A person-in-context approach to student engagement in science (article in JRST)

Over the past few years, I have worked with Jennifer Schmidt and Patrick Beymer to explore student engagement in science using the Experience Sampling Method (ESM). Most recently, we used what scholars have referred to as a “person-in-context” approach, using both ESM and a person-oriented approach. A figure is helpful for conveying how the person-oriented approach can be used to …

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Using MPlus from R with MPlusAutomation

According to the MPlus website, the R package MPlusAutomation serves three purposes: Creating related groups of models Running batches Extracting and tabulating model parameters and test statistics. Because modeling involves comparing related models, (partially) automating these is compelling. It can make it easier to use model results in subsequent analyses and can cut down on copy and pasting …

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Epistemic Caution and Climate Change

I have not, until recently, invested significant time in trying to understand climate modeling. These notes are primarily for my own use, however I welcome comments from readers who have studied this issue in more depth. I take a dim view of people who express strong opinions about complex phenomena without having understood the underlying …

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prcr update

The R package for person-oriented analysis (prcr) is updated (it’s now version 0.1.4). In particular, it was not clear how to use the profile assignments (i.e., what cluster each response is in) in subsequent analyses. So, the update now returns two different representations of the profile assignments, or which profile is associated with each observation: …

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History of Bayesian Neural Networks

This talk gives the history of neural networks in the framework of Bayesian inference. Deep learning is (so far) quite empirical in nature: things work, but we lack a good theoretical framework for understanding why or even how. The Bayesian approach offers some progress in these directions, and also toward quantifying prediction uncertainty. I was …

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Announcing clustRcompaR v.0.1.0

Announcing clustRcompaR v.0.1.0 Alex Lishinski and I worked on an R package over the last year or so. We are excited that it’s now available on CRAN. You can install the package using install.packages(‘clustRcompaR’) (only needed first time) and load it (more on its two functions below) using library(clustRcompaR). Here’s a description: Provides an interface …

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Can Life emerge spontaneously?

It would be nice if we knew where we came from. Sure, Darwin’s insight that we are the product of an ongoing process that creates new and meaningful solutions to surviving in complex and unpredictable environments is great and all. But it requires three sine qua non ingredients: inheritance, variation, and differential selection. Three does …

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Speed, Balding, et al.: “for a wide range of traits, common SNPs tag a greater fraction of causal variation than is currently appreciated”

I recently blogged about a nice lecture by David Balding at the 2015 MLPM (Machine Learning for Personalized Medicine) Summer School: Machine Learning for Personalized Medicine: Heritability-based models for prediction of complex traits. In that talk he discussed some results concerning heritability estimation and potential improvements over GCTA. A new preprint on bioRxiv has the …

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Some R Resources

(Should I have spelled the last word in the title “ResouRces” or “resouRces”? The R community has a bit of a fascination about capitalizing the letter “r” as often as possible.) Anyway, getting down to business, I thought I’d post links to a few resources related to the R statistical language/system/ecology that I think may …

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Machine Learning for Personalized Medicine: Heritability-based models for prediction of complex traits (David Balding)

Highly recommended talk by David Balding on modern approaches to heritability, relatedness, etc. in statistical genetics. (I listened at 1.5x normal speed, which worked for me.) MLPM (Machine Learning for Personalized Medicine) Summer School 2015 Monday 21st of September Heritability-based models for prediction of complex traits by David Balding Complex trait genetics has been revolutionised …

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Over- and Underfitting

I just read a nice post by Jean-François Puget, suitable for readers not terribly familiar with the subject, on overfitting in machine learning. I was going to leave a comment mentioning a couple of things, and then decided that with minimal padding I could make it long enough to be a blog post. I agree …

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$1.2 trillion college loan bubble?

See also When everyone goes to college: a lesson from S. Korea. Returns to a “college education” are highly dependent on the intrinsic cognitive ability and work ethic of the individual. WSJ: College Loan Glut Worries Policy Makers The U.S. government over the last 15 years made a trillion-dollar investment to improve the nation’s workforce, …

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University quality and global rankings

University quality and global rankings The paper below is one of the best I’ve seen on university rankings. Yes, there is a univariate factor one might characterize as “university quality” that correlates across multiple measures. As I have long suspected, the THE (Times Higher Education) and QS rankings, which are partially survey/reputation based, are biased …

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Coin Flipping

I don’t recall the details, but in a group conversation recently someone brought up the fact that if you flip a fair coin repeatedly until you encounter a particular pattern, the expected number of tosses needed to get HH is greater than the expected number to get HT (H and T denoting head and tail …

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Genetic ancestry and brain morphology

Population structure — i.e., distribution of gene variants by ancestral group — is reflected in brain morphology, as measured using MRI. Brain morphology measurements can be used to predict ancestry. Strictly speaking, the data only show correlation, not genetic causation, but the most plausible interpretation is that genetic differences are causing morphological differences. One could …

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GCTA, Missing Heritability, and All That

Bioinformaticist E. Stovner asked about a recent PNAS paper which is critical of GCTA. My comments are below. It’s a shame that we don’t have a better online platform (e.g., like Quora or StackOverflow) for discussing scientific papers. This would allow the authors of a paper to communicate directly with interested readers, immediately after the paper …

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On Statistics, Reporting and Bacon

I’ve previously ranted about the need for a “journalistic analytics” college major, to help with reporting (and editing) news containing statistical analysis. Today I read an otherwise well written article that inadvertently demonstrates how easy it is for even seasoned reporters to slip up. The cover story of the November 9 issue of Time magazine, …

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David Donoho interview at HKUST

A long interview with Stanford professor David Donoho (academic web page) at the IAS at HKUST. Donoho was a pioneer in thinking about sparsity in high dimensional statistical problems. The motivation for this came from real world problems in geosciences (oil exploration), encountered in Texas when he was still a student. Geophysicists were using Compressed …

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