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Re: st: Breusch and Pagan Lagrangian multiplier test for random effects


From   Austin Nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Breusch and Pagan Lagrangian multiplier test for random effects
Date   Mon, 7 May 2012 11:37:56 -0400

Caliph Omar Moumin <sheikmoumin@yahoo.com>:
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
<sheikmoumin@yahoo.com> 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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