## Statistics.

Hierarchical Bayes is an approach to modelling MaxDiff data which can provide better predictive accuracy than other approaches (like latent class analysis). However, it is…

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In this blog post I describe how to run Hierarchical Bayes for MaxDiff in Q, and explain the options and outputs available. Getting started Your…

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In this blog post I describe how to run Hierarchical Bayes for MaxDiff in Displayr, and explain the options and outputs available. Getting started Your…

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This article compares two ways to analyze Max Diff data - Tricked Logit and Rank-Ordered Logit with Ties - for latent class analysis or Hierarchical Bayes

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t-SNE is a method for visualizing high dimensional space. It often produces more insightful charts than the alternatives like PCA.

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If you've ever wanted a deeper understanding of what's going on behind the scenes of Correspondence analysis, then this post is for you. Examples are in R.

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Singular value decomposition (SVD) is explained using examples in R. SVD is a workhorse for techniques that decompose data, such as correspondence analysis.

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This posts answers the most common questions about how to interpret R-Squared. The basic mistake that people make with R-squared is to try and work out if a

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In this post I discuss the special case of Correspondence Analysis with square tables. Such tables often arise in the context of brand switching.

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Machine learning is a problem of trade-offs. Here I look at pruning and early stopping for managing these trade-offs in the context of decision trees.

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Although PLS and Johnson's Relative Weights are both techniques for dealing with correlations between predictors, they give fundamentally different results.

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Partial Least Squares in R is a great way to conduct relative importance analysis because it effectively compresses the data before regression.

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Why is Multiple Linear Regression the standard technique taught for Key Driver Analysis when it gets it so wrong? The better method is Johnson’s Relative We

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Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis…

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This post compares various approaches to analyzing MaxDiff data using a method known as cross-validation. Before you read this post, make sure you first read How MaxDiff…

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This post explains the basic mechanics of how preferences can be measured using the data collected in a MaxDiff experiment. Before you read this post, make sure…

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Correspondence analysis is one of those rare data science tools which make things simpler. You start with a big table that is too hard to…

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Shapley regression has been gaining popularity in recent years and has been (re-)invented multiple times. However, relative weights, should be used instead.

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