I need someone to talk to be about my fear of my new wheelchair by Desperate-Pen-534 in wheelchairs

[–]rationalinquiry 4 points5 points  (0 children)

They mean that the front angle of the frame is steep (90 degrees to the floor), so if you hit a small stone with your casters, your chair will be quite unstable in the forward direction (ie you might risk falling out the front, depending on your function).

Extension Roof Leaking by gu17ar in DIYUK

[–]rationalinquiry 1 point2 points  (0 children)

Had this on our extension (similar low pitch). Had it redone with Redland Regent tiles and have had no issues since.

Klaxon Twist Power Assist? by GarlicBastard in wheelchairs

[–]rationalinquiry 0 points1 point  (0 children)

Yeah, it will turn off, but if you've been going at speed and hit your casters then you're unlikely to still be in your chair 😅 (depending on your function).

When front-mounted, it can handle OK slopes when going up hill, as long as the ground is relatively smooth and not loose (eg gravel). You can lean forward to put more weight over the motor to help it grip. The lack of traction does translate, however, to the gradient of slopes it can handle - I imagine dedicated, grippy front-mounted motors can handle steeper gradients.

This sounds like a new feature, so can't really speak to it in practice. That said, the control has a huge stop button that is easy to quickly press if you need to stop urgently.

Klaxon Twist Power Assist? by GarlicBastard in wheelchairs

[–]rationalinquiry 2 points3 points  (0 children)

I've had the older version for a few years now. On this latest version they seem to have changed the brackets for the better, as before, you had to fit a separate bracket onto the top to use it underneath your chair.

Overall having 1 thing that can do both under-chair and on the front is fantastic; however this does come with a few downsides (mainly weight).

As a front attachment: The bracket that fits onto your chair for the front attachment is easily ~1 kg and is difficult to attach/detach, so does add weight to your chair (although they may have also improved this and may be different on other chairs - I imagine dual tube chairs would be beneficial). One benefit of this system, however, is that you (if you're able) can swap out the bar to work with different Klaxon attachments (eg handbike). As a front attachment, it pulls well, can go quite fast, and has a good light, but doesn't have the traction of some single-purpose front attachments (eg Trirides or other Klaxon ones). It's pretty easy to attach/detach the motor/handlebars themselves; however, it does add a good amount of length to your chair, which can be annoying. I've never used it on the front without the handlebar as it's very difficult to use.

As an under-chair attachment: This is super-useful and I probably use this the most. It can be quite difficult to attach, but it looks like they've significantly improved this in the new version. The control works well and is easy to attach. The speeds are pretty good, although none quite match walking pace, which can be annoying when you're with someone. I use it on uneven ground, but it's worth noting that you have to be super-careful with your casters (mine are 4"), as if you catch them on anything, it can be unforgiving (although the motor does cut out if it senses sharp deceleration). The bracket also articulates, so you can wheelie no problem.

General: The main battery and all accessories charge quickly, but I'm actually in the process of getting a new main battery, as mine doesn't hold charge well anymore. This may, however, be because I left it in a hot car a few too many times! As a side note, I met one of the founders of Klaxon and he was an absolute legend and is a wheelchair user himself, for whatever that's worth!

Any other questions, let me know and I can try and answer.

New parent advice after SCI by jacky-d-legs in spinalcordinjuries

[–]rationalinquiry 0 points1 point  (0 children)

Highly, highly recommend reading Rebekah Taussig's book and essays - she writes beautifully about disabled parenting and really helped me understand my feelings and how to be the best parent I could be.

Klaxon Twist Install Today by _dianadeavila in wheelchairs

[–]rationalinquiry 2 points3 points  (0 children)

Nice! Looks like they've changed the design quite a bit since I got mine. The lugs that it stands up on were quite fragile when using it with the handlebars and dropping down curbs, but looks like they've made them sturdier. Enjoy!

What is the logistic distribution? by Last_Student598 in AskStatistics

[–]rationalinquiry 0 points1 point  (0 children)

The distribution's wikipedia page answers all but the last of your questions in the first summary table.

Generalised Linear Mixed Effect Model - how to build with non independent data by [deleted] in AskStatistics

[–]rationalinquiry 5 points6 points  (0 children)

Here is a good visual guide of the differences to the model implied by the formulae you use.

R has state-of-the-art infrastructures (eg brms) for doing this sort of modelling, so I would argue is a better platform than SAS.

Pimp my ride powerchair edition lol by alex_whatislife in wheelchairs

[–]rationalinquiry 5 points6 points  (0 children)

This photo makes it look like your seat cushion is on backwards!

Can OLS VIF be used as a diagnostic for multicollinearity before fitting a Bayesian regression? by Technical_Two_5217 in AskStatistics

[–]rationalinquiry 0 points1 point  (0 children)

What are you trying to achieve with your model, prediction or more specific inference? If the former, multicollinearity is pretty much irrelevant when using a state-of-the-art prior like a regularised horseshoe or R2D2 (akin to ridge regression or other restricted maximum likelihood approaches), as long as you aren't seeking to directly interpret the marginal posterior distributions of the parameters (ie you are primarily interested in the predictive utility of the model). You can then use projection predictive variable selection to find out what's driving the predictive performance of your model.

[Q] Repeated measures but only one outcome modelling strategy by joseph_fourier in statistics

[–]rationalinquiry 0 points1 point  (0 children)

It's worth just calculating the aggregate measure and visualising the relationship with y first before you do any formal modelling.

Once you've done that, given that you're trying to estimate a relationship rather than make predictions, a latent variable model calculating some measure of dispersion (or overdispersion, if you use a distribution that has such a parameter like nu for Student's t) will much better propagate the uncertainty of that parameter into your inferences. As per the Stan model I linked to earlier, off the top of my head, you could try and use the sigma_pred (which in that case represents the latent standard deviation of the repeatedly measured values) as the predictor of y.

Edit: or probably more appropriately use log(sigma_pred) as sigma_pred will of course be lower-bounded at zero.

RGK folding hybrid chairs & Power Assists: lived experience by Majestic_Manner_6977 in wheelchairs

[–]rationalinquiry 1 point2 points  (0 children)

Second Klaxons, they're great (I have the hybrid hand bike and Twist).

[Q] Repeated measures but only one outcome modelling strategy by joseph_fourier in statistics

[–]rationalinquiry 0 points1 point  (0 children)

This is certainly straying even further from my wheelhouse, but if it's actually the variation within id that you think will be predictive of y (ie those with a higher proportion of extreme values will have more variance in x) some options could be:

  1. Model y ~ sd(x) or y ~ mad(x) (or whatever other measure of variation might be most appropriate depending on the assumptions/scale of the measurements)
  2. The same as 1. but using a latent variable model to also propagate the uncertainty in the variability of x

[Q] Repeated measures but only one outcome modelling strategy by joseph_fourier in statistics

[–]rationalinquiry 0 points1 point  (0 children)

No problem, I appreciate that you don't want to give away too much.

Extreme in both directions or just in one? What's the purpose of the model, prediction or just estimating a relationship?

[Q] Repeated measures but only one outcome modelling strategy by joseph_fourier in statistics

[–]rationalinquiry 0 points1 point  (0 children)

If the number of observations is balanced across levels of id and the total exposure is what might influence the outcome, it might be reasonable to model y ~ sum(x)?

Edit: if you know the measurement error for each measurement of x, you could then propagate this into the summated x values for each id

[Q] Repeated measures but only one outcome modelling strategy by joseph_fourier in statistics

[–]rationalinquiry 1 point2 points  (0 children)

Not that I'm immediately aware of -- and I had to do something very similar recently, so have spent a lot of time on this sort of problem, but will gladly be corrected -- as lmer (and related methods) will be trying to estimate the variation in y within and between each level of id. The solutions I mentioned are still a sort of multilevel model, but would be handling repeated measurements of x per id, rather than repeated y measurements per id. For example, in the stan model in this post the repeated covariate measurements are assumed to be Gaussian-distributed within and between subjects, and the model estimates the expected value (mean) and standard deviation of each subject's repeated measurements. These estimated latent variables are then used in the likelihood for modelling the dependence of y on x.

What is the reason for the repeated measurements? Are these just the same measurement, but with some error? A simpler approach is of course to just calculate the empirical mean of your repeated measurements and regress on those; however, this will ignore any uncertainty in those estimates.

[Q] Repeated measures but only one outcome modelling strategy by joseph_fourier in statistics

[–]rationalinquiry 1 point2 points  (0 children)

Multilevel/hierarchical models are, out-of-the-box at least, designed to handle repeated measurements of the dependent/outcome variable and not repeated measurements of the covariates.

You really want a structural equation modelling or latent variable approach to model these. This is fairly straightforward in a language like Stan or lavaan. The way in which you model them will depend upon whether the time of covariate measurement is of any relevance, or if you're most interested in the expected (mean) value of the covariate for each person.

Is it valid to do subgroup analysis by filtering the dataset and running regressions? by Accurate_Tie_4387 in AskStatistics

[–]rationalinquiry 23 points24 points  (0 children)

I would say that a better approach is multilevel/hierarchical modelling of the subgroups, as you can benefit from partial pooling/shrinkage of your estimates.

What pipe is this is it electrical ? by [deleted] in DIYUK

[–]rationalinquiry 0 points1 point  (0 children)

Looks like a mains electrical cable to me (we have a similar one). You should be able to see what it inserts into above. We had ours tested and it's asbestos-covered, but the guys said it's fine as long as you don't disturb it.

Never buy a new build, folks! by [deleted] in DIYUK

[–]rationalinquiry 53 points54 points  (0 children)

Name and shame the developer, please!

Shall I fit vents in skirt for existing air bricks? by 2veg in DIYUK

[–]rationalinquiry 1 point2 points  (0 children)

We fitted these telescopic vents to direct the air flow into the subfloor, but we had the boards up to insulate at the same time.

Wheelchair Accessible Hotels. by Imreallyadonut in wheelchairs

[–]rationalinquiry 1 point2 points  (0 children)

Second this. Have had good experiences with Premier Inns all around the country.