Application of Multiple Imputation in Cluster Analysis

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What is the purpose of pooling the results from each imputed data set?

To combine the optimal number of clusters and subset of selected variables that gives the highest CritCF in each imputed data set

How can the optimal number of clusters (kfin) be decided?

It is the most frequently selected one according to CritCF

What method can be used to describe uncertainty in kfin associated with missing data?

Barplot of selection frequency for each value of k and boxplot of CritCF for each value of k

What is the purpose of deciding the subset of clustering variables?

To decide the variables to be included in the final analysis according to their selection frequency

What type of plot does the miclust package provide for describing uncertainty in kfin associated with missing data?

Barplot of selection frequency for each value of k and boxplot of CritCF for each value of k

What does 'kopt' represent in the context of multiple imputation in cluster analysis?

The optimal number of clusters obtained from each imputed data set

What is the proposed framework by Basagaña et al.?

An algorithm for multiple imputation in cluster analysis

What is the main purpose of the miclust package?

To integrate multiple imputation with cluster analysis

What does the getdata function do in the miclust package?

Formats the provided multiply imputed data sets

What is the purpose of the summary method in the miclust package?

To print a summary of the results

What do the slides summarize about the proposed framework by Basagaña et al.?

The methods to handle missing data in cluster analysis

What is the purpose of the miclust package's plot method?

To visualize the results of cluster analysis

What does the miclust function do in the miclust package?

Performs the proposed analysis detailed in Table 1

What are the main functions in the miclust package?

getdata, miclust, summary, plot

This quiz covers the framework for applying multiple imputation in cluster analysis and pooling the results. It also includes the procedure for obtaining optimal k and subsets of selected variables from imputed data sets. The content is based on the Statistics in Health Sciences lecture by Jose Barrera (ISGlobal & UAB) for the academic year 2023/2024.

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