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author=Gwern;
description=Miscellaneous statistical stuff;
keywords=cs/haskell, cs/js, cs/r, genetics, iq, statistics/bayes, statistics/causality, statistics/decision, statistics/order, statistics/power-analysis, survey;

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of, power, the, for, analysis, on, data, with, value, and, in, statistical, critiques, test, dealing, bayesian, model, unreliability, variables, student, mean, samples, human, risk, learning, are, not, expected, large, deer, cost, benefit, binomial, population, notes, someone, should, do, something, wishlist, miscellaneous, project, ideas, estimating, censored, scores, traveling, gerontologist, problem, bayes, nets, genome, sequencing, costs, proposal, hand, counting, mobile, app, more, fluid, group, discussions, air, conditioner, replacement, some, ways, measurement, error, information, clinical, prediction, instruments, suicide, averaging, all, or, nothing, dysgenics, racial, admixture, studies, continuous, operating, an, aneurysm, twins, revisiting, scottish, milk, experiment, example, rnn, metadata, mimicking, individual, author, style, mcts, candy, japan, defries, fulker, inferring, iqs, from, smpy, tip, elite, genius, revisited, high, iq, elementary, schools, great, scott, personal, name, collisions, birthday, paradox, detecting, fake, markov, chain, bots, optimal, existential, reduction, investment, criticism, via, machine, proportion, important, thinkers, by, global, region, over, time, charles, murray, accomplishment, program, non, spaced, repetition, review, past, written, materials, serendipity, rediscovery, archive, revisiter, new, methods, probability, exact, replication, expectations, deviations, number, oh, could, evolve, to, avoid, car, accidents, evolution, as, backstop, reinforcement, acne, good, quantified, self, topic, fermi, calculations, selective, emigration, personality, trait, change, most, abandoned, books, goodreads, best, ever, little, law, wild, tail, collapse, backlinks, similar, links, bibliography, failed, facebook, correlation, causation, cancer, research, aerobic, vs, weightlifting, moxibustion, mouse, study, daily, weight, graph, zeo, sleep, parameters, sensitivity, selection, snps, mutation, load, weaknesses, genetic, availability, sibling, adoption, loss, founder, effects, see, also, discounting, binary, proprietary, public, european, ancestry, standard, deviation, simulation, qaly, daly, adjustment, abc, mixture, weakening, heuristic,

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Text of the page (random words):
t available criteria for causal inference however there is no information on how the criteria should be weighed and they cannot be combined into one probability estimate for causality our objective is to provide an empirical basis for weighing the bradford hill criteria and to develop a transparent method to estimate the probability for causality study design and setting all 159 agents classified by international agency for research of cancer as category 1 or 2a carcinogens were evaluated by applying the nine bradford hill criteria discriminant analysis was used to estimate the weights for each of the nine bradford hill criteria results the discriminant analysis yielded weights for the nine causality criteria these weights were used to combine the nine criteria into one overall assessment of the probability that an association is causal the criteria strength consistency of the association and experimental evidence were the three criteria with the largest impact the model correctly predicted 130 of the 159 81 8 agents conclusion the proposed approach enables using the bradford hill criteria in a quantitative manner resulting in a probability estimate of the probability that an association is causal sounds reasonable right take this iarc database presumably of carcinogens known to be such by randomized experiment and see how well the correlate studies predict after training with lda you might not want to build a regular linear model because those tend to be weak and not too great at prediction rather than inference it s not clear what they did to prevent overfitting but reading through something else strikes me the iarc has evaluated the carcinogenicity of a substantial number of chemicals mixtures and exposure circumstances these evaluations have been carried out by expert interdisciplinary panels of scientists and have resulted in classification of these agents or exposure conditions into human carcinogens category 1 probable human carcinogens category 2a possible human carcinogens category 2b not classifiable agents category 3 and chemicals that are probably not carcinogenic to humans category 4 iarc 2006 20ya although the iarc working groups do not formally use the bradford hill criteria to draw causal inferences many of the criteria are mentioned in the individual reports for instance the preamble specifically mentions that the presence of a dose eresponse is an important consideration for causal inference in this analysis the iarc database serves as the reference database although we recognize that it may contain some disputable classifications however to our knowledge there is no other database containing causal inferences that were compiled by such a systematic process involving leading experts in the areas of toxicology and epidemiology wait these evaluations have been carried out by expert interdisciplinary panels of scientists and have resulted in classification of these agents or exposure conditions into human carcinogens evaluations have been carried out by expert interdisciplinary panels iarc working groups do not formally use the bradford hill criteria to draw causal inferences many of the criteria are mentioned wait so their database with causality non causality classifications is based on opinion they got some experts together and asked them and the experts use the same criterion which they are using to predict the classifications what so it s circular worse than circular randomization and causality never even enter the picture they re not doing causal inference nor are they giving an overall assessment of the probability that an association is causal and their conclusion the proposed approach enables using the bradford hill criteria in a quantitative manner resulting in a probability estimate of the probability that an association is causal certainly is not correct at best they are predicting expert opinion and maybe not even that well they have no idea how well they re predicting causality but wait maybe the authors aren t cretins or con artists and have a good justification for this approach so let s check out the discussion section where they discuss rcts using the results from randomized controlled clinical trials as the gold standard instead of the iarc database could have been an alternative approach for our analysis however this alternative approach has several disadvantages first only a selection of risk factors reported in the literature have been investigated by means of trials certainly not the occupational and environmental chemicals second there are instances in which randomized trials have yielded contradictory results for instance in case of several vitamin supplements and cancer outcomes you see randomized trials are bad because sometimes we haven t done them but we still really really want to make causal inferences so we ll just pretend we can do that and sometimes they disagree with each other and contradict what we epidemiologists have already proven while the experts iarc database never disagrees with themselves thank goodness we have official iarc doctrine to guide us in our confusion this must be one of the most brazen it s not a bug it s a feature moves i ve ever seen mon chapeau gerard ludovic mon chapeau incidentally google scholar says this paper has been cited at least 40 times looking at some it seem the citations are generally all positive these are the sort of people deciding what s a healthy diet and what substances are dangerous and what should be permitted or banned enjoy your dinners aerobic vs weightlifting aerobic vs weightlifting exercise claims multiple problems but primarily p hacking difference in statistical significance is not a significant difference and controlling for intermediate variable for example weightlifting enhances brain function reverses sarcopenia and lowers the death rate in cancer survivors take this last item lowering death rate in cancer survivors garden variety aerobic exercise had no effect on survival while resistance training lowered death rates by one third http roguehealthandfitness com case for weightlifting as anti aging paper in question the effect of resistance exercise on all cause mortality in cancer survivors hardee et al 2014 12ya https www ncbi nlm nih gov pmc articles pmc4126241 this is a bad study but sadly the problems are common to the field claiming that this study shows weight lifting lowered death rates and aerobic exercise did not change survival is making at least 4 errors correlation causation this is simply your usual correlation study you know of the sort which is always wrong in diet studies where you look at some health records and crank out some p values there should be no expectation that this will prove to be causally valid in particular reverse confounding is pretty obvious here and should remind people of the debate about weight and mortality ah but you say that the difference they found between aerobic and resistance shows that it s not confounding because health bias should operate equally well read on power with only 121 total deaths 4 of the sample this is inadequate to detect any differences but comically large correlates of health as the estimate of predicting a third less mortality indicates p hacking multiplicity type s errors exaggeration factor take a look at that 95 confidence interval for resistance exercise which is the only result they report in the abstract which is an hr of 0 45 0 99 in other words if the correlate were even the tiniest bit bigger it would no longer have the magical statistical significance at p 0 05 there s at least 16 covariates 2 stratifications and 3 full models tested that they report by the statistical significance filter a hr of 0 67 will be a serious exaggeration because only exaggerated estimates would just barely reach p 0 05 on this small dataset with only 121 deaths we can rule out a hr of 0 67 as credible simply on a priori grounds no exercise rct has ever shown reductions in all cause mortality remotely like that and that s the sort of reduction you just don t see outside of miracle drugs for lethal diseases for example aspirin and vitamin d have rrs of 0 95 the difference between significant and not significant is not itself statistically significant http www stat columbia edu gelman research published signif4 pdf the difference between aerobic exercise and resistance exercise is not statistically significant in this study the hr in model 1 for aerobic exercise is 0 63 1 32 and for aerobic exercise 0 46 0 99 that is the confidence intervals overlap specifically comparing the proportion of aerobic exercisers who died with the resistance exercisers who died i get prop test c 39 75 c 1251 1746 p 0 12 to compute a survival curve i would need more data i think the study itself does not anywhere seem to directly compare aerobic with resistance but always works in a stratified setting i don t know if they don t realize this point about the null hypotheses they re testing or if they did do the logrank test and it came out non statistically significant and they quietly dropped it from the paper the fallacy of controlling for intermediate variables in the models they fit they include as covariates body mass index current smoking yes or no heavy drinking yes or no hypertension present or not diabetes present or not hypercholesterolemia yes or no and parental history of cancer yes or no this makes no sense both resistance exercise and aerobic exercise will themselves influence bmi smoking status hypertension diabetes and hypercholesterolemia what does it mean to estimate the correlation of exercise with health which excludes all impact it has on your health through bmi blood pressure etc you might as well say controlling for muscle percentage and body fat we find weight lifting has no estimated benefits or controlling for education we find no benefits to iq or controlling for local infection rates we find no mortality benefits to public vaccination this makes the results particularly nonsensical for the aerobic estimates if you want to interpret them as direct causal estimates at most the hr estimates here are an estimate of weird indirect effects the remaining effect of exercise after removing all effects mediated by the covariates unfortunately structural equation models and bayesian networks are a lot harder to use and justify than just dumping a list of covariates into your survival analysis package so expect to see a lot more controlling for intermediate variables in the future the first three are sufficient to show you should not draw any strong conclusions the latter two are nasty and could be problematic but can be avoided these concerns are roughly ranked by importance 1 puts a low ceiling on how much confidence in causality we could ever derive a ceiling i informally put at 33 2 is important because it shows that very little of the sampling error has been overcoming 3 means we know the estimate is exaggerated 4 is not important because while that misinterpretation is tempting and the authors do nothing to stop the reader from making it there s still enough data in the paper that you can correct for it easily by doing your own proportion test 5 could be an important criticism if anyone was relying heavily on the estimate contaminated by the covariates but in this case the raw proportions of deaths is what yields the headlines so i bring this up to explain why we should ignore model 3 s estimate of aerobic exercise s rr 1 this sort of problem is why one should put more weight on meta analyses of rcts for example progressive resistance strength training for improving physical function in older adults https onlinelibrary wiley com enhanced doi 10 1002 14651858 cd002759 pub2 so to summarize this study collected the wrong kind of data for comparing mortality reduction from aerobics vs weightlifting insufficient mortality data to result in strong evidence exaggerates the result through p hacking did not actually compare aerobics and weightlifting head to head and the analysis s implicit assumptions would ignore much of any causal effects of aerobics weightlifting moxibustion mouse study http www eurekalert org pub_releases 2013 12 nrr pam120513 php pre moxibustion and moxibustion prevent alzheimer s disease http www sjzsyj org cn article downloadarticlefile do attachtype pdf id 754 i don t believe this for a second but actually this would be a nice followup to my previous email about the problems in animal research this paper exhibits all the problems mentioned and more let s do a little critique here this paper is chinese research performed in china by an all chinese team the current state of chinese research is bad it s really bad some reading on the topic https web archive org web 20131203150612 https www wired co uk news archive 2013 12 02 china academic scandal https newhumanist org uk 2365 lies damn lies and chinese science https news bbc co uk 2 hi 8448731 stm https gwern net doc statistics bias 2010 zhang pdf https www nytimes com 2010 16ya 10 07 world asia 07fraud html https news bbc co uk 1 hi world asia pacific 4755861 stm https news bbc co uk 2 hi asia pacific 8442147 stm https www nature com articles 463142a https www sciencenews org view generic id 330930 title traditional_chinese_medicine_big_questions https journals plos org plosone article id 10 1371 journal pone 0020185 https www npr org 2011 15ya 08 03 138937778 plagiarism plague hinders chinas scientific ambition i will note that there have been statistical anomalies in some of the chinese papers on dual n back training i have used in my meta analysis so i have some personal experience in the topic traditional medicine research is really bad no matter where you go they mention acupuncture as justification that s just fantastic https en wikipedia org wiki acupuncture punctures some of the hyperbolic claims the plos link above deals with the poor quality of the chinese reviews meta analyses in general and cochrane is not too kind to acupuncture https www thecochranelibrary com details collection 691705 acupuncture ancient tradition meets modern science html and in many of the reviews meta analyses there are stark geographic differences where the east asian studies turn in tons of positive results while the western studies somehow don t the lead author is not an ordinary neuroscientist or doctor but works at the college of acupuncture and moxibustion is he really going to publish a study concluding moxibustion does not affect alzheimer s really does this claim even make sense moxibustion really for those not familiar https en wikipedia org wiki moxibustion entails suppliers usually age the mugwort and grind it up to a fluff practitioners burn the fluff or process it further into a cigar shaped stick they can use it indirectly with acupuncture needles or burn it on the patient s skin how on earth is this supposed to help ad how does burning a plant on your skin affect plaques in your brain or if the...