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Re: st: Question about xtlogit and temporal dummy variables


From   Steve Samuels <[email protected]>
To   [email protected]
Subject   Re: st: Question about xtlogit and temporal dummy variables
Date   Sat, 1 Mar 2014 19:19:09 -0500

Jacob privately pointed out that I had overlooked section 4.1 of the
Beck et al. paper ,which stated that probabilities predicted by the
logit an cloglog models were very close, with the average difference <
0.007% and with only 2% of predictions differing by more than 1%.

Fair enough. However I notice that the authors did not present odds
ratios in their tables, whereas presentation of hazard ratios would be
routine for a hazards analysis. I can only speculate that odds ratios,
would have looked, well odd, in a duration model.

Steve 
[email protected]


> "I think I'll go with xtcloglog. Given how close the cloglog and the
> logit results were in Beck's paper, I'd be surprised if there was a
> substantive difference between the specifications."


I'm not sure how you can say that Beck et al's cloglog and logit results
were close, when out of seven coefficients in their Table 1, logit Dummy
II vs cloglog Dummy IV, the five highest absolute percentage differences
(100*|(logit - cloglog)/cloglog|) were, from lowest to highest: 10%, 18%, 27%, and
49%.


Steve
[email protected]




> 
> On Mar 1, 2014, at 2:21 PM, Jacob Model <[email protected]> wrote:
> 
> Thanks, Stephen. That was a really thorough (and helpful answer).
> 
> I think I'll go with xtcloglog. Given how close the cloglog and the
> logit results were in Beck's paper, I'd be surprised if there was a
> substantive difference between the specifications. In fact, when I ran
> it the results were similar when running it with logit, cloglog or
> xtlogit or xtcloglog...
> 
> As far as worrying about frailty... I have firm-year observations. The
> other thing I tried to do to control for time-invariant unobserved
> heterogeneity across was to run xtlogit (with the time dummies) with
> fixed effects for firms. This specification has it's own problems
> (e.g., some firms in my sample become excluded by construction because
> they never experience an event).
> 
> -Jacob

On Sat, Mar 1, 2014 at 7:54 AM,  <[email protected]> wrote:
> Jacob Model <[email protected]>:
> 
> If you simply applied -xtlogit- to your TSCS (time-series cross-section) data set-up, you would be assuming that the (discrete) hazard were constant.
> 
> The point of the Beck et al. paper is to show to quant political science analysts that TSCS data with a binary outcome variable (BTSCS) are of exactly the same structure that one would use to fit a discrete time hazard regression model.
> 
> Hence they recommend creating a set of dummy/binary variables that correspond to the amount of time since the start of the spell (e.g. if modelling onset of peace in year T, then the binary variables indicate the years since war broke out). By using a set of variables in this way, the interval-censored "baseline hazard" is non-parametrically specified. Parametric specification of time-at-risk are also possible. In fact, note that to apply their proposed method 'out of the box' you would use -logit- not -xtlogit-.
> 
> Note that if you really want a discrete time PH hazard model, then use -cloglog- rather than -xtlogit-.
> 
> Note also the Beck et al.'s section 3.3 on "complications", especially on how to handle multiple spells and left-censored spells.  For the former aspect, you could control for correlations of unobserved factors across spells using -xtcloglog- (allows for normally distributed frailty) -- or -xtlogit- if you wish to persist with a logistic model. For country-year data, -xtset- the data: the iis variable is country and tis variable is year. Left-censoring is rather difficult to deal with, without advanced methods (and assumptions).
> 
> I suggest that you consult some standard texts on discrete time survival analysis. There are some citations at the website below my signature
> 
> Stephen
> ------------------
> Stephen P. Jenkins <[email protected]>
> Survival Analysis Using Stata: http://www.iser.essex.ac.uk/survival-analysis
> 
> ------------------------------
> 
> Date: Fri, 28 Feb 2014 14:40:33 -0800
> From: Jacob Model <[email protected]>
> Subject: st: Question about xtlogit and temporal dummy variables
> 
> I had a question about Beck, Katz and Tucker (1998)'s recommendation
> for using temporal dummies to approximate a proportional hazard model.
> (http://www-personal.umich.edu/~franzese/BeckKatzTucker.TakingTimeSeriously.AJPS1998.pdf)
> 
> I was trying to understand exactly if temporal dummies are necessary
> (or desirable) when using xtlogit to estimate a discrete time event
> history model.
> 
> I wasn't sure (and couldn't really tell in reading the documentation)
> to what extent xtlogit already incorporates this in its estimates or
> does the user have to specify them? Or if specifying them might
> interact with any correction that xtlogit does already.
> 
> Thanks for your input!
> 
> Best,
> - -Jacob
> 
> Please access the attached hyperlink for an important electronic communications disclaimer: http://lse.ac.uk/emailDisclaimer
> 
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