psychology
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I'll show a brief program below. The program demonstrates unclear/consistent behavior of the size, width and height arguments when creating a new Rect. Using the argparse module, the user can easily create a rectangle using the size argument. When the program isn't given any argument, the width and height argument of Rect() are used and then the the proper size is used for the rectangle, if the
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I wonder if there is an easy way to add a public significance statement right after the abstract. For example, this journal specifies that:
Authors submitting manuscripts to the Journal of Experimental Psychology: Human Perception and Performance are required to provide 2–3 (between 120–150 words) brief sentences regarding the public significance of the study or meta-analysis described in their
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Is there any utility to adding type and cov.std options to mxStandardizeRAM?
FYI , in lavaan,
type for continuous variables
- "std.lv" var of latents only
- "std.all" = var of both manifest and latent variables
- "std.nox" like "all", but exclude var of exogenous covariates.
cov.std
- If TRUE, residual observed covariances scaled by sqrt ‘Theta’ diagonal (residual latent
Update Readme.md
Update Readme.md to provide guidelines on how can take contribute and build on top of this repository.
Add links for all the existing information.
The docstrings (the help) for these functions must be completed... Easy but I did it too much already
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Hi,
umx is great, thank you for it!
I am looking for mediation-relate resources. Are there any? Is it possible to provide an example of mediation analysis with umx? I couldn't find it in the docs, only in the lavaan-to-openmx-helper function.
Particularly, it would be fantastic to exemplify hierarchical (mixed-effects) mediation because I think openmx/umx is the only framework in R that ca
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Feb 5, 2020 - HTML
Following on from work in #126
We have an example function demo_group_comparison.m. This runs parameter estimation on two groups of data, and then calls the function group_comparison
group_comparison.m
Should be able to use the following methods:
- Parameter estimation approach: compare the distribution of differences
- Bayesian Hypothesis testing: using Bayes Factors
- Po
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Users should be able to sort books on basis of rating, year published, title etc.
See https://github.com/hackerkid/Mind-Expanding-Books/tree/master/app to setup development environment