary we address these issues, as well as the premise of the article.</p>},
	keywords = {Neuroimaging, Peer Review, Research, Research Design, Statistics as Topic},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2013.02.056},
	author = {Lindquist, Martin A and Caffo, Brian and Crainiceanu, Ciprian}
}
@article {803,
	title = {Quantifying the reliability of image replication studies: the image intraclass correlation coefficient (I2C2).},
	journal = {Cogn Affect Behav Neurosci},
	volume = {13},
	year = {2013},
	month = {2013 Dec},
	pages = {714-24},
	abstract = {<p>This article proposes the image intraclass correlation (I2C2) coefficient as a global measure of reliability for imaging studies. The I2C2 generalizes the classic intraclass correlation (ICC) coefficient to the case when the data of interest are images, thereby providing a measure that is both intuitive and convenient. Drawing a connection with classical measurement error models for replication experiments, the I2C2 can be computed quickly, even in high-dimensional imaging studies. A nonparametric bootstrap procedure is introduced to quantify the variability of the I2C2 estimator. Furthermore, a Monte Carlo permutation is utilized to test reproducibility versus a zero I2C2, representing complete lack of reproducibility. Methodologies are applied to three replication studies arising from different brain imaging modalities and settings: regional analysis of volumes in normalized space imaging for characterizing brain morphology, seed-voxel brain activation maps based on resting-state functional magnetic resonance imaging (fMRI), and fractional anisotropy in an area surrounding the corpus callosum via diffusion tensor imaging. Notably, resting-state fMRI brain activation maps are found to have low reliability, ranging from .2 to .4. Software and data are available to provide easy access to the proposed methods.</p>},
	keywords = {Adult, Brain, brain mapping, Computer Simulation, Female, Humans, Male, Models, Biological, Neuroimaging, Reproducibility of Results, Statistics as Topic},
	issn = {1531-135X},
	doi = {10.3758/s13415-013-0196-0},
	author = {Shou, H and Eloyan, A and Lee, S and Zipunnikov, V and Crainiceanu, A N and Nebel, N B and Caffo, B and Lindquist, M A and Crainiceanu, C M}
}
