*H*i,

I am trying to fit a GEE model with *geeglm* function. The model is the
following:

Modelo<-geeglm(sqrt ~Tra+ Mes, id=Lugar , data=datos,
family=gaussian(identity), corstr="independence")

*Tra( is a experimental treatment, 2 levels)*, *Mes* (is the month of take
data, 4 levels) and *Lugar* (is the site of study, 3 levels) are categorical
variables and *sqrt* (sqrt of Total Carbon on soil) it's a continuous
variable. I want to know if *sqrt* can be to explained for *Tra* and
*Mes*when measures among
sites (*Lugar*) are repeated measures. I get this outpout summary (A) and
anova (B).

(A) Call:geeglm(formula = sqrt~ Tra + Mes, family = gaussian(identity), data
= datos, id = Lugar, corstr ="independence")


 Coefficients:

            Estimate Std.err  Wald Pr(>|W|)

(Intercept)   4.6733  0.7007 44.48  2.6e-11 ***

TraT1        -0.2155  0.0748  8.30    0.004 **

Mes2         -0.0159  0.0699  0.05    0.820

Mes3         -0.0596  0.1441 0.17    0.679

Mes4         -0.1581  0.0373 17.99  2.2e-05 ***


Estimated Scale Parameters:  Estimate Std.err

(Intercept)     1.33  0.165


(B) Analysis of 'Wald

statistic' Table

Model: gaussian, link: identity Response: sqrt

Terms added sequentially (first to last)


    Df       X2 P(>|Chi|)

Tra  1  9.00e+00    0.0025 **

Mes  3 -1.37e+14   1.0000


The convectional ANOVA analysis with repeated measures give *p* values of
both between groups (cofactors: *Tra* and *Mes*) and intra groups (levels of
*Lugar*). When i try to fit the following model for know the wald and p
values  of the *Lugar*'s levels I get strangers p and wald values with
summary function (A) and it’s impossible to run the anova function (B).

modelo<-geeglm(sqrt~Tra+ Lugar+ Mes, id=Lugar ,data=datos,
family=gaussian(identity), corstr ="independence")

(A)

Call:geeglm(formula = sqrt~ Tra + Lugar + Mes, family =
gaussian(identity), data
= datos, id = Lugar, corstr ="independence")

Coefficients:

           Estimate  Std.err Wald Pr(>|W|)

(Intercept)  3.23291  0.00000  Inf   <2e-16 ***

TraT1       -0.23229  0.00000  Inf   <2e-16 ***

Lugar2       1.97880  0.00000  Inf   <2e-16 ***

Lugar3       2.31549  0.00000  Inf   <2e-16 ***

Mes2         0.00147  0.00000  Inf   <2e-16 ***

Mes3        -0.04217  0.00000  Inf   <2e-16 ***

Mes4        -0.22612  0.00000  Inf   <2e-16 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’1

Estimated Scale Parameters:

             Estimate Std.err

(Intercept)    0.309  0.0818


(B) anova(modelo)

Error en solve.default(vbeta[zeroidx, zeroidx, drop = FALSE]) : rutina
Lapack dgesv: sistema es exactamente singular

It’s so necessary for me get this comparisons too. Please, I appreciate if
you can help me.


Marylin Bejarano

pH student

Instituto de Ecología-UNAM

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