Predict response given new input data | GLME

I am trying to fit a model between a dependent variable (Y) and two predictor variables (X, Z) using GLME.

First I divided the data into training (80%) and validation (20%). I've fitted a GLME model to the training data:

    X = Xtr % Validation portion of data (442x1);
    Z = Ztr % Validation portion of data (442x1);
    Y = Ytr % Validation portion of data (442x1);

    trTable = table(Y,X,Z);
    mdl_glme = fitglme(trTable,'Y ~ X + (1 | Z) + (-1 + X | Z)')'

Now I want to test this model on new (validation) data. This is where I run into problems. If I try:

    X = Xval % Validation portion of data (110x1);
    Z = Zval % Validation portion of data (110x1);
    Y = Yval % Validation portion of data (110x1);
    valTable = table(Y,X,Z);
    ypred = predict(mdl_glme,valTable)

I get the following error:

Error using categorical (line 434)
Unable to create default category names.  Specify category names using the CATEGORYNAMES
input argument.

Error in nominal (line 152)
            b = b@categorical(a,args{:},'Ordinal',false);

Error in classreg.regr.LinearLikeMixedModel/makeInteractionVar (line 806)
            G = nominal(ds.(interactionVars{1}));

Error in classreg.regr.LinearLikeMixedModel/extractGroupingInfo (line 205)
                model.makeInteractionVar(ds,interactionVars);

Error in GeneralizedLinearMixedModel/predict (line 539)
        ginfo = extractGroupingInfo(model,ds);

Though if I inspect trTable and valTable the only difference I can see is the number of rows:

    442×3 table (trTable)

      Y             X           Z 
      _________    _________    ________

       1.2107       1.2011      0.098847

   110×3 table (valTable)

      Y             X            Z 
      _________    _________    ______

       1.6064       1.6024      1.6024

I would be very grateful for any feedback and/or advice.

Regards J

[the cyclist]

Can you upload your dataset, or a minimal subset that exhibits the problem?

(Sometimes trying to find the minimal subset that causes the problem will actually help identify the cause.)

[Joel]

Thanks! I really appreciate it! I will upload it first thing tomorrow morning as I do not have access to it at the moment (home computer).

Regards J