Research Project

Overview

Throughout the entire semester you will be analyzing a data set with the end goal of creating a poster presentation to present your research. Your assignments will serve as a first draft of exploration into your research questions, and helps you build your story. Homework assignments alone will not be sufficient for a good analysis.

You will build up your project in stages, revising multiple times. The end goal is a research poster that you will present during finals week. You will be summarizing your findings using Google Slides. This will help you concisely explain your research topic and findings in a way will be easier to translate (fit) onto a poster. Here is the general outline, with each stage is explained in detail further below.

  • Stage 1: Choose a data set and identify a few research topics
  • Stage 2: Introduce your project and variables of interest
  • Stage 3: Explore your data and relationships
  • Stage 4: Analyze bivariate relationships
  • Stage 5: Multivariable modeling & summarizing findings
  • Stage 6: Poster Creation & Presentation
Peer Review

Stages 2-6 are subject to peer review. See the help with peer review page for details.

Once you have addressed a particular piece of feedback mark it as “resolved” in Google Slides.

⚠️ Do Not Delete Feedback until notified that it is okay

General Notes

  • At each reviewed stage you should update anything you need to change based on feedback, such as correctly making graphics, writing results correctly etc.
  • The contents of each slide are specified in the slide template and explained below.
    • You are welcome to have “staging” slides where you can dump content, thoughts, analyses that you may end up using. These extra slides should be at the END of the required slides.
  • There are also example slides from prior students as a references.
Dr. D’s interpretation of your research

I will be using this Google file to summarize your research progress as I do my reviews. I may ask you to review it and address critical questions.

Stage 1: Choose a data set and identify a few research topics

  • Project data you can choose from can be found in this Google Drive folder.
  • Browse through the available data sets, read the summaries and skim the codebooks.
  • Add your name to Dr D’s summary of your research once you have chosen a topic.
  • Download the data and codebook to your Math615/data folder.
  • You will work through writing out a few research questions as part of Homework 02.

Under only very strict certain circumstances I will allow for other data sets to be used (this includes your graduate thesis data). You must make an appointment to meet with me to go over your data, codebook and research question for this to be a consideration.

Criteria for proposing new data sets

  • File type must be a .txt, .csv, .xlsx or .xls file
  • File size is less than 1 Gig
  • A codebook or data dictionary that fully explains what each variable means is available.
  • There are at least 200 rows (observations), but ideally between 500-1000.
  • There are 20 or more variables
    • At least 4 quantitative variables
    • At least 1 categorical variable

Stage 2: Introduce your research question and variables of interest

  • Make a copy of this Template and save it in the Project -00 Poster prep folder in our Google Drive.
  • Name your file using your username only

These slides for this stage are pale yellow in the template.

  • Slide 01. Title
  • Slide 02. Introduction
  • Slide 03. Background & lit review.
  • Slide 04. Explain the research problem / topic area
  • Slide 05. State your Research Question as a testable hypothesis.
  • Slide 06. Introduce the data. Where does it come from, how was it collected. How many records?
  • Slide 07. Description of measures (variables) being used.
Warning

⚠️ Pay attention to slide Numbers!

  • Please ensure that all content is on the slide as expected.
  • Slides will not be filled in in direct numerical order.
  • Check the template if you are confused. I have added slide background coloring to help you keep you on track

Stage 3: Exploratory data analysis

These slides are pale blue in the template.

  • Slide 09. Fully describe your primary response variable
  • Slide 10. Fully describe your primary explanatory variable
  • Slide 11. Fully describe the relationship between your primary explanatory and primary response variables
  • Slide 13. Fully describe the relationship of a third variable to either your explanatory or response variables

All using appropriate summary statistics, graphic and an explanatory sentence.

Stage 4: Bivariate Inference

These slides are pale purple in the template.

  • Slide 08. Describe in a few sentences what analysis tools you will use to answer your research question

  • Slide 12. Analyze the relationship discussed in slides 11

  • Slide 14. Analyze the relationship discussed in slides 13

  • This should be a conclusion written in English, in the context of the problem, includes summary statistics, confidence interval and a p-value.

Stage 5: Multivariable modeling & summarizing findings

You are trying to understand the relationship between your explanatory and response variable, in presence of information contained in other variables.

These slides are pale green in the template.

Slide 15: Model Building

  • Build a multivariable model by adding additional predictors to the model.
  • Explain your model building process in a few bullet points.
    • What variables did you test as other explanatory variables?
    • Which ones did you examine as confounders, or as effect moderators?
    • How did you determine your final model?
  • See the lecture notes (ASCN Ch 10) on model building as guidance.
  • Include any variables that were found to be significantly associated with the outcome
  • If you found a moderator, your model should include an interaction term with your moderating variable.
  • If you have a confounding variable, you still need to keep your primary explanatory variable in the model.

Slide 16: Multivariable Model - Summary of results

  • A table or plot of the regression coefficients (or Odds Ratios) must be presented.
  • At least one coefficient, the primary explanatory variable, must be interpreted in context of the problem.

Slide 17. Model Assessment

  • If using a linear or log-linear model;
    • present and interpret the model diagnostic plots
    • report and interpret \(R^{2}\)
  • If using a logistic regression model;
    • report the results of a test for goodness of fit
    • report and interpret the model accuracy, and the cutpoint used. (Ref: ASCN Ch 12.5)

Slide 18. Discussion

  • Here you will explain what your graphical and inferential results tell you about your topic.
  • Discuss if your research hypothesis was supported, if it was not, why you think that might be
  • Explain the overall story/trend/what you learned when you consider your univariate, bivariate & multivariate results about your topic.
  • Compare your results to previous research results. Do they agree or disagree?

Slide 19. Implications

  • What are the practical implications of your results?
  • What could others do with your findings?
  • What future research needs to be conducted?
    • This needs to be more specific than “other variables could be explored”. Which variables and why? What other research articles indicate that those other variables are relevant?

Slide 20. Limitations

  • Who are the results of this study generalizable to? (i.e. a subset of individuals?)
  • Were there any model assumptions that were not upheld?
  • If this is an observational study, you should make a statement about the findings are associations and not causal in nature
  • Are there other factors that could explain your response variable that you did not include in your model?

Slide 21. References

  • You can use smaller font to get all references on one slide.
  • Use references from research plan, and any additional references gathered along the way.
  • Make sure these are correctly done in APA format.
  • Proper citations for

Stage 6: Posters Presentations

Reproducibility

  • You will transfer all findings into a research poster, print the poster, and then present your research to your classmates.
  • You will create a new script file, named poster_script.qmd that replicates all the findings, graphs and analysis done for your poster.
    • You will also turn in your data management file along with this script file.
    • I should be able to reproduce every finding in your poster with the raw data, and these two script files.
  • Posters can be in powerpoint (the standard format for research posters), or Google Slides (once appropriately sized)
    • Regardless of the file type, you must use a template. Do not try to reinvent the wheel.
  • Submit the poster file itself (as PDF) into the Poster Final Google Drive folder.

Poster Creation Guidelines

See the full guidelines in this blog post. This post includes:

Draft version

This draft is graded based on how complete the poster is. You should consider this a draft that you would circulate to your colleagues for final review and comments. There is a rubric in Canvas with details.

Save your poster as a PDF and upload to the Poster Draft folder in Google Drive.

Peer review of draft

To conduct your peer review, open the PDF from Google Drive directly in your browser. Ask for help if needed with this. Do not download a copy.

  • Use the comment feature to write the comments directly into the poster file itself.
  • Provide at least two specific comments for each
    • something that can be improved
    • something that is good

Final Version

Upload your final poster as it is printed in PDF format to the Poster Final folder.

Presentation

When not presenting, you will walk around and learn about others research. Ask the presenters questions and fill out an evaluation form as you go.


Grading Method

Instead of assigning specific points to each stage and adding up the points for an overall score, this work will be done through a series of revisions gaining feedback from both your peers and the instructor at each stage.

  • For each slide to be assessed you will be marked as either “needing revision”, “meeting expectation”, or “exemplary”.
  • I will update your status column for the slides that are being assessed at that stage.
  • You can request a reassessment of prior work at (nearly) any time. (You can ask for it, I just may not get to it until the next time I’m reviewing slides.)
  • You are responsible for keeping track of your status and asking for reassessment.

Rubric

This is a method of ‘ungrading’ that I have been wanting to try for a while. The Assessment item descriptions are a work in progress. I may add, combine, or reword items as I do my revisions to better fit what I am actually looking for.

Each person has their own ‘project assessment’ Google spreadsheet (same location as your poster) that shows you what achievement stage you are at for each item. It is locked to only view mode and only you and I have access to it.

… but points!??

In the end this still has to be converted to a point value/letter grade right? So here’s how I’m going to do it.

  • If you have \(\geq\) 90% of assessment items at ‘exemplary’ and none at ‘needs revision’, that’s “A” work and you get the full points.
  • If you have \(\geq\) 90% of assessment items at ‘meets expectation’ and no more than 1 at ‘needs revision’, that’s “B” work and you get 90% of the points. Note ‘meeting expectation’ does not correspond to A level work
  • If you have \(\geq\) 80% of assessment items at ‘meets expectation’ and no more than 2 at ‘needs revision’, that’s “C” work and you get 80% of the points.

Anything below this is considered not passing and will be based on the number of items at each mastery level.

In your individual grading rubric an estimate of your final score is created by adding up the status’s for each slide: E gives full credit. ME gives 90% credit. NR gives 75% credit.

Poster Grading

Poster + presentation scoring follows the evaluation criteria and will be done via Google Forms. The link is in Canvas. Printed copies will be available upon request.