Suppose I have $n$ data sets where each variable has the same variable types, but possibly a different number of data points. For instance, age, sex, and height, for $n$ different counties. After performing analysis (linear, logistic, Poisson, etc..) on each data set (country), how do I display information for all the results? Do I show a histogram of the regression coefficients, do I give the number of significant results? What do statistical packages do? (Does R have a library for this?) I'm currently not sure how to search for an r package that does this.
The purpose of the information display is to summarize the results of all the different models, where I asume that a model is a combination of method and data set. What I don't understand is how to compare or summarize, let's say $n$ p-values, where each p-value is computed with a different data set. Is there an intelligent way summarize all the different p-values, regression coefficients, AIC, BIC, ...?
An example taken from the above would be: After $n$ models have been computed (1 for each country), we gather 2 $\times$ $n$ $\times$ $m$ p-values and regression coefficients where $m$ is the number of variables used in each of the $n$ models. Is there an informative method for describing or summarizing my all my results. The brut force method would, in my option, be to display each model summary (p-values, coefficients,etc), but this could be a list that is too large. Getting an understanding of the state of all countries after analysis, might be difficult with the brut force method. How would someone go about getting a simple view of the state of all countries?