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o_guest's profile
Olivia Guest | Ολίβια Γκεστ
Olivia Guest | Ολίβια Γκεστ
Olivia Guest | Ολίβια Γκεστ
@o_guest

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Olivia Guest | Ολίβια Γκεστ

@o_guest

• goth gremlin • computational cognitive/neuroscience modeling • geek & techish Cypriot • plant aficionada • came up with #bropenscience • http://neuroplausible.com  •

Τότεναμ, Λονδίνο & Cyprus
olivia.science
Joined October 2015

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    1. Micah Allen‏ @micahgallen 18 Nov 2018
      • Report Tweet
      Replying to @micahgallen @djnavarro

      Even if you end up diverging quite far from these steps, it can still be useful to the modeller and eventual reader to know what knowledge you started with and what you discovered along the way.

      1 reply 0 retweets 7 likes
    2. Micah Allen‏ @micahgallen 18 Nov 2018
      • Report Tweet
      Replying to @micahgallen @djnavarro

      I think the hardline 'full blown registered reports or bust' stance isn't productive. As you say, this kind of modelling would actually benefit from a more customized framework that maximized transparency while not constraining you to untenable assumptions.

      1 reply 0 retweets 7 likes
    3. Micah Allen‏ @micahgallen 18 Nov 2018
      • Report Tweet
      Replying to @micahgallen @djnavarro

      In a perfect world, PR would help modellers document the process and the divergence from prior, helping us understand where our theories are weakest and also enabling better confirmatory work of the original exploratory piece.

      1 reply 0 retweets 6 likes
    4. Micah Allen‏ @micahgallen 18 Nov 2018
      • Report Tweet
      Replying to @micahgallen @djnavarro

      Thanks again for your thoughtful thread!

      2 replies 0 retweets 2 likes
    5. Joshua Skewes‏ @JCSkewesDK 21 Nov 2018
      • Report Tweet
      Replying to @micahgallen @djnavarro

      I still see the issue very much through basic the lens of phil. of sci. - Pre-reg is a consistent with logical empiricism (Carnap, Popper). - Modelling uses abductive reasoning and only LOOKS like exploration through a Carnapian lens. ....

      3 replies 1 retweet 2 likes
    6. EJ Wagenmakers‏ @EJWagenmakers 21 Nov 2018
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      Replying to @JCSkewesDK @zerdeve and

      Cherry-picking hypotheses, selective reporting of data, fishing, hindsight bias, confirmation bias: no framework sanctions these if the purpose is to learn something about the world. Exploration is great but a confirmatory check is needed at some point

      1 reply 0 retweets 4 likes
    7. Berna D.‏ @zerdeve 21 Nov 2018
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      Replying to @EJWagenmakers @JCSkewesDK and

      Was the opposite was suggested anywhere by any modelers? I have not seen that claim made in these threads. As a side note though, also important to acknowledge that not all exploratory research includes data exploration/fishing.

      2 replies 0 retweets 2 likes
    8. Donald Williams‏ @wdonald_1985 21 Nov 2018
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      Replying to @zerdeve @EJWagenmakers and

      I have been following these debates, and I am not sure what is meant by "modeler". What is a "modeler." Is it someone that fits custom models ?

      3 replies 0 retweets 0 likes
    9. Donald Williams‏ @wdonald_1985 21 Nov 2018
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      Replying to @wdonald_1985 @zerdeve and

      I sometimes fit models that take weeks of tinkering to even get the model to converge. Is this modeling ?

      1 reply 0 retweets 0 likes
    10. Berna D.‏ @zerdeve 21 Nov 2018
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      Replying to @wdonald_1985 @EJWagenmakers and

      I don’t know if the definition matters all that much for my comment. You could replace it with researchers or just people and my question would be the same. But I think we all do different kinds of modeling so there isn’t a specific mold if that’s what you meant to ask.

      1 reply 0 retweets 2 likes
      Olivia Guest | Ολίβια Γκεστ‏ @o_guest 22 Nov 2018
      • Report Tweet
      Replying to @zerdeve @wdonald_1985 and

      It's broad. https://en.m.wikipedia.org/wiki/Computational_model …

      12:16 AM - 22 Nov 2018
      • 3 Likes
      • Chris Madan 🐘🧠💻 Berna D. Åse Kvist Innes-Ker
      1 reply 0 retweets 3 likes
        1. New conversation
        2. Donald Williams‏ @wdonald_1985 22 Nov 2018
          • Report Tweet
          Replying to @o_guest @zerdeve and

          Indeed. Before coming to psychology I was in biology. When someone was a "modeler" this almost NEVER meant they used *statistical* models. Rather, they were mathematical models to, for example, study animal response and survival from environmental change. Basically, to understand

          1 reply 0 retweets 1 like
        3. Donald Williams‏ @wdonald_1985 22 Nov 2018
          • Report Tweet
          Replying to @wdonald_1985 @o_guest and

          the logic of a system and to provide some interesting ways to think of things for empirical researchers. On the other hand, now that I am in psychology, the "modeling" I do is all based on statistical models and, IMO, can almost never be used to draw strong conclusions. Rather,

          1 reply 0 retweets 1 like
        4. Donald Williams‏ @wdonald_1985 22 Nov 2018
          • Report Tweet
          Replying to @wdonald_1985 @o_guest and

          I literally "trail blaze" a path from the data to the finished model, all in an effort to first get a model that converges and to also highlight what the MODEL can be used for in general. There are so (so) many data dependent decisions along the way, that I would conclude nothing

          1 reply 0 retweets 1 like
        5. Donald Williams‏ @wdonald_1985 22 Nov 2018
          • Report Tweet
          Replying to @wdonald_1985 @o_guest and

          from them, which is to EJs point. However, the intention is never meant to be inferential but to find some data to show case a MODEL that the hope is others can use in their own research.

          1 reply 0 retweets 1 like
        6. Donald Williams‏ @wdonald_1985 22 Nov 2018
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          Replying to @wdonald_1985 @o_guest and

          So for this kind of modeling the data is often intentionally selected (and combed over) with the goal of highlighting what the MODEL can be used for. However, I do think pre-reg would be helpful here as applied researchers often like to interpret the findings.

          0 replies 0 retweets 2 likes
        7. End of conversation

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