Statistics and Statistical Programming (Fall 2020)/pset5

Programming Challenges

For the programming challenges this week, we'll re-analyze data from the following study:

Aronow PM, Karlan D, Pinson LE. (2018). The effect of images of Michelle Obama’s face on trick-or-treaters’ dietary choices: A randomized control trial. PLoS ONE 13(1): e0189693. https://doi.org/10.1371/journal.pone.0189693

PC1. Download the dataset. You may want to familiarize yourself with the experimental treatment and key details of the research design from the (short) article.

PC2. Import the data into R. You may need to install the readstata13 package and identify an appropriate function with which to do so.

PC3. Get to know your dataset. Take a look at the codebook if necessary and make sure you have the two columns of the dataset that correspond to the experimental treatment (being presented with Michelle Obama's face) and the outcome (whether or not kids picked up fruit). Don't worry about any of the other measures for now.

PC4. Create a two-way contingency table summarizing these two variables. Make sure your table has easily understandable column and row names.

PC5. Conduct a test to determine whether or not the two groups are dependent. Report and interpret the results of your test and be prepared to discuss your findings. Please note that the paper uses a variety of techniques including linear regression and incorporates other variables, but you should use estimators and tests we read about in Chapter 6 last week. Do you have a sense, from your OpenIntro readings this week, why the results might be different when you use regression and incorporate the other variables?

PC6. Try to reproduce the top panel of Figure 1 using the same two columns of the dataset (by ignoring year and the other variables we are, in effect, working with the "pooled" sample). If you cannot reproduce that portion of the figure (or something like it), try to at least reproduce the values presented in it.

PC7. It's very important to be able to export tables directly into your word processor or typesetting software without cutting and pasting the contents of individual cells. Can you export the output of your table from PC4? There are a bunch of functions you can use to do this. I would likely use the xtable package to generate HTML and/or LaTeX output, but I think that write.table() and Excel could do the job just as well.

Empirical Paper Questions (with Statistical Questions baked in)

These questions are for the Buechley and Hill paper on LilyPad Arduino:

EQ1. For Study 1, let's focus on the statistical test:

(a) What is the unit of analysis? What is the dependent variable? The independent variable? What are groups being compared in the test? Is it a one-way or two-way design?

(b) Why not just summarize the results, like we did in week 2? Why bother with the statistical test? How do you decide when to use each statistical procedure?

(c) What is the null hypothesis being tested? What is the alternative hypothesis?

(d) Summarize or restate the results in statistical terms. Explain what these results mean in substantive terms? How convincing do you find these results? What should we be taking away?

And these are about the Shaw and Benkler paper on political blogs:

EQ2. Using the data from Table 3 and Figure 2:

(a) What statistical procedure produced the p-value in Table 3? What is the null hypothesis being tested?

(b) How convincing do you find these results? What are some reasons to be skeptical?

(c) Reproduce Figure 2 using the data in Table 3. One thing that's missing from that figure is error bars. Based on the reading from Reinhart §5, what type of error bars do you think you should use? Figure out how to calculate the error bars and figure out if they overlap? What does that tell us? (Bonus: figure out how to add error bars to the bar plot)

(d) Should we be concerned about the base rate fallacy described in Reinhart §4? Why or why not?