https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/ Recent content in Creating Designs in DisplayR on Handbook Hugo -- gohugo.io https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/introduction/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/introduction/ TL;DR DisplayR Design Module Overview TL;DR If you feel smart, and don’t want to waste time on brushing up your conjoint knowledge, you can go directly to the short tutorial on the DisplayR settings: Otherwise continue reading. Each conjoint study has a few critical parts that contribute to a successful project. We are capable of controlling some of these parts, while others are kept random. https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/algorithms/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/algorithms/ Algorithms Complete Enumeration Balanced Overlap Efficient Partial Profiles Alternative specific Random and Shortcut Algorithms The first thing you need to do is to decide which algorithm to use. The options are: Random Shortcut Complete Enumeration Balanced Overlap Efficient Partial Profiles Alternative specific - Random Alternative specific - Fedorov If you are puzzled, don’t worry, this is not as scary as it looks. https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/inputs/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/inputs/ Common options Algorithm specific options Random, Shortcut, Complete Enumeration, Balanced Overlap and Efficient algorithm input options Partial profile input options Alternative Specific input options Common options The plethora of possibilities might seem too much to handle, but the Random, Shortcut, Balanced Overlap, Complete Enumeration, and Efficient have the same input menu. Only Partial profiles and Alternative Specific designs are different. https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/outputs-and-statistics/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/outputs-and-statistics/ Design diagnostics Statistics Standard errors Frequencies and Pairwise Frequencies Overlaps Extracting Design Nice orange messages Design diagnostics So we managed to fill all the inputs, click the calculate button, and we need to interpret the output somehow. Output Preview Statistics In the first tab, you will see a bunch of statistics. The most important for us are: D-error (we want to minimize that) and balance (there are 4 different balance fields) – we want to keep it close to 1, but we assume that anything above 0. https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/sample-size/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/sample-size/ What sample size do I need? Sample size when using prohibitions What sample size do I need? Well the basic rule of thumb is 200 per each subgroup or at least 300 total, whichever is greater. Another rule of thumb is to use equation: \[n*t \geq 10 * \frac{k}{p}\] Where n is the sample size, t is the number of choice sets, k is the total number of levels minus the total number of attributes, and p is the probability of the least frequently chosen alternative. https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/additional-checks/ Mon, 01 Jan 0001 00:00:00 +0000 https://handbook.gradientmetrics.com/products/conjoint-experiments/Conjoint-Designs/creating-designs-in-displayR/additional-checks/ Additional things to do Check if you have not missed anything Do the conjoint tasks look reasonable? Additional things to do After you check the numbers and everything seems perfect in terms of the numbers, there are two more checks you should always do. Check if you have not missed anything The simplest way to do it, is to set up filters in your excel sheet with design.