algorithms.icc

ICC

Link to code

Calculates Interclass Correlation Coefficient (3,1) as defined in P. E. Shrout & Joseph L. Fleiss (1979). “Intraclass Correlations: Uses in Assessing Rater Reliability”. Psychological Bulletin 86 (2): 420-428. This particular implementation is aimed at relaibility (test-retest) studies.

Inputs:

[Mandatory]
mask: (an existing file name)
subjects_sessions: (a list of items which are a list of items which
         are an existing file name)
        n subjects m sessions 3D stat files

[Optional]
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run

Outputs:

icc_map: (an existing file name)
session_var_map: (an existing file name)
        variance between sessions
subject_var_map: (an existing file name)
        variance between subjects

ICC_rep_anova()

Link to code

the data Y are entered as a ‘table’ ie subjects are in rows and repeated measures in columns

One Sample Repeated measure ANOVA

Y = XB + E with X = [FaTor / Subjects]