Hi,

I am trying to generate a metabolic syndrome score for the children aged 11 to 12 years using PCA. I run the PCA with the standardised z-score of all five metabolic components But I confused on one statement mentioned in the article that I am following "

I USED THE FOLLOWING COMMAND. It will be highly ap[appreciated if you can help me out with missing command lines. I am badly stuck at this point.

Thanks in advance

I am trying to generate a metabolic syndrome score for the children aged 11 to 12 years using PCA. I run the PCA with the standardised z-score of all five metabolic components But I confused on one statement mentioned in the article that I am following "

*Our PCA identified*

2 principal components that were summed, with weights determined by the relative amount of variance, explained to generate a total MetSrisk score".

I am also missing Stata command for final analysis " we internally standardise the final met score to get mean 0 and SD 1 so that regression coefficient can be explained by SMD2 principal components that were summed, with weights determined by the relative amount of variance, explained to generate a total MetSrisk score".

I am also missing Stata command for final analysis " we internally standardise the final met score to get mean 0 and SD 1 so that regression coefficient can be explained by SMD

I USED THE FOLLOWING COMMAND. It will be highly ap[appreciated if you can help me out with missing command lines. I am badly stuck at this point.

*global xlist Z2TotChol Z2Glucose Z2HDL Z2TG fcbmizc*

global ncomp 2

** PCA

pca $xlist

screeplot, yline (1)

** PCA Component

pca $xlist, comp($ncomp)

pca $xlist, comp($ncomp) blanks(0.3)

rotate, varimax

rotate, varimax blanks(0.3)

rotate, promax

rotate, promax blanks(0.3)

estat loadings

estat residuals, fitted

estat loadings, cnorm(eigen)

predict Pc1 Pc2, score

gen PCAScore=Pc1 + Pc2global ncomp 2

** PCA

pca $xlist

screeplot, yline (1)

** PCA Component

pca $xlist, comp($ncomp)

pca $xlist, comp($ncomp) blanks(0.3)

rotate, varimax

rotate, varimax blanks(0.3)

rotate, promax

rotate, promax blanks(0.3)

estat loadings

estat residuals, fitted

estat loadings, cnorm(eigen)

predict Pc1 Pc2, score

gen PCAScore=Pc1 + Pc2

Thanks in advance

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