This question has been inspired by current events, namely the Covid-19 pandemic and, ermm... let's graciously call them &quot;vaccine skeptics&quot;. Also of note is that I'm not a medical scientist or even in any way connected to medicine, so my knowledge can be waaaay off. I feel like I have a rough, general understanding of the process required to bring a new drug to market. You first come up with the substance, then you try it in a petri dish and/or animal models, then you gather evidence that it does no harm, then you gather evidence that it does bring benefits, and along the way you also gather data on the exact efficiency, side effects, etc. Now, all this research is almost always done and funded by private pharmaceutical businesses. It's all very expensive so the companies are very interested in shining results of the tests so that they can sell lots of the new drug. This has on occasion lead to foul play, but I gather that most of the time these results are pretty trustworthy. So my question is - what makes them trustworthy? I understand that the research gets both peer review and government oversight (so we have neutral and/or competing third parties looking over their shoulder), but how do you check that the reported results are actually the same as observed in the field? In general, what steps are taken to make cheating in this research difficult?
120475
This question comes off the back of an answer to  where there was reference to a retraction of an article in The Lancet based on inaccuracies and fraudulent data. As a lot of research (if not all) are funded by interested parties such as pharmaceutical companies, the legal profession, etc. I was wondering if there are any articles released which has results in opposite to the best interest of the funding organisation(s)?  involves using Vagus Nerve Stimulation (VNS) to treat difficult-to-treat depression (DTD).  Due to the amount of research with conflicts of interest concerning manufacturer(s) of VNS equipment, it is hard if not impossible to find any research completely free of the possible influence the manufacturer(s) have had so far. Here I am looking for any examples which will show that there is medical research which is completely impartial and not necessarily just the example here.
7639
I am interested in the situation where you have a very interesting result. For instance, you have solved a very important open problem. However, you are not known in the field and do not have any remarkable publications. Your supervisor thinks the work is good and you submit the work to a high profile journal, but you get rejected.  The thing is that the contribution is very strong. It breaks what most people believe or what they have already proven: e.g., you solve the P vs. NP problem or any other well known open problem.   The reviewers strongly reject your work with no justification and they do not state why the result is wrong. Examples of reviewer comments include:   "The proof must be wrong."  "You cannot achieve such a result."  "You do not understand well the notion of ..."   My question is what to do in this situation? Where to go? If your advisor accepts the work, but the reviewers from the top journal reject the work without even explaining the mistakes,  what should you do?
70970
I have developed a method to process images I use for my research. It's nothing revolutionary but I think it might be useful to others than me, and why not, be worthy of being published somewhere (at least for me to cite when I use it).   As it is outside my primary field of research, nobody in my direct lab vicinity can help evaluating its scientific value or novelty (I did a bit of literature research and didn't find any obvious precedent). Normally I would just put it as an appendix in the first article where I use it, but this one is quite long to describe and completely out of my field. It would thus be off-topic in the journals in which I usually publish.  I though of seeking collaboration from someone in my university who works in signal/image processing, I don't know anyone personally and I foresee possible political issues, authorship quarrels, etc. I would nonetheless like to get some sort of evaluation before submitting to a journal. As an outsider, I wouldn't like to waste an editor's time and make a fool of myself.  I have zero experience submitting to the arXiv, by looking at the website it's not clear how/if there is an active system of feedback, even informal.   Is it advisable to submit my methods paper there and expect a feedback?
11665
I am new to research and I have yet to internalize the concept of journals and their utility in archiving scientific literature.  Almost all the papers I have read recently are from this website called . Arxiv calls itself to be a preprint archive. Anyone can upload a PDF file to the repository and it counts as a valid research. Large companies like Google and Facebook post all their research here. The research is peer reviewed, It does not have the tyranny of a fixed format and the publishing is instantaneous unlike journals which are painfully slow. It is also open access and unlike open access journals it does not cost a fortune to publish a paper.  My question is, why were journals used to begin with? Why are they used now?   I have heard some people say that if a paper is not published in a  journal then it does not have any value. Then why are so many people publishing here? As far as I know citations from arxiv are picked up by google scholar.   EDIT: Ok, so the entire system is a huge mess.
50402
I've got a study which is kinda messed up by the design...Turns out I ended up with about 50 patients of which 80% have the outcome and 20% don't (binary outcome).  I've been turning in my bed for the last month trying to figure out what to do with this. The only real answer is "don't" but I have to deliver something in the next days as it's part of a master's thesis.  I have about 10 predictors of interest for the outcome (various variable types) and the research question is whether any of these predictors can predict the outcome. Some already have an established correlation in the literature while some are original hypothesis. Several are significant with a univariate logistic regression, but it doesn't look good in any other way than the actual p-value.  Now obviously I'm not going to be able to answer this research question sufficiently but if you were in my shoes, what sort of statistical analysis would you perform to relay to your supervisors?  EDIT: Link to my (anonymized) data (CSV):
115782
I have conducted experiment that had unexpected result which goes against  consensus in my community and I worry whether it will be accepted by other researchers. For that reason I would like to make all my work public - the resources, the programs, the results.. Is there online service where I can publish the data for free and obtain DOI number that I can reference in my paper?  It makes over 2GB when packed.  I have heard that such services exist for people in biology and medical research but I work on transportation systems which is rather different (we do not produce so much data usually). I plan to submit the paper to journal published by IEEE.
79404
When planning a trip, I like to make sure I will feel safe enough (I am talking about war/terrorism risk, not pickpockets), or at least I like to have an idea about the risks. I know the risk could be subject to political views (for example the political stability of a region might not be acknowledged by every country) and therefore I am mostly interested in a Western country view.  In order to figure that, I thought about checking travel operators offers. I suppose if they do not organise trips to a specific region, it might be due to political instability risks. But it might be due to a lack of tourist interest too. As I tend to travel without their help, I am not really considering this kind of source as very helpful.  So I am interested in one (or two, for cross-checking) source(s) of information with a western view (I mean I understand the view could be biased) regarding the security of ideally any area in the world. My expectation is that, the same way I can browse a tour operator's catalog of visited areas, I could browse through the areas and see if it is recommended or not to travel there.
79144
We have witnessed (heard or read) about the birth of new academic journals many times. I have a vague idea how that happens:   A scientist or a group of scientists recognize the need for an academic journal in a specific field or a new scientific society considers to publish a journal,  they choose a group of experts as founders and/or chief editors,  they determine a scope and some basic rules for the journal,  they decide about the number of issues in each year and similar things,  they find a publisher or decide to publish the journal entirely on web, they establish a web site for the journal,  and then they announce the new journal in the related scientific community.    Did I miss any stage? But I suspect there are lots of discussions, negotiations, arrangements and cooperations behind the curtain, which public (the rest of the related scientific community) doesn't know. So my questions are:   What is a typical procedure for establishing a respectful academic journal?  Do financial considerations play a key role?  Should the founders be top experts (to some degree) in the field?  Is it important the new journal be affiliated to a scientific society or be published by a recognized publisher?  Why are some new journals published only on-line?   What are the influential factors for the success of a new journal?  How do the founders choose the editors?  What else should one consider for initiating a new academic journal?   Please share your partial answers too if you don't have all the answers.  Disclaimer: I am just curious and I don't intend to initiate any new journals in the near future.;)
32002
First of all, this is about plagiarism in the sense of stealing ideas. Copy-and-paste plagiarism is included but not likely to happen in the cases relevant for this question.  Considering the publication of a paper prior to peer-reviewed publication on the ArXiv (or another preprint server), there are usually two main positions considering a possible theft of the idea (or somebody coming up with the same idea):   If somebody manages to publish your idea in a peer-reviewed journal before you do, you can prove that you came up with the idea first or at least independently if you have published your paper on the ArXiv. Therefore it is a good idea to publish papers on the ArXiv before they have been published in a peer-reviewed journal. If you publish your paper on ArXiv before it is published in a peer-reviewed journal, others may steal your work and publish it peer-reviewed before you do and thus take the scientific credit. It’s difficult to attack those people since the ArXiv is not peer-reviewed. Somebody could make a living of plagiarising ArXiv papers. Therefore it is a bad idea to publish papers on the ArXiv before they have been published in a peer-reviewed journal.   Are there any example cases (or even studies) supporting either of these statements? Such examples would include, but are not limited to:   Has a peer-reviewed journal ever withdrawn a paper because it plagiarised an ArXiv paper? Are there well-known cases of “unpunished” plagiarism of ArXiv papers?  Has anybody ever successfully resolved a priority dispute with a publication on ArXiv? Has anybody ever accused somebody of plagiarising an ArXiv article (with the fact that the plagiarised article was published on ArXiv affecting the outcome).   Note that it is really examples and not a theoretical analysis of the statements, I am looking for. (Neither of the two positions fully reflect my opinion and some of the soft premises¹ are debatable. However, debating about these viewpoints on a theoretical basis or attacking some of the premises is usually futile.)     ¹ e.g., that scientific credit is only decided by peer-reviewed publication
99507
Does it make sense to compute confidence intervals and to test hypotheses when data from the whole population is available? In my opinion, the answer is no, since we can accurately compute the true values of the parameters. But then, what is the maximal proportion of data from the original population that allows us to use the aforementioned techniques?
80403
I have been reading a lot on Cross Validated for a while now, but this is my first post here. Thanks for all the help I've received! I am currently working on a project where we are trying to estimate the effects of a drug on overall and disease-specific mortality. This is a prospective observational study, where patients are enrolled when they have a blood test, which happens at different time points. Patients are then followed until death, emigration, or the end of the study. To figure out if the drug impacts mortality, we have set up a Cox regression model where drug exposure is allowed to accumulate over time with the cumtdc function specified . The problem is that the proportional hazards assumption is severely violated - with p-values approaching 0 for most of the covariates. I am a beginner to this type of analysis and what I have read and tried so far is:  Splitting continuous variables (such as age) into categories, which did not make a difference. Could interaction variables be helpful here - if so, how do I best implement them? Would this analysis be better suited to be performed with an accelerated failure time model? Is it possible that the analysis could be valid despite the non-proportional hazards? I am asking this since, intuitively, there are many individuals in the study (&gt; 300 000) and many events (&gt; 30 000), so even minimal violations might be registered as significant.  I am attaching the Schoenfeld plots with the respective p-values for the covariables.  I would be most appreciative of any suggestions to this problem. There seem to be many different approaches out there, making it a bit tricky to navigate for a beginner. Thank you! ADDITON TO ORGINAL QUESTION These are the log hazards for the variables age and X. I have now attempted both restricted cubic splines and categorization without meaningful changes to the Schoenfeld residuals.  ADDITION 2 TO ORIGINAL QUESTION The output from cox.zph:  The requested plots from cox.zph for A and age:
51960
I am currently submitting a paper for Nature Structural &amp; Molecular Biology. I worked on this project for the last four years and was the only one working on this project. I had everything going very well. In order to get the crystallization, I gave the plasmid construct to another laboratory which has expertise in crystallization. Fortunately, they got the crystals. After the crystallization got successful, one researcher (say, A) from their lab came to my lab and my professor told me to teach him all the methods. I happily agreed to do so. After A went back to his lab, I got the draft of the paper from my professor, where, my name appeared as first co-author! I almost fainted. There were 20 figures in the paper. 13 were contributed by me, 4 by A and rest by 2 other people. The paper was mostly about my work. But in the contribution section, my prof and the prof of A  mentioned that I and A had equal contribution. In fact it is mentioned that A was solely contributor of crystals and he equally contributed in all other results. I discussed this issue with my prof, but he tells that he is getting pressure from A's prof to make A the first author. And my prof does not want to estrange relationship with A's prof. I am heart-broken and I don't know what to do. Please suggest me what to do. Edit 2021: It has been quite some time since I posted this question. I accepted the authorship as recommended by my advisor. Now I feel mature and realize that maintaining a cordial relationship with one's advisor and colleagues is more important than anything else. If one is capable enough, s/he will get more opportunities to prove their worth.
91250
I am six years into a business role and have a bachelor's in physics and applied math/stats. Sean Carroll's (Caltech physicist)  opened me to the idea that Bayesian statistics is one useful way of thinking about anything - inevitably you hold a prior and you should update your credence as additional information becomes available.   Is there a path to training your intuition to thinking this way? Critically, it would require repeated practice with verifiable answers through either a course, or self study that includes many problems and solutions. I do not believe simply reading will do.  Possible resources, having read every related question on this site I could find:   "Probability Theory" by Jaynes. Pro: analytic; intuitive explanation of bayesian statistics. Con: prerequisites; missing problems/solutions. "Doing Bayesian Data Analysis" by Kruschke. Pro: includes problems &amp; solutions; requires only "algebra and rusty calculus". Con: works in R, which I think provides for less intuitive learning than the analytical (I may be wrong).   If it is a multi-year path I need to take, starting elsewhere, I am happy to do so! Ideally, I would avoid the frequentist methods, as I have no use for them.  My goal is not to be a scientist, but to leverage insight into how reality works to go above and beyond the established thinking in business.  Many thanks for any suggestions!
109644
Please go through the following incidents to understand the problem.  Mr. A is a Ph.D. student of some institute who was working with Prof. B of another institute on a very interesting mathematical problem since last three years. Recently, they came across a significant solution to it. They wrote a research article to publish in a very good mathematics journal that accepts the online submission.  Prof. B wanted to submit it to the journal by himself. Mr. A agreed.   A few days ago, Mr. A wanted to know about the submission of their article via telephone. Prof. B informed that the article is submitted. But, Mr. A received any confirmation e-mail neither from the journal nor Prof. B forwarded the submission mail to him. Prof. B did not upload it in arXiv, which is a free preprint repository.  Mathematics journals used to take a long duration to review and publish an article. Prof. B told that submitting this article to arXiv will immediately attract community attention. Many researchers will start working in the new direction. As a result, Mr. A and Prof. B may lose their opportunity to work on that problems. Also, the article may be stolen.  Mr. A did not ask Prof. B to forward the submission confirmation mail to him. Prof. might think that Mr. A is suspecting him. It may affect the relationship. Also, Prof. is a very powerful person in the administration, who may prevent an opportunity for Mr. A to gain a job. Again from some of his friends, Mr. A came to know that Prof. had distributed related research problems to his collaborators.  As a consequence, Mr. A is thinking that Prof. has submitted this work in his own name and he has lost his credit as the first author of this article.  Now the question is: How Mr. A may save his credit and his work without hampering his relationship with Prof B?
82325
I have to test the difference between two samples which were selected via stratified randomization. The problem is that the samples are not independent due to randomization was stratified.  How should I conduct the test?      Edit:    There are 80 patients. They were strafified by weight into four groups, each containing 20 observations. There are 4 treatments A,B,C,D. 5 patients from each group were randomly assigned to each of the four treatments.  The question is how to compare these treatments?    Weight is known to be the most important factor influencing the desease. The researcher tries to "adjust for weight", i.e., to provide "balance" of weights among the treatments.  The problem in comparing treatments for each weight separately is that we will then have only 5 observations per group.
104993
I am a nontraditional applicant for medical school and wanted to ask questions about my application here. I was previously enrolled in another MD program. I had an undiagnosed disability that resulted in some abnormal behavior, including research misconduct (data fabrication). It led to me withdrawing from medical school program, but I have spent several years recovering. I have finished a PhD. I have published many papers including a few at top journals (Cell) since then. I maintain a strong interest in academic medicine and I am ready to take another go at it. How might my application be processed differently? How successful could an applicant like myself be? Do you have advice on how I can present myself in the best manner? Do I have a chance?
53689
I'm an undergraduate statistics student looking for a good treatment of clinical trials analysis. The text should cover the fundamentals of experimental design, blocking, power analysis, latin squares design, and cluster randomization designs, among other topics.   I have an undergraduate knowledge of mathematical statistics and real analysis, but if there's a fantastic text that requires a bit higher level of statistics or analysis, I can work up to it.