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Signal Detection Theory vs. Logistic Regression

Signal Detection Theory vs. Logistic Regression

I recently came across a paper that explained the equality between the parameters of signal detection theory (SDT) and the parameters of logistic regression in which the state (“absent”/“present”) is used to predict the response (“yes”/“no”, but also applicable in scale-rating designs) (DeCarlo, 1998; DOI: 10.1037/1082-989X.3.2.186). Here is a short simulation-proof for this equality. Setup For this simulations we will need the...

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(Bootstraping) Follow-Up Contrasts for Within-Subject ANOVAs

(Bootstraping) Follow-Up Contrasts for Within-Subject ANOVAs

Permutation ANOVA Bootstrapping with car and emmeans 1. Make your data WIIIIIIIIIIDEEEEEEEE 2. Fit your regular model 3. Define the contrast(s) of interest 4. Run the bootstrap Summary So you’ve run an ANOVA and found that your residuals are neither normally distributed, nor homogeneous, or that you are in violation of any other assumptions. Naturally you want to run some a-parametric analysis… but how? In this post...

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Quidditch: Is It All About the Snitch?

Quidditch: Is It All About the Snitch?

The Game, the Rules Estimating the Average Game Length Estimating the Rate of Goals Scored Simulating the Games R Setup Equal Teams Unequal (but matched) Teams Conclusion Much has been said about how the game of Quidditch is ruined by the scoring system - specifically how it makes no sense that the snitch is worth 150 points and that catching it ends the game (1, 2, 3)....

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Examining Inter-Rater Reliability in a Reality Baking Show

The Format In the blind auditions, candidates have 90 minutes to prepare a dessert, confection or other baked good, which is then sent to the show’s four judges for a blind taste test. The judges don’t see the candidate, and know nothing about him or her, until after they deliver their decision - A “pass” decision is signified by the...

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cheatR: an R package for catching cheaters

cheatR: an R package for catching cheaters

Our idea was to compare each hand-in to all other hand-ins and see the degree of overlap between them. This was achieved using the ngram r-package to break each hand-in into a list of “phrases” and then to count how many times each phrase appeared across a pair of documents1. Finally, the percent of non-unique phrases was calculated. Looking for...

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