nipype.algorithms.icc module

ICC

Link to code

Bases: BaseInterface

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.

mask : a pathlike object or string representing an existing file subjects_sessions : a list of items which are a list of items which are a pathlike object or string representing an existing file

N subjects m sessions 3D stat files.

icc_map : a pathlike object or string representing an existing file session_var_map : a pathlike object or string representing an existing file

Variance between sessions.

subject_var_mapa pathlike object or string representing an existing file

Variance between subjects.

nipype.algorithms.icc.ICC_rep_anova(Y)

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]