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From |
Tobias Morville <tobiasmorville@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Several questions regarding xtprobit and margins command |

Date |
Mon, 12 Nov 2012 15:58:21 +0100 |

Hi everyone, my first post at StataList, so be nice :) I have a set of questions regarding the margins command, and marginal effects in general. I have a unbalanced paneldataset of 4124 observations, unevenly distributed on 18 subjects. My model is as follows: P(stop) = Outcome outcome_lag1 seqEarn, which im estimating in a RE probit setting with xtprobit command. Outcome: Outcome of a dice in period t. Lies from 1 to 6 Outcome_lag1: Outcome of the dice in period t-1 seqEarn: Accumulated earnings over each game. Drops to 0 if subject chooses to stop, or the dice shows a one. Starts at zero, and can only get more positive as people climb the reward ladder. All of these regressors are significant. Sooo, now the questions begin: 1) If i use -margins Outcome- (followed this guide http://www.stata.com/stata12/margins-plots/), then i get this errormessage: "'Outcome' not found in list of covariates", and that actually is the case for all margins commands, and is my number one headache. The only marginscommand that works, is if i use the -margins, dydx(Outcome outcome_lag1 seqEarn)-, which leads me to my next problem: 2) When i use a -margins, dydx(Outcome outcome_lag1 seqEarn)- my marginal effects are exactly the same as my regression coefficients? If i change the code to -margins, dydx(Outcome outcome_lag1 seqEarn) atmeans- they're the same again..? (So APE = MEM?) Im really confused about this, and i've read the ealier post (http://www.stata.com/statalist/archive/2009-11/msg01517.html), which covers some of the questions i have, but dosen't really anwser them. If i use mfx compute, predict(pu0) they change, but they become very small. And im guess that pu0 means that Im setting the random effects slope to 9, which is a bad idea for my data, as there is quite alot of random variability. 3) If i choose to ignore the fact that my marginal effects are the same as my probit regression coefficients, then im in my next pickle. That my marginal effects are constant. If i plot the predicted probability of stopping the game, over seqEarn, its constant, which suits my data very badly. And im afraid that i've misunderstood something very basic. if i try -margins, dydx(seqEarn) at (Outcome=(2 3 4 5 6)) vsquish- marginal effects are the same over Outcome size... .. and it's basically the same. What i would idealy like to see, is that predicted probability changes both over seqEarn and over Outcome and outcome_lag1 in some systematic way, but right now my newbieness in Stata problemshooting is driving me up the wall. ------ Background (just for the interested): I'm currently working with a dataset of 18 subjects, playing a virtual dicegame for 25 mins while in a fMRI scanner. The dice is random (1-6), and if you roll one, you lose whatever you accumulated this round. It's a balloon kind of thing: How far do people dare to go up the exponential reward ladder, before banking their earnings. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Several questions regarding xtprobit and margins command***From:*Nick Cox <njcoxstata@gmail.com>

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