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Re: st: Breusch and Pagan Lagrangian multiplier test for random effects
From
Austin Nichols <[email protected]>
To
[email protected]
Subject
Re: st: Breusch and Pagan Lagrangian multiplier test for random effects
Date
Mon, 7 May 2012 11:57:49 -0400
Caliph Omar Moumin <[email protected]>:
You may also want a less parametric form for duration e.g. dummies for
each duration.
On Mon, May 7, 2012 at 11:37 AM, Austin Nichols <[email protected]> wrote:
> Caliph Omar Moumin <[email protected]>:
> 92 percent of your sample has only one observation in the first time
> period, then you have a few cases with longer durations? Only
> duration varies across cases? I would use pooled OLS and cluster on
> id, myself. Is cost a nonnegative depvar? In that case, you may
> prefer glm with a log link:
> http://www.stata.com/meeting/boston10/boston10_nichols.pdf
> http://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-friend/
>
> On Sat, May 5, 2012 at 10:22 AM, Caliph Omar Moumin
> <[email protected]> wrote:
>> Dear all
>>
>> For the past two weeks i spent to decide whether i apply fixed effect or random effect model in my strongly unbalanced panel data. But I couldn't decide it.
>> These are the tests i applied so could you please give a minute and advice me what to apply? I understood the my hausman test impllies that i can apply either fixed or random effect modells. Is that so? If that is correct then i choose to apply the random effect model becuase of some time in-variant involved.
>>
>> What about Breusch-Pagan Lagrange multiplier (LM) test? I have no clue as to how interperate this test? Could any help me?
>>
>> xtdescribe
>> id: 6, 9, ..., 809378 n = 14503
>> nadmission1: 1, 2, ..., 16 T = 16
>> Delta(nadmission1) = 1 unit
>> Span(nadmission1) = 16 periods
>> (id*nadmission1 uniquely identifies each observation)
>> Distribution of T_i: min 5% 25% 50% 75% 95% max
>> 1 1 1 1 1 2 16
>> Freq. Percent Cum. | Pattern
>> ---------------------------+------------------
>> 13302 91.72 91.72 | 1...............
>> 797 5.50 97.21 | 11..............
>> 160 1.10 98.32 | 111.............
>> 97 0.67 98.99 | 1111............
>> 58 0.40 99.39 | 11111...........
>> 31 0.21 99.60 | 111111..........
>> 29 0.20 99.80 | 1111111.........
>> 12 0.08 99.88 | 11111111........
>> 8 0.06 99.94 | 111111111.......
>> 9 0.06 100.00 | (other patterns)
>> ---------------------------+------------------
>> 14503 100.00 | XXXXXXXXXXXXXXXX
>>
>> I want to compare between this two groups
>> xttab group;
>> Overall Between Within
>> group | Freq. Percent Freq. Percent Percent
>> ----------+-----------------------------------------------------
>> alcohol | 275 1.64 191 1.32 100.00
>> nonalcoh | 16443 98.36 14312 98.68 100.00
>> ----------+-----------------------------------------------------
>> Total | 16718 100.00 14503 100.00 100.00
>> (n = 14503)
>>
>>
>>
>> .quietly xtreg cost duration sex age group, fe;
>> . estimates store fixed;
>> . quietly xtreg cost duration sex age group, re;
>> . estimates store random;
>> hausman fixed random;
>> ---- Coefficients ----
>> | (b) (B) (b-B) sqrt(diag(V_b-V_B))
>> | fixed random Difference S.E.
>> -------------+----------------------------------------------------------------
>> duration | 874.4642 944.5754 -70.11117 84.24204
>> ------------------------------------------------------------------------------
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