A @BarackObama sandwich-selfie at the @WhiteHouse, earlier today with Bill Nye @TheScienceGuy http://twitter.com/neiltyson/status/439577841689436160/photo/1
Shared via Plume
- University of WisconsinGraduate Student, 2008 - present
- Wisconsin Department Of Public InstructionResearch Analyst, 2013 - present
- Wisconsin Department of Public InstructionPolicy Research Advisor, 2011 - 2013
- Office of the Governor of WisconsinPolicy Analysis Intern, 2009 - 2010
I am passionate about fulfilling the potential of applied statistical models and quality data visualization to inform policy makers and practitioners and improve the effectiveness of services - particularly in education. Since 2010 I have been exploring a number of different techniques to achieve these goals focusing on the methodology that best fits the needs of the audience. While working at the Wisconsin Department of Public Instruction, I have led a number of projects exploring this nexus of policy, practice, and evidence.
Major projects have included:
- Developing and deploying a statewide Dropout Early Warning System (DEWS) in Wisconsin
- Building training material in the R open-source statistical software DPI R Bootcamp
- Assembling a diverse set of techniques for analyzing administrative data
- Applying classification models to administrative records to determine natural groupings and patterns
- Visualizing education data in unique ways to explore temporal, spatial, and correlational relationships For public examples of this work please visit the Presentations page.
I also believe in building techniques that scale. A big part of this is building partnerships and sharing work. It is this problem of scale that drives my interest in open platforms and open science. This includes developing shared open source tools on GitHub, building communities of practice within and across state lines, and professionalizing the analysis of administrative data for use by practitioners.
Leveraging administrative records to inform policy and practitioners involves investigating the appropriate methods that meet the needs of the users. Analytical methods are about the producing information from data, and the method chosen helps determine what information can be provided. I am continually searching for methods that meet those needs. Linear regression is not the beginning and end of data analysis and has many limits that policymakers and practitioners inherently understand. Currently I am very interested in investigating the application of the following methods:
- Latent variable analysis including latent class analysis and structural equation modeling
- Bayesian data analysis that includes incorporating the judgment of subject matter experts with data
- Predictive modeling techniques including SVM, neural networks, and other classification algorithms
- Mixed effect models that incorporate nested and crossed random effects
- Variance decomposition
Once the analysis has been conducted, the challenge turns toward presenting the results in a way that is meaningful and actionable by educators. All too often important findings are buried in technical jargon, Greek letters, and incomprehensible tables filled with stars. Practitioners need visualizations that are engaging, meaningful, and make the complex workings of the analytical model accessible. I am interested in exploring the following approaches to this problem:
- Simulation studies to dynamically explore model parameters
- Multi-model inference to adjust models to different questions
- Interactive displays of model results that can be controlled by intuitive UI elements
A final piece of this puzzle is building partnerships around key initiatives. This includes building partnerships within governmental entities and partnerships between governmental entities and external organizations. Selecting and building partnerships requires extensive communication and genuine commitment - but such work is vital. Quality partnerships allow partners to achieve economies of scale and more comprehensive investigations of problems and solutions. I currently participate in a number of such partnerships and am committed to identifying such opportunities and pursuing them in alignment with the needs of policymakers and practitioners.
Look for more information in the future as more of these projects roll out. Stay tuned!
- University of Wisconsin-MadisonPolitical Science, PhD, present
- University of Wisconsin-MadisonPolitical Science MA, 2008 - 2009
- Pacific UniversityPolitics And Government; German Studies, 2004 - 2008
- Ludwig-Maximillians UniversitaetGerman, 2006 - 2007
Laurel man injured in motorcycle-deer collision on Molt Road
A 32-year-old Laurel man riding a motorcycle suffered non-life-threatening injuries Friday after crashing into a deer that ran in front of h
Online resources for handling big data and parallel computing in R
by Yanchang Zhao, RDataMining.com Compared with many other programming languages, such as C/C++ and Java, R is less efficient and consumes m
Interactive Graphics with the iplots Package (from “R in Action”)
(This article was first published on R-statistics blog » R, and kindly contributed to R-bloggers) To leave a comment for the author, please
Technical Analysis of Kansas Voter Registration Data
Computer Assisted Reporting [Note: Many of the links attached to images below are not working correctly.] This article describes technical
Getting Started with JAGS, rjags, and Bayesian Modelling
This post provides links to various resources on getting started with Bayesianmodelling using JAGS and R.It discusses: (1) what is JAGS;(2)
Reproducible Research: Export Regression Table to MS Word
Here's a quick tip for anyone wishing to export results, say a regression table, from R to MS Word:Read more »
David MacKay and Occam’s Razor « Statistical Modeling, Causal Inference...
Statistical Modeling, Causal Inference, and Social Science. Skip to content. Home; Books; Blogroll; Sponsors; Authors; Feed. « Absolutely la