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Advanced Statistical Analysis of Lab Data: PCA, Linear Discriminant Analysis, and Clustering

Perform PCA on placebo & Tamoxifen groups, conduct LDA, and compare methods in ISwR dataset 'alkfos'. Cluster data using hclust(), kmeans(), and Mclust(). Evaluate 2-group clustering against treatment classification.

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Advanced Statistical Analysis of Lab Data: PCA, Linear Discriminant Analysis, and Clustering

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  1. Exercise 1 • In the ISwR data set alkfos, do a PCA of the placebo and Tamoxifen groups separately, then together. Plot the first two principal components of the whole group with color coding for the treatment and control subjects. • Conduct a linear discriminant analysis of the two groups using the 7 variables. How well can you predict the treatment? Is this the usual kind of analysis you would see? • Use logistic regression to predict the group based on the measurements. Compare the in-sample error rates. • Use cross-validation with repeated training subsamples of 38/43 and test sets of size 5/43. What can you now conclude about the two methods? SPH 247 Statistical Analysis of Laboratory Data

  2. Exercise 2 • In the ISwR data set alkfos, cluster the data based on the 7 measurements using hclust(), kmeans(), and Mclust(). • Compare the 2-group clustering with the placebo/Tamoxifen classification. SPH 247 Statistical Analysis of Laboratory Data

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