LME- log-normal distribution of parameters

["Pravin" <jadhavpr@vcu.edu>]

Hello,

>lme(response ~ time, data="" random = ~ 1+time|ID)
##"time" is used a predictor for the "response" in the data frame "data.g"
##Random regression intercepts and slope on "time"
##Random effects vary over  individual ID

The above model assumes that the intercept and the slope are normally distributed. How can I specify log-normal distribution for these parameters. But the residual error can be normally distributed-- that is fine. One suggestion was to use log transformation. But I cannot use log transformation in the fixed effects model (log(response)~log(time)) because there are a few 0's in the predictor column.

Thank you,

Pravin

Pravin Jadhav