# Monthly Archives: August 2012

## Spearman’s Rho

Spearman’s Rho Rank Correlation There are generally three types of correlation that a researcher may encounter: Pearson’s r, Kendall’s Tau, and Spearman’s Rho.  They each have their own uses and applications depending on the data and what you’re trying to achieve.  This example shows how Spearman’s Rho rank correlation is calculated.

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## Generating Random Correlated Data Part 2

Generating Multivariate Random Associated Ordinal Datasets This is a second post on generating multivariate random associated data.  This example will create random data with pre-defined correlations and marginals.

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## Generating Random Correlated Data Part 1

Generating Randomly Correlated Data with Cholesky Decomposition This example shows how to transform randomly generated data continuous data into correlated data with a specified correlation.  This example uses the Cholesky decomposition to make the transformation into correlated data.  The second part to generating random data will be to discuss the process to generated associated random… Read More »

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## Fisher’s Exact Test

Fisher’s Exact Test Fisher’s Exact Test is a useful tool when dealing with smaller sample sizes.  It allows a researcher to use the hypergeometric distribution to calculate a p-value when the assumptions from the test do not apply (e.g. small cell counts).  This example walks through the calculations to compute the probability density and cumulative… Read More »

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## K-Means Cluster Analysis

K-Means Cluster Analysis K-means cluster analysis is a very useful multivariate partitioning tool.  This R example shows how one can perform cluster analysis and provides an example of creating a scree plot to determine an appropriate number of clusters.  It is also a highly useful data mining technique.

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## Outlier Detection using Local Outlier Factor

PDF Document of Outlier Detection Outlier detection is an extremely useful tool. There are many ways to identify an outlier. This example will discuss one univariate approach and one multivariate approach. There are many uses for outlier detection. One use can be to inspect a dataset prior to analysis to ensure accurate analysis. It can also be… Read More »

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## Dominance Analysis

Dominance Analysis Raw Data Dominance Analysis Regression provides the ability to create models for prediction and to create models for inference.  Dominance analysis adds to that and provides the ability to determine the relative importance of each variable.  This example walks through an example predicting income in 2009.

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## Latent Class Model

Latent Class Analysis This example is actually less of an example but more to draw attention to a valuable tool.  Latent class analysis is a highly useful categorical data technique that can be used to create groups  known as latent classes.  This technique can be compared to k-means cluster analysis that is often used for… Read More »

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## The Jackknife

When it comes down to estimating parameters the standard error is often forgotten.   This is a slightly more complex way to estimate the standard error.  However, this is a good approach when dealing with complex samples.  This is a simple example of how to calculate a jackknife standard error.  This approach can be extended… Read More »

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## Iterative Proportional Fitting

Iterative Proportional Fitting Once a survey is conducted it is common for the researcher to adjust the survey weights to match known population values.  This process is known as iterative proportional fitting (IPF) or also known as raking.  This process was first introduced by Edwards Deming.  This process is something that can actually be performed… Read More »

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