That is the atmeans: marginal effect at the mean. Note that $p$ and its derivative/finite difference are both function of $x$ and $d$, so you can evaluate either of them at various possible values.
Marginal effects of categorical/factor variables like $d$ (those prefixed with i.) are calculated by using finite differences rather than derivatives. This tells you the change in probability from a 1 unit increase in $x$. $$Pr = p = \frac = \beta \cdot p \cdot (1-p). If I were to use asObserved, what potential criticisms would you have of that? Q3(Bonus): I'm under a heavy time crunch, so I'm running with a method of using Mtable, setting binary variables to their modal values, and then using atMeans for the rest, simply because right now I have a better grasp and can write about that. They're all at a conference, and I have a draft due, so 'm askin yall. Am I missing something that Stata is doing? Or am I misconceptualizing this?Ĭompounding this is that when I go online I see people discuss predicted probabilities and marginal effects interchangeably, so I'm worried that I'm straying off course and will be explaining something to my thesis committee that is totally different than from what I'm actually doing. I've been reading papers however where people set their categorical variables to means. 8 range, and wasn't theoretically sound, as I couldn't justify picking one ideal type amongst 8*8*6*6*6*3*2*2*2 levels across 2 possible outcomes for my variables. I initially attempted to set all of my categorical variables to their modal values (Which in hind set, was silly and wasted time), and realized that it would skew the probabilities into the. Mtable, at(RecodedG21 = (0, 1) A3 = 2 A4A_new_w = 1) atmeans statistics(all) I can write about this, however I'm worried that I'm not getting the most accurate description of my model from this option. When I used atMeans, the predicted probabilities jump outside the range of what I would expect, at. Mtable, at(RecodedG21 = (0, 1) A3 = 2 A4A_new_w = 1) asobserved statistics(all) This makes me suspicious, because they resemble the initial cross tabs I did of my DV and IV. When I use asObserved, I get values that fall within an expected range. I can see the difference in the values rendered, which is major, but I can't quite get at the theory of what as observed is doing, and whether that still qualifies as holding variables at a constant value. I'm struggling with the difference between the two.
Specifically, whether I should hold them at their means using atMeans or at their observed values, using asObserved. The problem comes when attempting to hold the rest of my variables constant at a value. I have seen some commentary online about how you can get predicted probabilities from the margins (And thus Mtable) using the at(spec) option. However, the authors of prvalue (Long and Freese) have created the mtable command have released Spost13, which extends Stata's stock margins command. Prvalue does not allow for factor variables (The i. The command he suggested was prvalue, which is part of Spost9. One of my professors suggested that, in addition to odds-ratios, it would be a good idea to use predicted probabilities. The other dataset has 2 continuous variables. In one dataset (NFCS2012) all 8 are categorical variables. My dependent variable is Homeownership, and the independent variable is whether or not a respondent has student loans, both of which are binary variables. Just for background, I am running a statistical analysis using a binary logistic regression on a pair of datasets in Stata14.
Question 3 (Bonus): The nearest method I've developed, and am using due to a time crunch, is to set dichotomous (Binary) variables to their modal values, and then set the rest to asObserved. Question 2: What is the conceptual/statistical difference between the atMeans and asObserved options in Stata14's Margins commands? Question 1: What is the difference between predicted probabilities and Marginal Effects? More specifically: Is there a way I can judge when the Stata margins command is moving from one to the other? Please let me know if I left anything out. Or I might be asking you to diagram a kafka-esque monster for me.
#MARGINSPLOT STATA CODE#
To be clear: This isn't so much a syntax or code question, its more of a concept/theory question that takes the form of a code difference. I've been running on it nonstop for two or three days, and am running out of time. This is a complicated question, and I'd very much appreciate any help I can get.