Jihong Zhang, M.S.

Jihong Zhang, M.S.

Ph.D. Candidate

University of Iowa

Biography

I’m a doctoral student of Educational Measurement and Statistics, mainly focusing on Bayesian latent variable modeling, Item response theory modeling, diagnostic modeling. I’m also interested in machine learning and data science.

My research tries to help other practitioners understand their data and correctly interpret, and to wisely use the powerful tools of statistics.

Download my CV.

Interests
  • Bayesian Psychometric Modeling
  • Machine Learning and data mining in Education
  • Diagnostic Classification Models
Education

  • Ph.D. in Educational Measurement & Statistics, 2019 - Present

    University of Iowa

  • M.S. in Educational Psychology, 2015 - 2019

    University of Kansas

  • B.S. in Applied Psychology, 2009 - 2013

    Soochow University, China

Recent Posts

Thesis Defense
Last updated on Oct 23, 2022 0 min read
NSF Grant on Bayesian Cognitive Diagnosis
The NSF grant awards can be easily searched via NSF website. Check Active Awards and type “Bayesian & Cognitive Diagnosis” into the search box. Two things I’m really interested in: (1) Who as Principal Investigator (PI) obtained most NSF awards?
Last updated on May 21, 2022 2 min read
Web Scraping Academia Institute's Grant Fundings using R
This is an example of how to web scrape grants of active research in college’s official website. Please follow the academia institute’s website robotes rules. library(XML) library(stringr) library(rvest) library(tidyverse) library(kableExtra) Web Scrapping topics = rep(NA, 84) fundings = rep(NA, 84) iter = 0 for (page in 1:9) { ## parent webpage scrape_url <- paste0('http://XXXXXXXXXXXXXXXXXXXXXX', page) html_form_page <- read_html(scrape_url) ## find the child web page containing projects' name, total award, topic etc.
Last updated on May 17, 2022 2 min read blog
Power Analysis for Structural Equation Modeling
Table of Contents Global Power Local Power Conclusion Discussion The statistical power of a hypothesis test is the probability of detecting an effect, if there’s a true effect presented to detect.
Last updated on May 2, 2022 6 min read R, Rshiny, webpower, Lavaan
[Workshop] Creating Academic Blog via R
Resource Michael Clark has a great workshop in his blog introducing distill package. I suggest readers check it out first. Requirement Following software is necessary to replicate the steps in this post:
Last updated on May 2, 2022 2 min read R, Github, Rstudio, Workshop
More Posts

Skills

R

90%

Statistics

100%

Photography

10%

Experience

 
 
 
 
 
Intern
SRI International
Jan 2021 – Present California

Responsibilities include:

  • Analysing
  • Modelling
  • Deploying
 
 
 
 
 
Intern
Edmentum Cop.
Jan 2018 – Dec 2019 Remote
Expolre item exposure issues using R. Two algorithms are designed for the specific data structures

Recent Publications

Quickly discover relevant content by filtering publications.
January, 2022 Structural Equation Modeling: A Multidisciplinary Journal, Vol.29(2)
A Model Comparison Approach to Posterior Predictive Model Checks in Bayesian Confirmatory Factor Analysis
A Model Comparison Approach to Posterior Predictive Model Checks in Bayesian Confirmatory Factor Analysis

In this study, we proposed a new method of PPMC based on comparing posterior predictive distributions of a hypothesized and saturated BCFA model.

PDF Cite Slides Source Document DOI
December, 2021
Fully Gibbs Sampling Algorithms for Bayesian Variable Selection in Latent Regression Models
Fully Gibbs Sampling Algorithms for Bayesian Variable Selection in Latent Regression Models

This study proposed efficient Gibbs sampling algorithms with different types of shrinkage priors for variable selection in a latent regression model under a unidimensional two-parameter logistic item response theory model.

PDF Code Dataset Project Slides DOI

Popular Topics

Blog Clustering DCM Deep Learning Demo Education gganimate ggplot2 glmnet Jags julia Lasso Lavaan LCM R R Markdown Source Themes Statistics Tutor tutorial

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