Re: [R] predict.lme / glmmPQL: "non-conformable arguments"

From: David Reitter <david.reitter_at_gmail.com>
Date: Wed 01 Feb 2006 - 07:39:15 EST

  On 30 Jan 2006, at 22:01, David Reitter wrote:

> I'm trying to use "predict" with a linear mixed-effects logistic
> regression model fitted with nlmmPQL from the MASS library.
> Unfortunately, I'm getting an error "non-conformable arguments" in
> predict.lme, and I would like to understand why.

I'd like to add a bit of information. (Correction: I am talking about glmmPQL from the MASS library.)

Again, the error I'm getting is:

> > yp = predict(model, newdata=new, type="response", level=0)
> Error in X %*% fixef(object) : non-conformable arguments

I have ensured that I input a data frame in newdata with the fixed factors/predictors filled in (as factors with the correct level sets where appropriate).

Debugging this, I had a look at lme.R from the nlme library. Specifically, line 1909:

if (maxQ == 0) {

     ## only population predictions
     val <- c(X %*% fixef(object))
     attr(val, "label") <- "Predicted values"
     return(val)

   }

the 'fixef' structure in my model looks like this (7 elements)

fixef(model)

                       (Intercept)                     log(distance)
                       -2.14560407                       -0.13207341
                             roler                     sourcemaptask
                       -0.58692474                       -0.93108113
               log(distance):roler log(distance):rolei:sourcemaptask
                        0.16449238                        0.06877369
log(distance):roler:sourcemaptask
                       -0.12278367


But the predict.lme function produces the following 6x5 matrix

   (Intercept) log(distance) roler sourcemaptask log (distance):roler log(distance):roler:sourcemaptask

           1     0.0000000     1             0           0.0000000  0
          1     0.6931472     1             0           0.6931472  0
(...)

We're missing the coefficient for the 3-way interaction "log (distance):rolei:sourcemaptask", which is why we can't come up with the inner product of X and the fixed effects coefficients.

Is this an issue with predict.lme, and/or can I do something about it?

Thanks
D



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