Mastering Conjoint Analysis - Online Course
A 3-Day Livestream Seminar Taught by
Jens Hainmueller10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm
Conjoint analysis is a powerful tool for understanding multidimensional preferences, often used in market research, product development, and policy analysis. It allows researchers to dissect the preferences of individuals and determine the relative importance of different attributes when making decisions. Recent years have seen an increased use of conjoint analysis in the social sciences, thanks to the increasing ease of implementing survey experiments via online surveys.
This course offers a comprehensive journey through the entire process of designing, implementing, analyzing, and presenting results from a conjoint experiment. You will gain practical skills and theoretical understanding necessary to conduct your own conjoint studies effectively.
Throughout the course, you will engage in hands-on activities, including designing mock conjoint experiments, implementing surveys, analyzing simulated data, and creating visualizations. Real-world examples and case studies will be used to illustrate concepts and facilitate learning.
Starting October 3, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.
*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
More details about the course content
The course commences with an introduction to conjoint analysis, providing insights into its practical applications and emphasizing the significance of comprehending multidimensional preferences.
Subsequently, we delve into the fundamental principles of designing conjoint experiments, scrutinizing various design choices such as the selection of features, profiles, choice tasks, outcome measures, and randomization schemes. We will assess the merits and drawbacks of different options and acquire the skills to effectively design a conjoint experiment.
The focus then shifts towards the implementation phase, where you gain proficiency in programming conjoint surveys. You will be guided through the intricacies of survey interface design, mastering techniques for incorporating feature randomization, and internalizing best practices for collecting data.
We then turn to methods for analyzing conjoint data. You will navigate through core statistical methods, encompassing the estimation of average marginal component effects, the discernment of conditional effects based on respondent and profile characteristics, and marginal mean estimates. Additionally, insights into interpreting results and their implications for decision-making will be imparted. Lastly, you will be equipped with effective visualization techniques to convey findings to stakeholders.
By the end of the course, you will be equipped with the skills and knowledge to independently run your own conjoint experiments. You will understand the intricacies of experimental design, survey implementation, data analysis, and result visualization, enabling you to make informed decisions based on multidimensional preferences.
The course commences with an introduction to conjoint analysis, providing insights into its practical applications and emphasizing the significance of comprehending multidimensional preferences.
Subsequently, we delve into the fundamental principles of designing conjoint experiments, scrutinizing various design choices such as the selection of features, profiles, choice tasks, outcome measures, and randomization schemes. We will assess the merits and drawbacks of different options and acquire the skills to effectively design a conjoint experiment.
The focus then shifts towards the implementation phase, where you gain proficiency in programming conjoint surveys. You will be guided through the intricacies of survey interface design, mastering techniques for incorporating feature randomization, and internalizing best practices for collecting data.
We then turn to methods for analyzing conjoint data. You will navigate through core statistical methods, encompassing the estimation of average marginal component effects, the discernment of conditional effects based on respondent and profile characteristics, and marginal mean estimates. Additionally, insights into interpreting results and their implications for decision-making will be imparted. Lastly, you will be equipped with effective visualization techniques to convey findings to stakeholders.
By the end of the course, you will be equipped with the skills and knowledge to independently run your own conjoint experiments. You will understand the intricacies of experimental design, survey implementation, data analysis, and result visualization, enabling you to make informed decisions based on multidimensional preferences.
Computing
The methods you will learn in this seminar can be applied in any software package. We will primarily walk through the analysis in R, but resources (e.g., replication code and examples) will also be provided for participants who prefer to use Stata instead.
For R, you are strongly encouraged to use a computer with the most recent version of R installed. It is also recommended to download and install RStudio, a free front-end for R that makes it easier to work with.
For Stata, any version 14 or higher can be used to replicate the examples. Seminar participants who are not ready to purchase Stata can take advantage of StataCorp’s 30-day software return policy.
For the survey design examples, we will use the software platform Qualtrics. You are strongly encouraged to create a Qualtrics account prior to the beginning of the course. If your employer, school, or another organization you belong to has a license with Qualtrics, you can often get an account with many premium features at no expense. To sign up under a company, university, or other organization, you will need that organization’s branded Qualtrics URL. You can get this from a colleague, professor, your organization’s website, or by asking Qualtrics Support. If your organization doesn’t have a license, you can sign up for a free account to test out Qualtrics for this course. You can always upgrade this account later if you want to add more features. See here for details.
The methods you will learn in this seminar can be applied in any software package. We will primarily walk through the analysis in R, but resources (e.g., replication code and examples) will also be provided for participants who prefer to use Stata instead.
For R, you are strongly encouraged to use a computer with the most recent version of R installed. It is also recommended to download and install RStudio, a free front-end for R that makes it easier to work with.
For Stata, any version 14 or higher can be used to replicate the examples. Seminar participants who are not ready to purchase Stata can take advantage of StataCorp’s 30-day software return policy.
For the survey design examples, we will use the software platform Qualtrics. You are strongly encouraged to create a Qualtrics account prior to the beginning of the course. If your employer, school, or another organization you belong to has a license with Qualtrics, you can often get an account with many premium features at no expense. To sign up under a company, university, or other organization, you will need that organization’s branded Qualtrics URL. You can get this from a colleague, professor, your organization’s website, or by asking Qualtrics Support. If your organization doesn’t have a license, you can sign up for a free account to test out Qualtrics for this course. You can always upgrade this account later if you want to add more features. See here for details.
Who should register?
This seminar is for you if you want a hands-on introduction to conjoint analysis and have a basic statistical background and familiarity with regression. It is helpful for graduate students, applied researchers in industry, academia, government, and others who want to learn these methods for the first time, as well as for researchers who are familiar with the methods but want to learn contemporary techniques now widely available for conducting and analyzing conjoint experiments. Note that the course assumes a good working knowledge of linear regression at the level of introductory textbooks like Wooldridge’s Introductory Econometrics or Lewis-Beck’s Applied Regression.
This seminar is for you if you want a hands-on introduction to conjoint analysis and have a basic statistical background and familiarity with regression. It is helpful for graduate students, applied researchers in industry, academia, government, and others who want to learn these methods for the first time, as well as for researchers who are familiar with the methods but want to learn contemporary techniques now widely available for conducting and analyzing conjoint experiments. Note that the course assumes a good working knowledge of linear regression at the level of introductory textbooks like Wooldridge’s Introductory Econometrics or Lewis-Beck’s Applied Regression.
Seminar outline
Day 1: Introduction and data analysis in conjoint experiments
- Introduction to conjoint analysis
- Motivation for conjoint analysis
- Understanding multidimensional preferences
- Exploring practical applications
- Analyzing data from conjoint experiments
- Data formats and structures
- Key quantities of interest
- Average Marginal Component Effects (AMCEs)
- Marginal means
- Conditional AMCEs based on respondent and profile characteristics
- Visualizations and their interpretation
Day 2: Designing conjoint experiments
- General design principles
- Types of choice tasks and number of profiles
- Selection of attributes and attribute values
- Randomization schemes
- Outcome measures
- Practical design considerations
- Best practices for designing effective conjoint experiments
- Case studies and examples
Day 3: Implementing conjoint experiments
- Implementation strategies
- Questionnaire and randomization implementation
- Best practices for data collection
- Ensuring data quality and reliability
Day 1: Introduction and data analysis in conjoint experiments
- Introduction to conjoint analysis
- Motivation for conjoint analysis
- Understanding multidimensional preferences
- Exploring practical applications
- Analyzing data from conjoint experiments
- Data formats and structures
- Key quantities of interest
- Average Marginal Component Effects (AMCEs)
- Marginal means
- Conditional AMCEs based on respondent and profile characteristics
- Visualizations and their interpretation
Day 2: Designing conjoint experiments
- General design principles
- Types of choice tasks and number of profiles
- Selection of attributes and attribute values
- Randomization schemes
- Outcome measures
- Practical design considerations
- Best practices for designing effective conjoint experiments
- Case studies and examples
Day 3: Implementing conjoint experiments
- Implementation strategies
- Questionnaire and randomization implementation
- Best practices for data collection
- Ensuring data quality and reliability
Payment information
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.