I am a relatively inexperienced user of R studio. I have performed a PCA using the princomp() function. From the loadings I can tell that the actual values of all the variables I used in the analysis are inversely related to Principal Component 1 scores (all scores are negative). This means when I then use PC1 scores to generate e.g. a boxplot, the higher PC1 scores indicate lower actual values of my variables, which is quite unintuitive for a reader. Is there any way I can reverse the 'direction' of the scores for PC1 to make it more intuitive?
Thank you in advance. Any advice much appreciated!