CLME stands for Constrained Linear Mixed Effects. I wrote this R package (CRAN link) during my postdoctoral work at NIEHS.
The fundamental idea is similar to the Jonckheere–Terpstra or any other test for ordered alternatives: If the treatment groups are ordinal, then a trend of some sort may be of interest. If a researcher has such a hypothesis, they can not only test for the ordered alternative, but they can constrain the estimation to respect the order from the alternative hypothesis.
There are many applications in which a statistic follows, at least asymptotically, a normal distribution with a singular or nearly singular variance matrix. A classic example occurs in linear regression models under multicollinearity but there are …
In many applications researchers are typically interested in testing for inequality constraints in the context of linear fixed effects and mixed effects models. Although there exists a large body of literature for performing statistical inference …
Oxidative stress is elevated in numerous environmental exposures and diseases. Millions of dollars have been spent to try to ameliorate this damaging process using anti-oxidant therapies. Currently, the best accepted biomarker of oxidative stress is …