Dear all,


How do you compute the confident intervals for the estimations of the random
coefficients? I have not seem a lot of discussion about this in the forum. I
wonder why. Is there any theory background about this?

Description of my data:

I have 29 time series of data, biomass over time for 29 populations. I want
a hierarchical linear model with varying intercepts and slopes. So it
computes 29 intercepts, 29 slopes and the overall mean of the intercept and
slope and the variation among intercepts and slopes.

*Here you have my linear mixed model:
*
ssb_model2.1<-lme(log(SSB_tonnes)~year2,random=~year2|id, data=ssb)

*Data:*
SSB_tonnes: spawning stock biomass (ssb), continuous variable
year2: time in years, continuous variable
id: there are 29 id, in other words 29 populations of fish

*Here, in the summary of the ouput* I find the oveall mean of the interceps
and slopes and their variation.
*> summary(ssb_model2.1)*
Linear mixed-effects model fit by maximum likelihood
 Data: ssb
       AIC      BIC    logLik
  1575.647 1605.880 -781.8235

Random effects:
 Formula: ~year2 | id
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev     Corr
(Intercept) 3.30025584 (Intr)
year2       0.02960239 -0.674
Residual    0.42259598

Fixed effects: log(SSB_tonnes) ~ year2
                Value Std.Error   DF   t-value p-value
(Intercept) 13.190739 0.6271420 1110 21.033098  0.0000
year2       -0.019053 0.0058418 1110 -3.261529  0.0011
 Correlation:
      (Intr)
year2 -0.69

Standardized Within-Group Residuals:
        Min          Q1         Med          Q3         Max
-5.34384192 -0.39116381  0.04824214  0.41871509  4.60300635

Number of Observations: 1140
Number of Groups: 29

*Here I have the estimations for the random coefficient. 29 interceps and 29
slopes. How do you compute the confidence intervals for these estimations?
please any advise.
 *
*> coef(ssb_model2.1)*
   (Intercept)        year2
1    11.490207 -0.017008685
2    11.169138  0.008690365
3    13.373769 -0.030298582
4    13.680485 -0.024891089
5    15.498426 -0.033080606
6    14.869951 -0.012568273
7    13.016336 -0.025133918
8    13.968938 -0.030511346
9    13.079165 -0.017713727
10   12.935920 -0.054212415
11    9.124597 -0.026398183
12   11.493282 -0.005128911
13   10.371121  0.012636602
14   18.273836 -0.081414152
15   15.679493 -0.015946371
16    5.397496  0.027787751
17   14.479558 -0.024691465
18   16.388451 -0.030843356
19   18.326202 -0.098614391
20   12.031710 -0.010605874
21   10.352634 -0.008145436
22   14.501495 -0.038909443
23   14.415786  0.009461663
24    6.915476  0.025257749
25    7.247051  0.016988203
26   14.519202 -0.026469286
27   16.403880 -0.035931279
28   18.120565  0.014417736
29   15.407256 -0.019264309

Thanks

-- 
>))):)   >))):)   >))):)   >))):)   >))):)   >))):)   >))):)   >))):)

Maria Jose Juan Jorda

AZTI - Tecnalia / Unidad de Investigación Marina
Herrera Kaia Portualde z/g
20110 Pasaia, Gipuzkoa, Spain

Recursos Marinos y Pesquerias
Depart. Biologia Animal, Vegetal y Ecologia
Universidade A Coruña
Campus A Zapateira s/n
15071, A Coruña, Spain

Tel. Oficina +34-981167000 ext. 2204
Tel. Mobil + 34-671072900
Fax. +34981167065
mjuan@pas.azti.es
mjuanjorda@gmail.com

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