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A introduction about gt package is here knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE, fig.align = "default", eval = TRUE) library(gt) suppressMessages(library(tidyverse)) Basics of gt A basic gt table can be created as so data("iris") glimpse(iris) ## Rows: 150 ## Columns: 5 ## $ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4… ## $ Sepal.Width <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.

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Last night, I read the 1st chapter of Statistical Rethinking: A Bayesian Course with Examples in R and Stan from Richard McElreath. I found this is nice book to share with my friends. The core idea of that chapter is the relationship between NULL hypothesis and statistical model. That is, should we trust the statistical models to reject the NULL hypothesis? It is a long history to use statistical models to figure out what is true?

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R language could be easily used as a bash script using Rscript *.R. system() is a R base function which could run command line within R. Below is a simple example which allows to automate create a new blog post: (1) Ask users to type in filename, title and language (2) Create a new markdown file in specific directory (i.e. your local posts saved path) (3) Add some metadata in .

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A brief introduction of using Network Model to visualize latent attributes’ hierarchy of Diagnostic Modeling.

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See the handout and download the poster here.

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Skills

R

90%

Python

10%

Linux

10%

Statistics

100%

Education

90%

Projects

*

Latent Network Diagnostic Classfication Model

A Proposed Model Embeding Networking Modeling with DCM

Posterior Predictive Model Checking for DCM

Model checking in Diagnostic Classification Models (DCM) is an underdeveloped area

Teaching

I am a teaching instructor for the following courses at University of Kansas:

  • EPSY 906: Latent Trait Measurement and Structural Equation Models

Contact

ORCID iD iconhttps://orcid.org/0000-0003-2820-3734