Think I'll join in too as maybe it'll shame me into working a bit harder...

10 yesterday; 8 today.

Not shaping up to be the most productive week, but at least I'm getting some of the boring stuff done before I go on holiday next month. :-)

It's something you'd want to know, sure, but I'd never leave a review of my supervisors - there would be no anonymity, especially if your supervisor is at an early stage of their career and hasn't supervised many students yet. I imagine if everyone in my lab wrote even a short paragraph about my sup, I would quite easily be able to tell who wrote what - and so would my supervisor.

Even on this forum, I think a lot of people come dangerously close to compromising their anonymity. They don't state their names of course, but the information they provide about themselves make them easily identifiable to their supervisor, if they ever checked the site.

I agree with this. Does it mean what words do you associate with health? Or pick three words from the above paragraph?

I work with neuroimaging and I have to say a lot of post docs I've seen advertised want someone who already has some experience in analysing this type of data. It takes a long, long time to learn how to do that if you're using something like fMRI or MEG (especially MEG) because you learn on the job, analysing your data set one step at a time. It would help if you were at least familiar with MATLAB. The easiest way to do it is to find a place that has a very strong reputation for that technique - your supervisor should be an expert, rather than someone branching out into the technique and make sure there are lots of other post docs and senior PhD students to support your training. Good luck!

As someone once told me, it's not about how often that journal tends to get cited, it's about how often your paper gets cited. There's defintely something to be said for publishing in lower impact journals if that's where other researchers tend to publish work on your topic. Same goes for open access journals - the more people that can read it, the better. If your paper gets cited 20 times, no-one is gonna care where it was published.

Playing a bit fast and loose with the facts aren't they?

I wouldn't read too much into it Blue - what I said was just a way to be more informal, but I don't think anyone would choose not to reply to the message you sent. There must be some other reason. Hopefully they get in touch with you soon. :-)

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Friendly always trumps formal in my view, but I do work in a department where there aren't really any boundaries between staff and students, everything is very informal.

As Dafydd says, I'd be more inclined to say something like: I'm free every day this week from 9am onwards, so just let me know what time would suit you to meet.

Don't quit. Go to whoever is in charge of postgrad affairs in your department and ask them to mediate in a meeting between you and your supervisor, to discuss these issues. In my experience, the person who gets the flack when students fail to submit within the 4 year deadline is the person to keep your supervisor in check. Provide them with a summary of the work so far, they will likely say yes you have enough for a PhD and the three of you (or more if you bring your other supervisors along) can negotiate a write-up timetable. Believe me, once that has been done, it is very difficult for your supervisor to then suggest further data collection or analysis. If they do, you just politely remind them that the issue has already been resolved. ;-)

I would do it. You could see about getting a retrospective absence from your PhD i.e. the university could mark down the last 3 months as you being off sick. Then you could take some time off right now as well, then come back in a month or so? Only if you think any of that would help obviously. What do you want to happen - what's your main concerns about it?

I never heard of this before...

I don't get why the desktop icons would change to Adobe - unless they are pdf files rather than links to locations on your computer or other programs? If they are pdf files then it seems like you changed your default program to open a pdf with to Adobe. And possibly the installation didn't work properly for some reason e.g. it's for a different version of your operating system than the one you're actually using.

But why do you need Adobe at all? It's not the only pdf reader and editor out there, there are many good quality free alternatives available. I use pdf xchange viewer and it's pretty good. You could try downloading that instead.

I think option A is best. But long term, if the other student can't replicate what he reported in his thesis, that sounds like a major issue. Did the work in the thesis get published? Because you would probably still want to publish your new results because they contradict the previous research.

Just as an aside - do you have the same supervisor? If so, isn't a bit weird that your supervisor hasn't noticed the difference between the previous and current results? Are they going to be at the talk - because surely if you present it as 'this is what I found, and it's the same as what X found', your supervisor will think 'no, this is different from the results in the thesis I read before submission'.

Web of Science has most stuff in my field.

The reasons are well documented for anyone that wants to look. The frequentist GLM approach (e.g. ANOVAs, t-tests) are based on the normal distribution - the accuracy of the test depends on your data fitting this model distribution; however real life data often doesn't. I know we all know that data have to be normally distributed to use these tests, but the fact is a lot of social scientists just use them anyway even when the assumptions are not met. The benefit of bootstrapping is that you use your sample as the reference for your statistic i.e. you don't make these assumptions about the distribution so the results are more robust. The reason a lot of behavioural scientists don't use bootstrap is simply because it takes longer - you end up using MATLAB or something, and you have to learn the language, plus the bootstrapping itself takes time to run. Compare that to the ease of plugging your data into SPSS or Statistica, and it spitting out a nice p-value... people just don't want to do it because they didn't get into this field to end up doing math, and if the academics are happy with the status quo they just say to their students "oh don't bother with that, just do a t-test". Then the students become the next generation of academics, and they say the same thing to their students.