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The Gelman View – spottedtoad
I have read Andrew Gelman’s blog for about five years, and gradually, I’ve decided that among his many blog posts and hundreds of academic articles, he is advancing a philosophy not just of statistics but of quantitative social science in general. Not a statistician myself, here is how I would articulate the Gelman View:

A. Purposes

1. The purpose of social statistics is to describe and understand variation in the world. The world is a complicated place, and we shouldn’t expect things to be simple.
2. The purpose of scientific publication is to allow for communication, dialogue, and critique, not to “certify” a specific finding as absolute truth.
3. The incentive structure of science needs to reward attempts to independently investigate, reproduce, and refute existing claims and observed patterns, not just to advance new hypotheses or support a particular research agenda.

B. Approach

1. Because the world is complicated, the most valuable statistical models for the world will generally be complicated. The result of statistical investigations will only rarely be to  give a stamp of truth on a specific effect or causal claim, but will generally show variation in effects and outcomes.
2. Whenever possible, the data, analytic approach, and methods should be made as transparent and replicable as possible, and should be fair game for anyone to examine, critique, or amend.
3. Social scientists should look to build upon a broad shared body of knowledge, not to “own” a particular intervention, theoretic framework, or technique. Such ownership creates incentive problems when the intervention, framework, or technique fail and the scientist is left trying to support a flawed structure.

Components

1. Measurement. How and what we measure is the first question, well before we decide on what the effects are or what is making that measurement change.
2. Sampling. Who we talk to or collect information from always matters, because we should always expect effects to depend on context.
3. Inference. While models should usually be complex, our inferential framework should be simple enough for anyone to follow along. And no p values.

He might disagree with all of this, or how it reflects his understanding of his own work. But I think it is a valuable guide to empirical work.
ratty  unaffiliated  summary  gelman  scitariat  philosophy  lens  stats  hypothesis-testing  science  meta:science  social-science  institutions  truth  is-ought  best-practices  data-science  info-dynamics  alt-inst  academia  empirical  evidence-based  checklists  strategy  epistemic 
november 2017 by nhaliday
Peer review is younger than you think - Marginal REVOLUTION
I’d like to see a detailed look at actual journal practices, but my personal sense is that editorial review was the norm until fairly recently, not review by a team of outside referees.  In 1956, for instance, the American Historical Review asked for only one submission copy, and it seems the same was true as late as 1970.  I doubt they made the photocopies themselves. Schmidt seems to suggest that the practices of government funders nudged the academic professions into more formal peer review with multiple referee reports.
econotariat  marginal-rev  commentary  data  gbooks  trends  anglo  language  zeitgeist  search  history  mostly-modern  science  meta:science  institutions  academia  publishing  trivia  cocktail  links 
september 2017 by nhaliday
No, science’s reproducibility problem is not limited to psychology - The Washington Post
But now then: Are psychology experiments more likely than, say, chemistry experiments or physics experiments to have issues with reproducibility? Ioannidis told me yes, probably so.

“I think on average physics and chemistry would do better. I don’t know how much better," he said.

Maybe someone should try to constrain the differences between the physical sciences and the social sciences. Perhaps physics and chemistry will do their own version of the reproducibility study?
news  org:rec  ioannidis  replication  science  meta:science  social-science  psychology  social-psych 
september 2017 by nhaliday
Of mice and men: why animal trial results don’t always translate to humans
It showed that of the most-cited animal studies in prestigious scientific journals, such as Nature and Cell, only 37% were replicated in subsequent human randomised trials and 18% were contradicted in human trials. It is safe to assume that less-cited animal studies in lesser journals would have an even lower strike rate.
news  org:mag  org:edu  science  meta:science  medicine  meta:medicine  model-organism  human-study  homo-hetero  data  pro-rata  org:nat  replication  methodology 
september 2017 by nhaliday
All models are wrong - Wikipedia
Box repeated the aphorism in a paper that was published in the proceedings of a 1978 statistics workshop.[2] The paper contains a section entitled "All models are wrong but some are useful". The section is copied below.

Now it would be very remarkable if any system existing in the real world could be exactly represented by any simple model. However, cunningly chosen parsimonious models often do provide remarkably useful approximations. For example, the law PV = RT relating pressure P, volume V and temperature T of an "ideal" gas via a constant R is not exactly true for any real gas, but it frequently provides a useful approximation and furthermore its structure is informative since it springs from a physical view of the behavior of gas molecules.

For such a model there is no need to ask the question "Is the model true?". If "truth" is to be the "whole truth" the answer must be "No". The only question of interest is "Is the model illuminating and useful?".
thinking  metabuch  metameta  map-territory  models  accuracy  wire-guided  truth  philosophy  stats  data-science  methodology  lens  wiki  reference  complex-systems  occam  parsimony  science  nibble  hi-order-bits  info-dynamics  the-trenches  meta:science  physics  fluid  thermo  stat-mech  applicability-prereqs  theory-practice 
august 2017 by nhaliday
Fear and Loathing in Psychology - The Unz Review
Warne and Astle looked at 29 best-selling undergraduate textbooks, which is where psychology students learn about intelligence, because less than 10% of graduate courses offer an intelligence option.

3.3% of textbook space is dedicated to intelligence. Given its influence, this is not very much.

The most common topics start well, with IQ and Spearman’s g, but do not go on to the best validated, evidence-led Cattell-Horn-Carol meta-analytic summary, but a side-stream, speculative triarchic theory from Sternberg; and a highly speculative and non-specific sketch of an idea about multiple intelligences Gardner. The last is a particular puzzle, since it really is a whimsical notion that motor skill is no different from analytical problem solving. All must have prizes.
Commonly, environmental influences are discussed, genetic ones rarely.

What Do Undergraduates Learn About Human Intelligence? An Analysis of Introductory Psychology Textbooks: https://drive.google.com/file/d/0B3c4TxciNeJZOTl3clpiX0JKckk/view

Education or Indoctrination? The Accuracy of Introductory Psychology Textbooks in Covering Controversial Topics and Urban Legends About Psychology: http://sci-hub.la/https://link.springer.com/article/10.1007/s12144-016-9539-7

Twenty-four leading introductory psychology textbooks were surveyed for their coverage of a number of controversial topics (e.g., media violence, narcissism epidemic, multiple intelligences) and scientific urban legends (e.g., Kitty Genovese, Mozart Effect) for their factual accuracy. Results indicated numerous errors of factual reporting across textbooks, particularly related to failing to inform students of the controversial nature of some research fields and repeating some scientific urban legends as if true. Recommendations are made for improving the accuracy of introductory textbooks.

Mapping the scale of the narcissism epidemic: Increases in narcissism 2002–2007 within ethnic groups: https://www.sciencedirect.com/science/article/pii/S0092656608000949

The increasing numbers of Asian-Americans at the UCs over time may have masked changes in narcissism, as Asian-Americans score lower on the NPI. When examined within ethnic groups, Trzesniewski et al.’s data show that NPI scores increased significantly between 2002 and 2007 at twice the rate of the yearly change found over 24 years in Twenge et al. (2008a). The overall means also show a significant increase 2002–2007. Thus the available evidence suggests that college students are endorsing progressively more narcissistic personality traits over the generations.

Birth Cohort Increases in Narcissistic Personality Traits Among American College Students, 1982–2009: http://journals.sagepub.com/doi/abs/10.1177/1948550609355719

Both studies demonstrate significant increases in narcissism over time (Study 1 d = .37, 1982–2008, when campus is controlled; Study 2 d = .37, 1994–2009). These results support a generational differences model of individual personality traits reflecting changes in culture.

could this just be a selection effect (more people attending)?
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july 2017 by nhaliday
National hiring experiments reveal 2:1 faculty preference for women on STEM tenure track
Here we report five hiring experiments in which faculty evaluated hypothetical female and male applicants, using systematically varied profiles disguising identical scholarship, for assistant professorships in biology, engineering, economics, and psychology. Contrary to prevailing assumptions, men and women faculty members from all four fields preferred female applicants 2:1 over identically qualified males with matching lifestyles (single, married, divorced), with the exception of male economists, who showed no gender preference. Comparing different lifestyles revealed that women preferred divorced mothers to married fathers and that men preferred mothers who took parental leaves to mothers who did not.

Double-blind review favours increased representation of female authors: http://www.sciencedirect.com/science/article/pii/S0169534707002704
Double-blind peer review, in which neither author nor reviewer identity are revealed, is rarely practised in ecology or evolution journals. However, in 2001, double-blind review was introduced by the journal Behavioral Ecology. Following this policy change, there was a significant increase in female first-authored papers, a pattern not observed in a very similar journal that provides reviewers with author information. No negative effects could be identified, suggesting that double-blind review should be considered by other journals.

Teaching accreditation exams reveal grading biases favor women in male-dominated disciplines in France: http://science.sciencemag.org/content/353/6298/474
This bias turns from 3 to 5 percentile ranks for men in literature and foreign languages to about 10 percentile ranks for women in math, physics, or philosophy.
study  org:nat  science  meta:science  gender  discrimination  career  progression  planning  long-term  values  academia  field-study  null-result  effect-size  🎓  multi  publishing  intervention  biases 
july 2017 by nhaliday
Alzheimers | West Hunter
Some disease syndromes almost have to be caused by pathogens – for example, any with a fitness impact (prevalence x fitness reduction) > 2% or so, too big to be caused by mutational pressure. I don’t think that this is the case for AD: it hits so late in life that the fitness impact is minimal. However, that hardly means that it can’t be caused by a pathogen or pathogens – a big fraction of all disease syndromes are, including many that strike in old age. That possibility is always worth checking out, not least because infectious diseases are generally easier to prevent and/or treat.

There is new work that strongly suggests that pathogens are the root cause. It appears that the amyloid is an antimicrobial peptide. amyloid-beta binds to invading microbes and then surrounds and entraps them. ‘When researchers injected Salmonella into mice’s hippocampi, a brain area damaged in Alzheimer’s, A-beta quickly sprang into action. It swarmed the bugs and formed aggregates called fibrils and plaques. “Overnight you see the plaques throughout the hippocampus where the bugs were, and then in each single plaque is a single bacterium,” Tanzi says. ‘

obesity and pathogens: https://westhunt.wordpress.com/2016/05/29/alzheimers/#comment-79757
not sure about this guy, but interesting: https://westhunt.wordpress.com/2016/05/29/alzheimers/#comment-79748
http://perfecthealthdiet.com/2010/06/is-alzheimer%E2%80%99s-caused-by-a-bacterial-infection-of-the-brain/

https://westhunt.wordpress.com/2016/12/13/the-twelfth-battle-of-the-isonzo/
All too often we see large, long-lasting research efforts that never produce, never achieve their goal.

For example, the amyloid hypothesis [accumulation of amyloid-beta oligomers is the cause of Alzheimers] has been dominant for more than 20 years, and has driven development of something like 15 drugs. None of them have worked. At the same time the well-known increased risk from APOe4 has been almost entirely ignored, even though it ought to be a clue to the cause.

In general, when a research effort has been spinning its wheels for a generation or more, shouldn’t we try something different? We could at least try putting a fraction of those research dollars into alternative approaches that have not yet failed repeatedly.

Mostly this applies to research efforts that at least wish they were science. ‘educational research’ is in a special class, and I hardly know what to recommend. Most of the remedial actions that occur to me violate one or more of the Geneva conventions.

APOe4 related to lymphatic system: https://en.wikipedia.org/wiki/Apolipoprotein_E

https://westhunt.wordpress.com/2012/03/06/spontaneous-generation/#comment-2236
Look,if I could find out the sort of places that I usually misplace my keys – if I did, which I don’t – I could find the keys more easily the next time I lose them. If you find out that practitioners of a given field are not very competent, it marks that field as a likely place to look for relatively easy discovery. Thus medicine is a promising field, because on the whole doctors are not terribly good investigators. For example, none of the drugs developed for Alzheimers have worked at all, which suggests that our ideas on the causation of Alzheimers are likely wrong. Which suggests that it may (repeat may) be possible to make good progress on Alzheimers, either by an entirely empirical approach, which is way underrated nowadays, or by dumping the current explanation, finding a better one, and applying it.

You could start by looking at basic notions of field X and asking yourself: How do we really know that? Is there serious statistical evidence? Does that notion even accord with basic theory? This sort of checking is entirely possible. In most of the social sciences, we don’t, there isn’t, and it doesn’t.

Hygiene and the world distribution of Alzheimer’s disease: Epidemiological evidence for a relationship between microbial environment and age-adjusted disease burden: https://academic.oup.com/emph/article/2013/1/173/1861845/Hygiene-and-the-world-distribution-of-Alzheimer-s

Amyloid-β peptide protects against microbial infection in mouse and worm models of Alzheimer’s disease: http://stm.sciencemag.org/content/8/340/340ra72

Fungus, the bogeyman: http://www.economist.com/news/science-and-technology/21676754-curious-result-hints-possibility-dementia-caused-fungal
Fungus and dementia
paper: http://www.nature.com/articles/srep15015
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july 2017 by nhaliday

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