[R] Transformed predictor in linear model

Hi I fitted a mixed model with several categorical and continuous fixed variables and 3 nested random intercepts, using a transformation of the predictor y = log(y+1) and I used the defaults contrast treatment and contrast polynomial. The resulting coefficients are in log units meaning that

Re: [R] Polynomial lags

Thanks to Thomas, Roger and Spencer on your reply! I am trying to replicate/validate the results from the black box Econometrics software Eviews, compared to R and EViews uses the Almon approach. I will try the code kindly offered by Thomas. I would be interested in the way to apply the

Re: [R] Example of cell means model

answer! Best regards Francisco From: Douglas Bates [EMAIL PROTECTED] To: Francisco Vergara [EMAIL PROTECTED] CC: [EMAIL PROTECTED] Subject: Re: [R] Example of cell means model Date: 15 Oct 2003 08:40:33 -0500 This is an example from chapter 11 of the 6th edition of Devore's engineering

Re: [R] (no subject)

[EMAIL PROTECTED] To: Francisco Vergara [EMAIL PROTECTED] Subject: Re: [R] (no subject) Date: 08 Oct 2003 19:21:13 -0500 Francisco Vergara [EMAIL PROTECTED] writes: I want to specify the contrasts to build a cell means model on LME when there are several fixed effect as factors in the model

[R] Sorry! Previous subject was cell means model in LME

Hi everybody I want to specify the contrasts to build a cell means model on LME (each coefficient is the mean value of the independent variable for the specific category of a factor variable) when there are several factors as fixed effect in the model and also interactions between them. Can