Hi,
I'm sorry to bother you, but I was wondering whether anyone had ever run into
this problem. This is a problem for me both on Stata 7 and Stata 8.
I am running a clogit regression where the dependent variable can be 1 multiple
times for observations within the same group.
When I run a clogit regression against an independent variable which is a
characteristic of the choice (and which is the same across different groups), I
get the following results:
. clogit indicator rgdpch, group(id_number)
note: multiple positive outcomes within groups encountered.
Iteration 0: log likelihood = -41843.543
Iteration 1: log likelihood = -38224.759
Iteration 2: log likelihood = -37944.648
Iteration 3: log likelihood = -37831.499
Conditional (fixed-effects) logistic regression Number of obs = 264383
LR chi2(1) = .
Log likelihood = . Prob > chi2 = .
------------------------------------------------------------------------------
indicator | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
rgdpch | .0000689 . . . . .
------------------------------------------------------------------------------
I also run the clogit regression on the same dataset but with different
explanatory variables. These explanatory variables are characteristics not of
the choice but of the individual (group). However, I seperate all choices into
two groups and interact this individual level variable with dummies for each of
these two groups. In addition to getting empty results, now, when I run this
regression I get different numbers for the coefficient each time.
. clogit indicator s_prod2 w_prod2, group(id_number)
note: multiple positive outcomes within groups encountered.
Iteration 0: log likelihood = -33021.493
Iteration 1: log likelihood = -31149.417
Iteration 2: log likelihood = -31010.648
Iteration 3: log likelihood = -30996.459
Iteration 4: log likelihood = -30994.814
Iteration 5: log likelihood = -30993.758
Iteration 6: log likelihood = -30993.396
Conditional (fixed-effects) logistic regression Number of obs = 208025
LR chi2(2) = .
Log likelihood = . Prob > chi2 = .
------------------------------------------------------------------------------
indicator | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
s_prod2 | .0985613 . . . . .
w_prod2 | .0066312 . . . . .
------------------------------------------------------------------------------
Any help would be greatly appreciated.
Stanley Watt
Department of Economics
Harvard University
[email protected]
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