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12

MANOVA is definitely a bad idea given that one dv is continuous and the other is binomial. After exploring a number of different approaches to combining RT and accuracy data, I've come to conclude that the best current approach is to use linear ballistic accumulator model (e.g., see Donkin et al 2011). The LBA is a simple (structurally and computationally) ...


12

Here are a few options. I have not tried them yet personally. LBA Scott Brown has a copy of Donkin et al (2009) on his web page with some code in R, Excel, and WinBUGS for fitting the LBA model: http://www.newcl.org/publications/DonkinAverellEtAl2009BRM.pdf http://www.newcl.org/members/chris/fitLBA.zip Diffusion model The Diffussion model is ...


10

A paper comparing the performance of Inverse Efficiency Scores and diffusion models for the quantification of RT and accuracy can be found here. Rach et al. (2011) "On quantifying multisensory interaction effects in reaction time and detection rate " Psychological Research Volume 75, Number 2, 77-94, DOI , PDF


9

There are a variety of models solving accuracy and RT that have been pretty well tested and LBA is probably fine (I haven't used it). If you don't want to go that far there is a rather simple way to analyze data controlling for SAT that has much better mathematical properties than IE scores (which, as Mike said were named by me, but offhandedly proposed by ...


8

You can find an accessible overview of some of the issues in Whelan (2008) which contains further references discussing the issue. Note that from a statistical perspective, the sample mean and median are unbiased estimators of their population equivalents. That said, with outliers, skew and the like, the standard error of the sample mean can be quite a bit ...


8

The basic approach that you are describing sounds like inverse efficiency scores (e.g., see Townsend and Ashby, 1978,1983), which are measured as $$\frac{r}{1-e} = \frac{r}{c}$$ where $r$ is reaction time, $e$ is proportion error, and $c$ is proportion correct. John Christie provides a critique of inverse efficiency scores here or see the discussion in ...


6

Using Parameters Estimated from an Individual in a Group Analysis In a way this is exactly what usually happens when we calculate the mean reaction time across all conditions for a group of participants. When we normally calculate mean reaction times we assume that some process (P) takes t milliseconds to complete plus some Gaussian distributed noise. We ...


5

Another possible approach is using EZ-diffusion model suggested by Wagenmaker, van der Mass and Grasman (2007). Quoting Brown & Heathcote (2008; p. 4): This model is extremely simple, with just one source of variability in evidence accumulation—within-trial randomness—and simple linear accumulation (although evidence for one response does count ...


5

I recently had similar problem and I used inverse efficiency (IE) scores. These scores were derived by dividing the response times by correct response rates separately for each condition, carried out in such a way that the higher the score was, the worse was the performance. So you get something like "corrected reaction time" scores. Here is example of paper ...


5

In short: none that I could find. Indeed, it's a very one-way relationship - the more you drink the worse reaction time gets. However, there is a starting point, which is generally put around .02-.06 depending on your chosen study - below that threshold the effect of BAL on reaction times is difficult to pin down. Most studies I found showed that below .05% ...


5

For the diffusion model, there is also Eric-Jan Wagenmakers' "EZ-diffusion model", which you can find here. This paper compares three different pieces of software for estimation of diffusion model parameters: von Ravenzwaaij D., & Oberauer, K. (2009). How to use the diffusion model: Parameter recovery of three methods: EZ, fast-dm, and DMAT. ...


5

I think you need to think about what you mean by "speed of thinking". Your language implies that you are looking for a generalised way to be more intelligent. I have not seen any simple interventions for increasing general intelligence. You may find it more productive to focus on particular domains of your life that you want to improve. Practice and ...


5

First off, what button-box you use is going to be influenced by what software you're using to run the experiment, so ideally you should specify that. The PST serial response box is probably the industry standard, and is what we have in my lab, although a lot of that is probably down to it coming from the makers of EPrime. EPrime doesn't work on OSX ...


4

The number of samples that are necessary for a good parameter estimation does indeed depend on the estimation method. I am not aware of a simple rule of thumb to determine an optimal sample size, but there has been a lot of literature on this topic. A paper that might be a good starting point for a literature search is Van Zandt T. (2000) How to fit a ...


4

Disclaimer: I'm not generally doing experiments where reaction time is the primary DV. But I thought I'd look at this issue and explored RTs from a neuroimaging dataset, and I think the findings are relevant to the question. I think without further qualification, this question doesn't have an answer. Here I've plotted the estimation of reaction time/RT over ...


3

I imagine most software designed for creating psychological experiments will be able to do this. (e.g., EPrime, Direct RT, MediaLab, SuperLab, etc.). I've mainly used Inquisit to record responses and response times. These are all proprietary options. You could also readily implement a trial interface with a textbox and response times in standard programming ...


3

vand den Bos et al (2002) van den Bos et al (2002) summarises research over various ages. They reported: The reading task was to read in 1 min, as fast and accurately as possible, the unique and unrepeated words of a stan- dardized word-reading test. Results indicate that word-reading speed and naming speeds of colors and pictures continue to ...


3

As mentioned in the other comments, ANOVA is problematic when mixing types of predictor variables. (Generalized) mixed effects models are gaining popularity these days and actually provide a very convenient way for modelling such things. A paper demonstrating the efficacy of this approach as well as giving a tutorial-like introduction is: Davidson, D. J. ...


3

You can transform RT, i.e., by log(1/RT). This makes the distribution roughly normal. The problem is that you don't usually run the ANOVA on the RT values collected at each trial, but on the average for each participant. So the distribution across participants need to be normal. A trick is to transform the single RT values, calculate the mean for each ...


2

There's a new program called "Paradigm" that has direct support for typed responses. It will measure the input speed, time to first key press and record the typed response. It's very easy to use and has a number of other great features. Check it out: Paradigm http://www.paradigmexperiments.com


2

This article by Whelan (2010) is one of the best introductory papers I've found on the subject. Normalization is covered quite clearly and extensively, including the caveats and "gotchas". References Whelan, R. (2010). Effective analysis of reaction time data. The Psychological Record, 58(3), 9.


1

My impression is that, recently, a consensus began to form recently that RTs should be transformed to satisfy model assumptions. This is especially true when data is analyzed with mixed models instead of ANOVAs. Concerning the stability of effects under different transformations, you may find this paper interesting: http://web.uvic.ca/psyc/masson/KMR10.pdf


1

If I managed to understand, each participant may have a slightly different viewing experience, as long as it's constant through multiple sessions each participant has. To achieve this, you may ask participants to sit an arm's reach from their monitor. Try to make the images span the same physical size (even though it's really hard to achieve ...


1

2 sounds reasonable. The variability you introduce by sticking to pixels or display ratios seems like it outweighs the apparent unreliability of monitor size calculations. Also, unlike TVs that scale the content to fit the size, most webpages do not scale -- so, when I drag a webpage from my laptop screen to my second (larger) monitor, the size stays ...


1

In chess it helps not to watch for the entire thing, instead to watch only out for "structures" you know, e.g., some particular structure of a famous checkmate position. You can also think in layers, and remove minor threads out of your thinking, like pawns or pieces on the starting line. This should also work in real world thinking. Remove minor threads ...



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