How does the distribution of the outcome variable influence the difference between these two types of R2s?

Compare and contrast the contingency models of organizational structure.
November 27, 2020
Calculate all the ratios.
November 27, 2020

1.There are several alternative methods for calculating pseudo-R2 values in GLMs. One such approach in a dichotomous probit model is to construct a two-by-two table of observed and predicted outcomes, where individuals with Xβ > 0 assigned to have a predicted score of “1” (otherwise they receive a predicted score of “0”). The R2 is then simply the proportion of correctly classified individuals. Under a Bayesian approach, we would obtain multiple values for β and, hence, multiple possible R2 values. Perform this process and compare the result with what is obtained using the method I described in the chapter. How does the distribution of the outcome variable influence the difference between these two types of R2s?

2.Develop a strategy for handling missing data in the probit model (dichotomous or ordinal). Assume the data are MAR.

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