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Learn More About MaxDiff
This is a guide for everything you need to know about MaxDiff. It covers the “what is?” and the “how to…” of different approaches to the analysis, from preference share to profiling latent classes and finally how to interpret the...
https://www.displayr.com/learn-more-about-maxdiff/ -
MaxDiff
Displayr for MaxDiff Make MaxDiff a piece of cake Quickly go from experimental design, to analysis, to interactive report in one tool. Displayr automates all the painful manual steps and makes it easy to deliver best-in-class results, even for the novice. Book a...
https://www.displayr.com/maxdiff/ -
Comparing MaxDiff Results from Different Packages
Different models There are lots of different statistical models that you can use to compute MaxDiff. Some of these get different results from Sawtooth simply because they are wrong. If you are doing counting analysis, aggregate multinomial logit, or aggregate rank-ordered logit models,...
https://www.displayr.com/maxdiff-packages/ -
Comparing MaxDiff Models and Creating Ensembles in Displayr
Types of MaxDiff model There are two main categories of MaxDiff model: hierarchical Bayes and latent class. Within these categories, models are further specified by other parameters such as the number of classes. We frequently want to experiment with a variety...
https://www.displayr.com/comparing-maxdiff-models-and-creating-ensembles-in-displayr/ -
What is MaxDiff?
Example of a MaxDiff question A MaxDiff study involves presenting a sample of respondents with a series of questions, in which each question contains a list of alternatives. Respondents choose which alternative they like the most (best) and which the least...
https://www.displayr.com/what-is-maxdiff/ -
How to use Covariates to Improve your MaxDiff Model
MaxDiff is a type of best-worst scaling. Respondents are asked to compare all choices in a given set and pick their best and worse (or most and least favorite). For an introduction, check out this great webinar by Tim Bock. In...
https://www.displayr.com/how-to-use-covariates-to-improve-your-maxdiff-model/ -
Creating Pairwise Balanced MaxDiff Designs
Creating single version designs These earlier posts describe how to create MaxDiff experimental designs in Displayr, Q and with R. They also give some guidelines on how to set the numbers of questions and alternatives per question, as well as advice...
https://www.displayr.com/pairwise-balanced-maxdiff-designs/ -
Checking Convergence When Using Hierarchical Bayes for MaxDiff
Please read Using Hierarchical Bayes for MaxDiff in Q, or Using Hierarchical Bayes for MaxDiff in Displayr, prior to reading this post. Technical overview Hierarchical Bayes for MaxDiff models individual respondent utilities as parameters (usually denoted beta) with a multivariate normal (prior) distribution. The...
https://www.displayr.com/convergence-hb-maxdiff/ -
Using Hierarchical Bayes for MaxDiff in Displayr
Getting started Your MaxDiff data needs to be in the same format as the technology companies dataset used in previous blog posts on MaxDiff such as this one. To start a new Hierarchical Bayes analysis, click Insert > More > Marketing...
https://www.displayr.com/hb-maxdiff-displayr/ -
Case Study: Advanced Analysis of Experimental Data (MaxDiff)
This is the fourth in a series of blog posts designed as a DIY training course for using Displayr. This post presents the analysis of a relatively exotic experiment. Do not be concerned if you are unfamiliar with the technique...
https://www.displayr.com/advanced-analysis-maxdiff/ -
Comparing Tricked Logit and Rank-Ordered Logit with Ties for MaxDiff
[latexpage] Tricked logit Multinomial logit is used to model data where respondents have selected one out of multiple alternatives. The logit probability of selecting $y$ given the utilities $\beta$ is \[ \textrm{P}(y|\beta)=\frac{\textrm{exp}(\beta_y)}{\sum_{i\in A}\textrm{exp}(\beta_i)},\qquad(1) \] where $A$ denotes the set of alternatives. In MaxDiff, respondents select two alternatives...
https://www.displayr.com/tricked-vs-rank-ordered-logit/ -
11 Tips for your own MaxDiff Analysis
If you are a MaxDiff analysis novice, please check out A Beginner's Guide to MaxDiff analysis before reading this post.Download our free MaxDiff eBook! 1. Keep it simple (particularly if it is your first MaxDiff analysis) MaxDiff analysis projects come in all...
https://www.displayr.com/maxdiff-analysis-11-tips-to-diy/ -
How to Check an Experimental Design (MaxDiff, Choice Modeling)
In this post, I explain the basic process that I tend to follow when doing a rough-and-ready check of an experimental design. The last step, Checking with a small sample, is the gold-standard. I've never heard a good excuse for not...
https://www.displayr.com/check-experimental-design/ -
Using Cross-Validation to Measure MaxDiff Performance
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 analysis works, which describes many of the approaches mentioned in this post. Cross-validation Cross-validation refers to the...
https://www.displayr.com/best-method-analyzing-maxdiff/ -
How to Analyze MaxDiff Data in Displayr
This post discusses a number of options that are available in Displayr for analyzing data from MaxDiff experiments. For a more detailed explanation of how to analyze MaxDiff, and what the outputs mean, you should read the post How MaxDiff...
https://www.displayr.com/analyze-maxdiff-data-displayr/ -
How MaxDiff Analysis Works (Simplish, but Not for Dummies)
Download our free MaxDiff eBook! Counting the best scores (super-simple, super risky) The simplest way to analyze MaxDiff data is to count up how many people selected each alternative as being most preferred. The table below shows the scores. Apple is best....
https://www.displayr.com/how-maxdiff-analysis-works/