Hi folks





I am using the lmer function (in the lme4 library) to analyse some data where individuals are clustered into sets (using the SetID variable) with a single fixed effect (cc - 0 or 1). The lmer model and output is shown below.

Whilst the fixed effects are consistent with stata (using xtmixed, see below), the std dev of the random effect for SetID is very very small (3.5803e-05)compared to stata's (see below 1.002). Any ideas why this should be happening please....?



I am happy to share my data if that helps.



LMER MODEL



summary(lmer(AnxietyScore ~ cc + (1|SetID), data=mydf)) Linear mixed model fit by REML

Formula: AnxietyScore ~ cc + (1 | SetID)

   Data: mydf

   AIC   BIC logLik deviance REMLdev

493.4 503.4 -242.7    486.6   485.4

Random effects:

Groups   Name        Variance   Std.Dev.

SetID    (Intercept) 1.2819e-09 3.5803e-05

Residual             1.3352e+01 3.6540e+00

Number of obs: 90, groups: SetID, 33



Fixed effects:

            Estimate Std. Error t value

(Intercept)   3.1064     0.5330   5.828

cc            2.3122     0.7711   2.999



Correlation of Fixed Effects:

   (Intr)

cc -0.691





STATA XTMIXED



xtmixed anxietyscore cc || setid:, reml



Mixed-effects REML regression                   Number of obs      =        90

Group variable: setid                           Number of groups   =        33

Log restricted-likelihood = -242.48259          Prob > chi2        =    0.0023

------------------------------------------------------------------------------

anxietyscore |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]

-------------+----------------------------------------------------------

-------------+------

          cc |   2.289007   .7492766     3.05   0.002     .8204519    3.757562

       _cons |   3.116074   .5464282     5.70   0.000     2.045094    4.187053

------------------------------------------------------------------------------

------------------------------------------------------------------------------

  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]

-----------------------------+------------------------------------------

-----------------------------+------

setid: Identity              |

                   sd(_cons) |   1.002484    .797775      .2107137    4.769382

-----------------------------+------------------------------------------

-----------------------------+------

                sd(Residual) |   3.515888   .3281988      2.928045     4.22175

------------------------------------------------------------------------------





with thanks & best wishes

M




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