Forest plots in R

http://www.r-bloggers.com/forest-plots-in-r-ggplot-with-side-table/

More on Gelman and Shalizi's philosphy of Bayesian statistics

Gelman and Shalizi: Rejoinder

Denny Borsboom
How to practise Bayesian statistics outside the Bayesian church: What philosophy for Bayesian statistical modelling?

Deborah Mayo
The error-statistical philosophy and the practice of Bayesian statistics: Comments on Gelman and Shalizi: Philosophy and the practice of Bayesian statistics

Multi-topic paper dump

 Michael Hout et al.
Multi-dimensional scaling

Pennie Dodds
Perhaps unidimensional is not unidimensional

Michael Riley
The dynamics of cognition

Ut Na Sio
Sleep on it: problem solving

Lavelle
Contrastive explanation and the many absences problem

Unbiased peer review

Very interesting peer review

Links that i need to post before I forget them

Roderick Little
The Prevention and Treatment of Missing Data in Clinical Trials

David Bodescu
Revisiting the Gain–Loss Separability Assumption in Prospect Theory

Robert Tibshirani
Scientific research in the age of omics: the good, the bad, and the sloppy

Gerd Gigerenzer
Homo Heuristicus

John Thogerson
Does Green Consumerism Increase the Acceptance of Wind Power?

Publication bias

 Gregory Francis

Publication bias and the failure of replication

Some notes on writing

Discussion sections.  I usually hate writing discussions.  However, I find they are extremely useful for two things.  First, for each result (affirming and disconfirming) sincerely asking oneself why the results occurred.  Then for each why question, generate explanations and consider the ones I believe the most in detail.  Try to find other evidence or ideas that relates to these explanations.  This process allows surprises to emerge, changing our questions and explanations, but also allows us to build stories around the evidence.  These stories can be used to push the theory further.

Future Directions.  Future directions should be based on understanding the processes and theory, pushing them forward, rather than trying to find new contexts.  Process rather than context driven.

For prescriptions.  The prescriptions should either refine existing proposals based on the results of the experiments (descriptive research), distinguish among existing proposals, or develop new ones.


 

Trust and self-serving biases

Bicchieri and Mercier

Self-serving biases and public justifications in trust games

Could be useful for trust and communication of scientific results.

Theory of mind in strategic interactions

New from Niels A. Taatgen

 What eye movements can tell us about theory of mind in a strategic game
 

Social context, framing effects, and dictator games

Dreber et al

Do people care about social context? Framing effects in dictator games

Posterior predictive checks can and should be Bayesian

Krushke

Posterior predictive checks can and should be Bayesian


Senn

Comment on Gelman and Shalizi


Morey

The humble bayesian

CMU Psyh

CMU psych peeps

Ken Kotovsky
 Representations of engineering students

Bob Siegler
Early predictor of high school mathematics achievement.

Ken Koedinger
Goals and learning in microworlds

Dave Klahr
Educational interventions to advance children's scientific thinking

ASVAB

Could be a useful test
ASVAB

Thinking about methods

Thinking about methods:

When I do new experiments, I want to include 5-10 participants in each condition who do think-alouds, then do protocol analysis on the think-alouds.  It probably wouldn't be to hard to ask MTurk participants to record their voice as they go through the task.  Otherwise, just bring people into the lab.

Verbal Reports as Data

I also want to be sure to do normative analysis prior to descriptive work, along the lines of Anderson's rational analysis.

The Adaptive Character of Thought

Physics: Prediction and Explanation in the Multiverse

This seems very interesting

Prediction and Explanation in the Multiverse

Trial Preregistration

Horton R, Smith R: Time to register randomised trials. Lancet 1999, 354:1138–1139.

Horton R, Smith R: Time to register randomised trials. The case is now unanswerable. BMJ 1999, 319:865–866.

Tonks A: Registering clinical trials. BMJ 1999, 319:1565–1568.

Medical Decision-Making Joint Modelign Task Force

 Good modeling practices, with transparancy.

Medical Decision Making Joint Modeling Task Force

Psychological methods and Bayesian SEM

MacCallum, Edwards, and Li
Hopes and cautions in implementing Bayesian SEM

Muthen and Asparouhov
Bayesian SEM

Associative learning addition in "Learning and Behavior"

Kutlu and Schmajuk
Solving Pavlov's Puzzle

Gershman and Niv
Latent cause theory of classical conditioning

McLaren, Forrest, and McLaren:
Elemental representation and configural mappings

Ludvig, Sutton and Kehoe
Evaluating the TD model of classical conditioning

Behavior Matching in Multimodal Communication

Loosely related to communication

Behavior Matching in Multimodal Communication is Synchronized

Visualization and Illusion of Explanatory Depth

Might be useful to take advantage of this for teaching/explaining:

"People also seem to use misleading heuristics to assess how well they understand a system. Most notably, if they can see or easily visualize several components of a system, they are more convinced they know how it works. Thus, the more easily visible are parts in a system, relative to hidden ones, the stronger the IOED (Rozenblit & Keil 2002). Visual influences of this sort may be related to the appeal of visual “mental animations” in constructing and evaluating explanations of devices (Hegarty 1992)."

From Keil, 2006; Explanation and Understanding

Explanation as a learning strategy

Tamar: This would be an easy manipulation in the sim.  Compare feedback vs. feedback and explanation.

An effective meta-cognitive strategy

Meta-analysis, Similarity, and Hierarchy

Kind of interesting.  Generalization can be based on hierarchies (categories) or similarities.  I've thought about trying to come up with some similarity metric for meta-analysis, where studies are obviously more or less similar to each other, but not categorically related, or at least the hierarchies are extremely sparse (most categories have zero instances).

Properties of inductive reasoning

The structure and function of explanation

Explanation during IHD simulation

Tamar: Fonseca and Chi: if they explain themselves during a learning task they learn better than those who think out loud, especially going beyond presented material. Might be neat for IHD sim.  Might need to come up with tests that are `far transfer'.

"Instruction based self-explanation"
 
 Handbook of research on learning and instruction