Does democracy save lives? Do female political leaders respond more effectively to public health crises? Are ethnically diverse societies more vulnerable to COVID-19? How do you think political and social features of countries relate to cumulative COVID-19 deaths? Work with data we have assembled to build statistical models that predict COVID-19 mortality across and within countries. Take our model-building challenges!
New pedagogical materials will be made available in early 2022 to assist statistics and data analysis instructors in using the Model Challenges in the classroom in the first half of 2022. Please contact us for more information.
stackingapproach. This is a method for generating a meta-model that weights predictions from many models to generate a new and more accurate predictive model. A single model gets a lot of weight if its predictions are useful for generating an overall prediction considering the predictions from other models. For each challenge, you may submit both a general and a parameterized model. A general model provides a structure linking COVID-19 deaths to social and political predictors with actual parameter values and predictions to be calculated in the future. A parameterized model is a general model that also includes guesses about parameter values. A parameterized model indicates how strong a relationship is, for example, whereas a general model does not. Separate weights will be generated for general and parameterized model predictions. We use the weights that the stacking analysis places on each model to rank all legible submitted models.
legible,you will be asked to describe the rationale underlying your model choices. The whole exercise can take 20 minutes (or longer if you wish.)
More detailed information about the timeline can be found HERE
In order to be included in a model challenge, we ask you provide (English-language) text below describing the logic or rationale linking the predictors you selected to COVID-19 deaths as of 31 August 2021. We would like to know why you think the set of predictors you chose matters for the outcome. We encourage you to reference relevant political science literature.
Click on the red example links to see the kinds of arguments we have in mind. References are not required in your explanatory logic.