You can use the pingouin stats package for ICC calculation. Since it is a python library, it doesn't need you to install R or SPSS. You just need to drop the index to a single column as measurement. You can refer to their ICC wine dataset for information about how to rearrange your ...
charset-normalizer3.1.0pypi_0 pypi cycler0.11.0pyhd3eb1b0_0 fonttools4.25.0pyhd3eb1b0_0 freetype2.10.4h5b497f6_0 icc_rt2019.0.0h0cc432a_1 icu58.2ha925a31_3 idna3.4pypi_0 pypi intel-openmp2021.4.0h9f7ea03_3556 joblib1.1.0pyhd3eb1b0_0 jpeg 9e hc431981_0 kiwisolver1.4.2py39h6986b...
python代码实现方法如下: 首先读入数据 folderPath="/Users/.../ICC/features4ICC/"data1=pd.read_excel(os.path.join(folderPath,"reader1_ap.xlsx"))data2=pd.read_excel(os.path.join(folderPath,"reader2_ap.xlsx"))data1.insert(0,"reader",np.ones(data1.shape[0]))data2.insert(0,"reader"...
(ICC(2,1), ICC(2,k), ICC(3,1), ICC(3,k)) Returns: ICC: (np.array) intraclass correlation coefficient ''' [n, k] = Y.shape # Degrees of Freedom dfc = k - 1 dfe = (n - 1) * (k-1) dfr = n - 1 # Sum Square Total mean_Y = np.mean(Y) SST = ((Y - mean_Y...