# Assessing rmcorr asumptions: Error in shapiro.test(res) : all 'x' values are identical

Hi guys,
I'am using rmcorr package to make some repeated measures correlations based on a code that a colleague of mine built. code for making the correlation matrix:

library(rmcorr)
for(i in 24:46){#colunas com citocinas
for(n in 1:23){#colunas com OTUs ASVs etc
r=rmcorr(longitudinal_data_f\$sampleID,longitudinal_data_f[,i],longitudinal_data_f[,n],dataset = longitudinal_data_f)
Matriz_corr[i-23,n]=r\$r#Mudar número para a primeira coluna das citocinas menos 1.
Pvalues[i-23,n]=r\$p#Mudar número para a primeira coluna das citocinas menos 1.
}
}

colnames(Matriz_corr)=colnames(longitudinal_data_f)[1:23]
rownames(Matriz_corr)=colnames(Matriz_corr)

Today while assessing the normality of the residuals of the models with the following code:
normal_test=as.data.frame(NULL)
library(rmcorr)
for(i in 24:46){
for(n in 1:23){
r=rmcorr(longitudinal_data_f\$sampleID,longitudinal_data_f[,i],longitudinal_data_f[,n],dataset = longitudinal_data_f)
res=residuals(r\$model)
shap=shapiro.test(res)
normal_test[i-23,n]=shap
}
}
I was surprised with the following error: Error in shapiro.test(res) : all 'x' values are identical. (and in fact all the residuals of the correlation where it occurred were all zeroes)
I am still learning how to code in R, can anyone help me to modify the code in order to be able to:

1. remove all the correlations with none residuals variance
or
2. to overcome cases like this one and continue testing for the remaining correlations.

thank you in advance, best
Sara

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