I have now reformatted the responses into a csv file. So you can do something boring like create a scatterplot with Excel, as above. Or, you can import into R and dig for more interesting patterns. Here is an updated to the PDF which shows you the simple non-crossed results.
Also, out of curiosity I separated respondents into geneticists vs. non-biologists (so I exclude biologists who are not geneticists from this analysis). First, here are the non-biologists on race:
A few weeks ago I mentioned that I wanted do another survey. I’ve done a fair number of reader surveys since the mid-2000s of my readership. So, for example, I know that you’re politically well balanced, except for social conservatives (who are very underrepresented). You are also extremely male, pale, well educated, atheistic, and prone to being virgins at a higher clip than your age might suggest. So I didn’t want to overload on demographic questions this time. Rather, I wanted to know about specific responses to specific controversial questions. So I titled it the “Brave New World Survey” this time, because of the focus on uncomfortable questions and the like.
Mostly, I’m tired of arguing with readers about what is, and isn’t, controversial. My readership has a lot of intellectual oddballs (probably because as an atheist brown conservative I am one). So I assume I’m sampling from the extreme end of the pool in terms of openness to heterodoxy, so we’ll see how it shakes out.
I haven’t used this survey software before, so take that as a warning. I put the survey as an iframe below the fold, but it didn’t work too well. So please go to the link here. It’s all one one page, so you should be able to complete it quickly (you can omit questions you want to omit).
When 100 responses come up, I’ll post a summary below the fold. I’ll do so with every hundred. Usually I make it to ~500 responses for this weblog. Also, I’ll try and figure out how to export it once I close the survey (personally information won’t be in the export, so don’t worry).
Update: If it didn’t work when you tried it earlier, try it now. I didn’t set it ‘live’ because I’m stupid.
A regular issue that comes up on this weblog is that many of my posts are difficult to understand. I am aware of this. Unfortunately a problem is that there is a wide variation in fluency in genetics knowledge among the readership. To get a better sense I have created a survey with 60+ questions. It may seem like a lot, but the questions go fast because there are only three answers to each, and you should immediately know how to respond. I will likely use these responses to guide me in future “refresher” posts and the like. The questions range from relatively simple to moderately abstruse. That’s by design. Thanks.
Note: The survey will not show up in the RSS, so please click through!
Just got this email, and I thought I would share with my readers:
I’m a biologist from Germany and together with 2 fellow biologists I’m currently working on a project that evaluates the sharing of raw data from DTC-genetic-testing companies like 23andme. I was genotyped myself and have already published the data set on GitHub and I there are other people who already did the same (i know the list of the SNPedia). But up to now these data sets are scattered all over the net and nearly none of them have attached phenotypic data.
What we are working on (and would like to see around) is a website that collects the genetic datasets as well as phenotypic data. This would make it much easier to find appropriate data and in the end – as long as there are enough users – it could become a resource for a kind of open source GWAS, similar to the idea behind the research 23andMe performs in it’s walled garden right now.
But publishing genetic and phenotypic data freely accessible on the net is still seldom seen and many people object the idea because of privacy concerns. We would like to know how many people in principle would like to participate in something like this and for what reasons they would like it (or not). So we created a small survey that asks those questions, which can be found at http://bit.ly/genotyping_survey
// Bastian Greshake
I’ll be honest that I’m a lot more sanguine about release my genotype than entering my endophenotypes and what not in a public place. Genotypes give you probabilistic understanding, which you can gain in other ways. A lot of morphology is visible, and so there’s no privacy. But it’s a lot dicier when people want you to share how often you’ve taken anti-depressants. I think we’ll get to the stage where there will be less stigma and transparency will be the norm, but we’re not there yet….
(the survey took me less than 2 minutes, for what it’ worth)
Heritability is a fraught topic. It comes up repeatedly on this weblog, but even long time readers can be confused as to its implications, as evidenced by the incorrect inferences made from their own understanding of the concept. The most common problem is that too often people think that heritability is just a scienced up version of the colloquial idea of some traits being “more genetic” or “less genetic.” It’s not that at all. Traits totally specified in their details by genetic pathways can be non-heritable. That’s because heritability looks at the association between parents and offspring on a trait and attempts to separate the population-wide proportion of the variation attributable to genes and not attributable to genes. When you have a genetically specified trait, like the number of human fingers, you have no real variation within the population to work with (with some rare exceptions). It doesn’t make sense to talk about the heritability of the number of fingers, because this is a fixed trait in the human species.
In contrast, height is a perfect trait to illustrate heritability. Unlike behavioral or cognitive traits its measurement is clear, distinct, and uncontroversial. Additionally, there’s a normal distribution of the trait. By that, I mean that there is a bell curve from tall to short, with a median at the peak of the distribution. Not only does height vary within the population, but it varies across populations, and it varies within families. When considering the heritability of height there’s a lot to grapple with and ponder for a relatively easy to measure characteristic.
Intuition will tell you that parents and offspring tend to correlate positively in terms of height, but the trait is imperfectly correlated. Comparisons between identical and fraternal twins can allow us to partition the rough effects of genes vs. non-genes on the trail value. Identical twins share ~100% of their genes, while fraternal twins share ~50% of their genes, so the correlation in trait value should diminish in proportion to the decreased genetic similarity and the effect of genes on the trait value. In plain language, if genes don’t account for any of the variation in the trait value then identical and fraternal twins should exhibit the same correlations on a trait. In contrast, if genes control almost all the variation on the trait value then identical twins should be rather close in value, while fraternal twins far less, because the twins in the second case differ a great deal genetically while they do not in the former case.
But even with a trait like height environment matters, more or less. Again, intuition tells you that if you starve a child during a critical period they may never attain their height as might be inferred from their genetic potential. Therefore heritability is informative in light of background conditions. In the developed world the heritability of height is ~0.80 to ~0.90, which means that 80-90% of the variation in height can be explained by variation in genes. This is not so in other regions of the world, where environmental variables such as nutritional stress loom larger. There is no fixed proportion by which height is “more genetic” or “more environmental.”
There’s much more that could be said. But much of it has been said, and by those better able to say more. So I’ll move to my value-add: what is the profile of those who know and don’t know what heritability is? In the survey I asked: “Do you know that narrow-sense heritability is the proportion of the phenotypic variance due to the additive genetic variance?” The terminology may seem opaque to some of you, but to those who knew what heritability was it wouldn’t be. ~33% of you out of ~550 (the survey is still live) recognized what narrow-sense heritability was by the definition I offered. I was frankly nicely surprised, since I know many of you skim for topics of particular interest to you rather than “deep dive” into quantitative genetics, which I don’t talk much about in depth in any case.
The results from the survey will be analyzed in three parts:
- In the first knowledge of heritability is a function of another variable. In other words below you a see table which shows that 34 percent of males recognized the definition of narrow-sense heritability and 29 percent of females did. The average is ~33 percent because 80 percent of respondents were male vs. 20 percent female. Remember that the proportion in the aggregate pool is ~33 percent.
- The second section focuses on the differences between people who know what narrow-sense heritability is, and those who do not. So in this case you have other factors as a function of heritability as a categorical variable.
- A final section examines some scatter plots of estimated height vs. IQ heritabilities. An interesting point to remember here is that many people who weren’t totally clear on what narrow-sense heritability was nevertheless offered up a heritability estimate, probably because they got the gist of what the value was.
I’ve been taking surveys of the readership of this weblog since 2004. Here is my last one, from the summer of 2010. Before I moved to Discover I also did one in the winter of 2010. Here’s a reader survey from the winter of 2009. Another from 2005.
I set up a survey with a new service this time. I did integrate some of the suggestions of commenters as well. One difference between this survey and previous ones is that I have a lot more free-form text boxes with numeric answers. So you give your specific age or income, instead of selecting from a category. The survey shouldn’t take more than ~5 minutes, as many of the questions are yes/no, or very simple, such as your highest education attained.
I’ll post the first results within 24 hours, and probably post the raw files at some point in the near future if you want to crunch them yourself. I set it up so it goes from banal demographic questions in the beginning to more detailed and somewhat esoteric queries by the end. None of the questions are mandatory.
Update: Might as well point you to the early results (the “open-ended” results aren’t there, I’ll have to format that for later).
So that reader survey that I mentioned last week is done. I’m mostly interested in seeing the changes since I’ve moved to Discover from ScienceBlogs. I assume that the standard 85% male readership has shifted somewhat toward more balance, but I don’t know. Many of the basic demographic questions (sex, race, age, etc.) are the same, but I swapped out ones I usually ask with others. At this point I’m rather sure that a huge proportion of the readers of this weblog are introverted nerds, so I’m not going to ask about personality type and what not. I took some reader suggestions, so there are questions about what you read, as well what your somatotype is. I converted the political question to a 0 to 10 scale that I wouldn’t have to recode if I did a scatter plot, and also so that it’s a little more fine-grained.
As usual all questions are optional. I timed it and should take you 5 minutes max, though I guess I can’t account for lack of clarity in prose. If you don’t see your exact response, but want to respond, I think it is totally fine to give the closest equivalent.
Below are percentage breakdowns of last winter’s survey by sex.
About six months ago I did a survey of the readership of my two Gene Expression blogs (before moving to Discover). The N was around 600. You can view the raw frequency results here. One of the issues which I was curious about: did the disciplinary background of readers have any major correlates with responses? So I created three categories from the data on disciplines:
Social science had its own section, but for science I amalgamated those who studies Math, Engineering, Natural Science and Medicine. The balance were under “Not science.”
Edmund Yong has rebooted the “Who are you?” meme. I’ll quote him:
So let’s do it again. In the comments below, tell me who you are, what your background is and what you do. What’s your interest in science and your involvement with it? How did you come to this blog, how long have you been reading, what do you think about it, and how could it be improved?
I will try and be a little less…abrasive…on this thread in relation to comments, so feel free to let your hair down and “de-lurk”
That being said, I do take surveys of my readership periodically, so here are some of the demographic breakdowns which I have from a survey I took last winter….