[R] can R do Fixed-effects (within) regression (panel data)?

[Douglas Bates]

On 6/4/05, ronggui <0034058 at fudan.edu.cn> wrote:
> i want to ask 2 questions.
> 
> 1) can R do Random-effects GLS regression which i can get from Stata?
> the following result is frome Stata.can I get the alike result from R?
> 
> xtreg lwage educ black hisp exper expersq married union, re
> 
> Random-effects GLS regression                   Number of obs      =      4360
> Group variable (i) : nr                         Number of groups   =       545
> 
> R-sq:  within  = 0.1799                         Obs per group: min =         8
>        between = 0.1860                                        avg =       8.0
>        overall = 0.1830                                        max =         8
> 
> Random effects u_i ~ Gaussian                   Wald chi2(14)      =    957.77
> corr(u_i, X)       = 0 (assumed)                Prob > chi2        =    0.0000
> 
> ------------------------------------------------------------------------------
>        lwage |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
>         educ |   .0918763   .0106597     8.62   0.000     .0709836    .1127689
> ......................
>          d86 |   .0919476   .0712293     1.29   0.197    -.0476592    .2315544
>          d87 |   .1349289   .0813135     1.66   0.097    -.0244427    .2943005
>        _cons |   .0235864   .1506683     0.16   0.876     -.271718    .3188907
> -------------+----------------------------------------------------------------
>      sigma_u |  .32460315
>      sigma_e |  .35099001
>          rho |  .46100216   (fraction of variance due to u_i)
> 
> 
> 2)
> 
> can R do Fixed-effects (within) regression as Stata's xtreg?
> 
> the followng example is from
> "Introductory Econometrics: A Modern Approach" by Jeffrey M. Wooldridge
> Chapter 14 - Advanced Panel Data Methods
> 
> use http://fmwww.bc.edu/ec-p/data/wooldridge/JTRAIN
> iis fcode
> tis year
> xtreg lscrap d88 d89 grant grant_1, fe
> 
> Fixed-effects (within) regression               Number of obs      =       162
> Group variable (i) : fcode                      Number of groups   =        54
> 
> R-sq:  within  = 0.2010                         Obs per group: min =         3
>        between = 0.0079                                        avg =       3.0
>        overall = 0.0068                                        max =         3
> 
>                                                 F(4,104)           =      6.54
> corr(u_i, Xb)  = -0.0714                        Prob > F           =    0.0001
> 
> ------------------------------------------------------------------------------
>       lscrap |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
>          d88 |  -.0802157   .1094751    -0.73   0.465    -.2973089    .1368776
>          d89 |  -.2472028   .1332183    -1.86   0.066    -.5113797     .016974
>        grant |  -.2523149    .150629    -1.68   0.097    -.5510178     .046388
>      grant_1 |  -.4215895      .2102    -2.01   0.047    -.8384239   -.0047551
>        _cons |    .597434   .0677344     8.82   0.000     .4631142    .7317539
> -------------+----------------------------------------------------------------
>      sigma_u |   1.438982
>      sigma_e |   .4977442
>          rho |  .89313867   (fraction of variance due to u_i)
> ------------------------------------------------------------------------------
> F test that all u_i=0:     F(53, 104) =    24.66             Prob > F = 0.0000

I'm not sure what the models being fit by Stata are but I imagine that
they correspond to models that can be fit in R by lmer (package lme4)
or lme (package nlme).