I'm not a statistician so maybe my question is very simple but I've encountered some difficulties reading a statistical method in a cognitive psychology paper. Basically the dependent variable to model is a normal distribution where the mean and the standard deviation corresponds respectively to a systematic error in the experimental tasks and the precision in the task.
Authors report, without more reference or code, to perform a Hierarchical Linear Model:
We used HLM to examine the influence of trait anxiety, emotional valence, and their interaction effect on visual working memory resolution. The level-1 analysis included the within-individual variables (i.e., memory precision, two dummy variables indicating valence). The level-2 analysis included the betweenindividual variables (e.g., the standardized trait anxiety score). We used HLM 2 (measures within persons) to analyze the hierarchical model. Memory precision (i.e., the SD of error distribution) was entered as the outcome variable.
Given that I've a similar experiment, my question regards how to implement a HLM (I usually work with linear mixed-effects models) that model a standard deviation? Given that is basically a linear regression I should model the mean?
The reference is: