Standardize selected mouse-tracking measures across all trials or per level of one or more other variable, and store them in new variables. This function is a thin wrapper around scale_within, focussed on mouse-tracking data stored in a mousetrap data object.

mt_standardize(data, use = "measures", use_variables = NULL,
  within = NULL, prefix = "z_", center = TRUE, scale = TRUE)



a mousetrap data object created using one of the mt_import functions (see mt_example for details).


a character string specifying which data should be used. By default points to the measures data.frame created using mt_measures.


a vector specifying which variables should be standardized. If unspecified, all variables will be standardized.


an optional character string specifying one or more variables in data[["data"]]. If specified, all measures will be standardized separately for each level of the variable (or for each combination of levels, if more than one variable is specified).


a character string that is inserted before each standardized variable. If an empty string is specified, the original variables are replaced.


argument passed on to scale.


argument passed on to scale.


A mousetrap data object (see mt_example) including the standardized measures.

See also

mt_scale_trajectories for standardizing variables in mouse trajectory arrays.

scale_within which is called by mt_standardize.

scale for the R base scale function.


mt_example <- mt_measures(mt_example) # Standardize MAD and AD per subject mt_example <- mt_standardize(mt_example, use_variables=c("MAD", "AD"), within="subject_nr", prefix="z_") # Standardize MAD and AD per subject and Condition mt_example <- mt_standardize(mt_example, use_variables=c("MAD", "AD"), within=c("subject_nr", "Condition"), prefix="z_")