5

Yes, there is nothing wrong with your approach and you can simply add a time-varying covariate as a fixed effect. The only thing to be aware of is that this covariate could account for a large proportion of the autoregressive component, which could make the model unstable or singular. You might also want to allow for nested random effects, if you have ...


2

I will tackle your questions and concerns from the bottom of your post and work my way up. Are such data appropriate for a DID analysis? Yes. You're well within the realm of the "classical" difference-in-differences (DiD) approach. Your data is 'aggregated up' to the district level and treatment begins at the same time for all treated districts. ...


2

The outcome graduated is binary, so you need a model for binary data such as a logistic model. There appears to be repeated measures within id so you need to account for correlations within id. You could use a model with random effects for id to do so. To answer your research questions you can fit a model with fixed effects for time_with_new_teach and ...


1

You can look at this answer for a similar question. The solution relies on, in a first step, splitting clients on training and testing, say you have clients [0, 1, 2, 3] Split 1 : Train : [0, 1] Test : [2, 3] Split 2 : Train : [0, 2] Test : [1, 3] ... Then, for each training/testing split, split again in a times series way : Split 1a : Train on the 6 ...


1

I think that this is a decision only you can make. You say: I generally will produce full models, reduced models, and a null model, and compare them by AIC to select the most parsimonious model for analysis. The full models almost always score the best, and are used in the analyses. But that can produce a different model than you would choose based on ...


1

I think this is essentially the answer I was looking for: In Barr (2008): Analyzing ‘visual world’ eyetracking data using multilevel logistic regression, it is stated: "With orthogonal polynomials, the interpretation of each term in the equation is independent of all other terms (i.e., inclusion of a higher-order term does not change its interpretation)....


Only top voted, non community-wiki answers of a minimum length are eligible