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Version Control using RStudio & GitHub

4 minute read


Summary (TL;DR)

  • File > New Project > Version Control > Git. Set up a copy of the GitHub repository (local repository) in your own computer.
  • Tools > Version Control > Pull Branches. Before you start to make any changes, make sure the file version in your computer is the most up-to-date. To do so, you will need to pull branches from the GitHub repository.
  • Tools > Commit…. Any time you make changes, you need to commit or save changes to your local repository. Add a descriptive commit message in case you ever need to go back to a certain version.
  • Tools > Version Control > Push Branch. After you commit, you will need to push the changes, or upload changes to GitHub.



Relationship between item characteristics and detection of Differential Item Functioning under the MIMIC model

Published in Psychological Test and Assessment Modeling, 2019

In this study, we show that rates of success of identifying DIF items are higher when the anchor set is made up of highly discriminating items. We also show that DIF items are more easily detected if they have high discrimination and at least moderate difficulty (if using a correctly specified anchor). These findings reveal a relationship between item characteristics and DIF that have been previously ignored, which could lead test designers and DIF researchers to make erroneous recommendations about DIF detection.

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Robust Estimation for Response Time Modeling

Published in (accepted) Journal of Educational Measurement, 2020

Undesirable response behavior, such as speeding and innatentive responding, have long plagued educational and psychological assessments. With the advances in response time modeling, the challenge of handling such responses must be addressed. In this article, we introduce a robust estimation approach for the respondent’s working speed under the log-normal model by down-weighting aberrant responses.


Handling missing data on DIF detection under the MIMIC model


This study employs a two-step procedure which selects an anchor set and assesses the items outside the anchor for DIF (M-IT/M-PA; Wang & Shih, 2010). Results show that accuracy rates in selecting an anchor with multiple imputation were generally higher than with full-information maximum likelihood.

Bivariate Change-Point Analysis with Response Time and Accuracy


In this study, we propose the application of change-point analysis through a hierarchical framework for responses and response times. By leveraging information from both item responses and response times, we demonstrate this application to a real dataset of assessment data.

Careless Responses Using Response Time Data


Using survey data from a high school sample, in this study, we explore item-level response times, and response sequence and styles using process and meta data, and build on previously recommended methods for detection of careless response behavior.


Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.