Which statistical package?

My research stretches across clinical psychology, behavioural neuroscience and neuropsychology (and now, with a smidge of epidemiology thrown in). Researchers in these fields use different statistical approaches, and reflecting this, different packages. SPSS is common, although the neuroscience contingent (especially the younger researchers) tend to use R. I’m a long-time, disgruntled SPSS user. Disgruntled because it’s often clunky and slow, it’s a pain to produce attractive graphs, and it’s also expensive. (It’s free through most universities, but if I wanted to use it on my own it would be a fairly costly yearly subscription fee.)

Therefore, I’ve been teaching myself R, which has a rather steep learning curve, but is probably the best long-term option. In the meantime, I’ve also trialled other free packages that are easily available, namely PSPP and JASP. (I’ve also dipped a toe into STATA, which seems like a pretty good – paid – program, but haven’t used it enough to talk about it at length.)

R is definitely the most powerful and flexible, and the graphs it produces are very pretty. It’s open-source, and it has a large international user base. New packages for R are always being developed, and support is usually available (although I find that those who ask questions are similar in skill level to me – i.e. novices – , whereas those providing answers are…not. Which often makes the answers hard to understand.) I use R Studio, which provides a nicer environment through which to use R. That being said, it’s not a point-and-click interface at all, so to use R you have to use syntax/coding. There are lots of free web-based tutorials on using R. One of these, which looks good for new users, is provided by The Analysis Factor.

PSPP is an open-source take on SPSS, which looks and feels very similar, and as such it’s a great choice for someone needing relatively basic stats but not wanting to pay for SPSS. Pros: it will read SPSS dataset and syntax files, and syntax is almost identical, so if you’re familiar with SPSS it’s an easy transition. Even if you just need to get some data from SPSS files into something else, this will work. You can also edit data in it, i.e. create new variables, edit values within your variables, etc. Cons: It doesn’t have the full functionality of SPSS (e.g. GLM does not support continuous variables/covariates), and graphs are *very* basic. From memory it’s also a bit fiddly to install, but good instructions are available and it’s definitely worth it for a free “SPSS lite” program.

JASP is a good little program. Pros: it is very clean and simple to use. It reads both csv and SPSS (*.sav) data files, and it does some surprisingly funky stuff like some Bayesian analyses (not that I know much about Bayesian statistics at present). While it only has a limited number of analyses available, it does these well, and produces nice graphs, very easily. Cons: It is all point-and-click, i.e. you can’t use syntax. You also can’t use it to edit data at all. It lacks some more advanced options available in SPSS and R, such as bootstrapping.

For now, until I get better at R and can switch to using it full-time, I am using bits and pieces from all these packages (…as I procrastinate by writing this blog post instead of working on my second paper…).

State of the garden 2017

I’m back on the veg gardening wagon (for the time being – probably until I get really busy again and start neglecting the garden; it’s a cycle). The seedlings I planted before going to Tasmania have developed considerably, and hopefully I should have some edibles soon. Some pests are eating the lemon tree and the capsicum, but the passionfruit, tomato plants, and kaffir lime tree are all doing well. The cucumber plant is out of control – it has about 8 tiny cukes growing on it. Not pictured – eggplant! I also have some zucchini plants growing, but I’m not getting my hopes up – I’ve never been able to grow my own zucchs.

Happy 2017!

The end of the year was a whirlwind. Most of it was spent on preparing for, and then doing, the Overland Track in Tasmania. This is a hiking track in the Cradle Mountain-Lake St Clair National Park. It was *amazing*, and I won’t lie: getting back to civilisation was kind of hard. (But then, once I was in Hobart, I had a long shower, put on some clean clothes, had some delicious pastries and good coffee, and got over it.) I’m planning to write a separate post about the Overland Track, with more pictures. I enjoyed so much that I am now determined to do more multi-day hikes – Six Foot Track next, in April, and loosely considering the Tour du Mont Blanc in the future (that one has a lot more climbing and descending, and is a wee bit longer).

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I got back just before Christmas – some pretty intense shopping took place in the two days before Christmas, and then some pretty intense eating, drinking, lawn games and carol-singing, for the next few days. For (at least?) the past two years I was overseas for Christmas; least year I spent Christmas day flying overseas. So it was nice to have a relatively quiet Christmas and New Year’s Eve, for a change. NYE was spent playing games, making and eating pizza, and watching terrible films with a few dear friends – and it was great.

There’s been a bit of work over the break as well – together with a few colleagues, I’m working on a few chapters for an adolescent mental health book. Two of the three chapters have taken shape now and are with the publisher. I’ve also now received feedback from all my supervisors on the systematic review/meta-analysis that’s kept me busy for the second half of 2016, and I’m going to get it ready for publication in the next couple of weeks. (Daunting! It will be my first first-author publication – eep.)

I have some big life goals for next year, such as getting my registration, getting a Real (albeit part-time, while I continue with the PhD) Job, and training for a half marathon (aiming for the Blackmores Half, in September-ish). But I also have some smaller goals – smaller in scope, but in a way not easier, as they rely on consistency. Some of these are: get up and get into university earlier, which will hopefully go hand in hand with not working as late; go for at least a short run every couple of days; set time aside to do some creative writing, art, and also some game-playing (there are lots of games I want to play, especially through Steam); go rock-climbing more regularly, and try out outdoor climbing.

2016 was a mixed bag for me, and not great, globally (although Chris Hadfield posted a list of some amazing things that happened last year). So here’s to 2017 – I hope this year treats all of us, and the planet, kindly.

Not quite the plan

I really like research. So I did imagine that I would do more of it, some day. I thought I would finish my clinical doctorate, work for a while, hopefully in a place that had a strong research culture and then eventually do a PhD through work.

So part of me is a bit baffled to find that I’ve gone and upgraded from the smaller (MSc level) research component of my combined clinical/research degree to a PhD (so I’m now enrolled in the clinical degree alongside a PhD).

I really like the research I’m currently doing. I’ve had a lot of freedom (potentially too much) to set up my own studies. I have a lot of data, which would have already been too much for an MSc. And the truth is, there’s no guarantee that I’ll end up working clinically in a setting that is supportive of research. So here I am.

Life Things are mostly starting to pick up. I’ve picked up the exercise, which has helped. I do some exercise most days of the week now – running mostly, but also rock climbing, stairs, a bit of strength stuff (probably not enough). I’ve cut down on alcohol (not that I’m a huge drinker, but it helps). And I’ve started doing mindfulness again. I use either Headspace or Smiling Mind. Stop, Breathe and Think is another one I have on my phone, to try out. Here is a literature review looking at the features of various mindfulness apps.

And here’s an upbeat song I like at the moment – Against the Current – Running With the Wild Things.

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Strange days

All the hours you sleep

All the self-care you do

All the care, compassion and love you receive

All the km you run

All the melancholy piano pieces you listen to

All the other things you distract yourself with: work, TV, books, socialising

 

None of these change the fact that a person you love is no longer in this world.

Autumn running and research FOMO

It’s a cool, rainy Autumn morning – finally. I’m inside, with the kitty, planning to do some work on the lit review before heading into uni to do more testing, reading and writing once traffic subsides.

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Pearl Izumi E:Motion Trail N2 v2. Love the red, black and lime combo.

My body is feeling quite sore, but a good “done lots of things” sore. On Friday I did a short walk/run with a friend around a bay that’s close to uni (very lucky, running by the water – lots of dog-, people- and boat-watching), on Saturday I did the usual parkrun (10 sec slower than my PB, dammit), followed by more home decluttering – the pantry looks lovely and manageable now (although how long will that last?). On Sunday I did some trail running (almost 10k very slowly, I came 3rd last in my age and sex category, but I enjoyed it a lot). I hit the trails in my new shoes for the first time, and they felt very grippy and secure, although more neutral than I’m used to (less arch support) which I’m not 100% sure about.

It’s sinking in that in just over a month I will be going overseas (North America) to present my research at two conferences. I’m still testing participants, which means I won’t have much time to analyse results and think about discussing the findings. (So I’m quietly terrified.) I’ll be spending some time in the US and Canada beyond conferencing. I’m going with a friend, and I think it’ll be fun – apart from becoming enlightened and covering our dear alma mater with glory,  I think we’re going to hit up some haunted/creepy places, catch trains, and trial some fine local fare (especially of the liquid variety).

Conferences are funny things. They make you pay to attend even if you’re a presenter – so, essentially, you are providing the content, and yet you have to pay for the privilege of being there and providing said content. Also, I’ve just found out that one of the two conferences I’m going to won’t be providing lunch this year – outrage!! And yet we do it, because it’s good experience, good “networking” (ugh…) and not least because the university subsidises the attendance of research students and academics.

Lately I’ve had massive research FOMO. My degree is a combined clinical and research degree, and my research as part of this degree will finish in a few months. I’ve been going to quite a few research seminars and colloquia, and I really wish I was sticking around to do more research – I have ideas on how I’d like to continue the research I’m doing, but it involves more experimental work of a kind that my current university is not really equipped for. Also, I don’t want to lose my clinical skills (hard-earned over the past three years), and I do really like clinical work. So the sensible option is to finish, get a job, and then think about coming back for more research later, which is something lots of psychs do. I just have to make my peace with not being able to Do All The Things at the same time…

Back to Stats

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Tools of the trade: coloured whiteboard markers, eraser, Casio calculator of a vintage that makes me feel old, tissues, and mints because talking for hours requires minty fresh sustenance. Plus accidental e-reader.

It’s the first week of tutorials for the undergrads, and the first day of tutoring for me. I started doing university tutoring two years ago, not having done any kind of teaching before, and (mostly) loved it, so here I am, back again, doing it alongside research and other work.

I’ve tutored various 1st, 2nd and 3rd year units, but most of the time I stick with Statistics. Why Stats? Quite a few of the students I teach openly admit they’re scared Stats. So I give them a bit of a spiel at the start of the semester. Stats is important, obviously so if you’re running your own research, so you can make sense of your data and see how your hypotheses fared. But even if you don’t go on to run your own experiments, in any area of science or health science you end up in, you’ll be able to critically evaluate journal articles, for example about different treatments, and make up your own mind about the results*. And even if you don’t stay in science, if you get Stats you will find people who want to be your friends, because so many people are scared of Stats**. Stats is also relevant to lots of other areas, like marketing and politics.

Riveting stuff 😉

But I do think the above is true, and the reason I generally choose to tutor Stats over other areas is because I want to make it a bit less scary for the students, and hopefully get some of them interested in Stats. (And also, other more selfish reasons, like keeping it fresh in my mind for my own research needs, and also because the marking is more objective and straight-forward than in other subjects. And also professionally selfish reasons, like increasing the Stats literacy of the future Psychology workforce.)

 

* What I don’t tell them is that it takes a long time, and a fair bit of not only statistical knowledge, but also knowledge of research methods in general and also often of a particular area of research, to really be able to engage critically with a paper’s results section.

** You might prefer people to befriend you based on your stellar personality and sparkling wit, but as a fellow Stats enthusiast I’m certain you possess both of these attributes in spades.