scholarly journals Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

2014 ◽  
Vol 22 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Jens Hainmueller ◽  
Daniel J. Hopkins ◽  
Teppei Yamamoto
Keyword(s):  
Causal Inference ◽  
Conjoint Analysis ◽  
Stated Preference ◽  
Attitudes Toward Immigrants ◽  
Multiple Treatment ◽  
Stated Preference Experiments ◽  
Randomized Design ◽  
Survey Experiments ◽  
Voter Decision Making ◽  
Identification Analysis

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show howconjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants.

scholarly journals Can Calibration Reconcile Stated and Observed Preferences?

2005 ◽  
Vol 37 (1) ◽  
pp. 237-248 ◽  
Author(s):  
F. Bailey Norwood
Keyword(s):  
Public Good ◽  
Conjoint Analysis ◽  
Lower Bounds ◽  
Stated Preference ◽  
Hypothetical Bias ◽  
Upper And Lower Bounds ◽  
Stated Preference Experiments

Hypothetical bias is a pervasive problem in stated-preference experiments. Recent research has developed two empirically successful calibrations to remove hypothetical bias, though the calibrations have not been tested using the same data or in a conjoint analysis. This study compares the two calibrations in a conjoint analysis involving donations to a public good. Results find the calibrations are biased predictors of true donations but that calibrated and uncalibrated models together provide upper and lower bounds to true donations.

scholarly journals Understanding Midwives’ Preferences for Providing Information About Newborn Bloodspot Screening

2018 ◽  
Vol 3 (1) ◽  
pp. 238146831774617 ◽  
Author(s):  
Stuart James Wright ◽  
Fiona Ulph ◽  
Tina Lavender ◽  
Nimarta Dharni ◽  
Katherine Payne
Keyword(s):  
Conjoint Analysis ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Screening Program ◽  
Stated Preference ◽  
Information Provision ◽  
Stated Preference Survey ◽  
Newborn Bloodspot Screening ◽  
Types Of Information

Background: Understanding preferences for information provision in the context of health care service provision is challenging because of the number of potential attributes that may influence preferences. This study aimed to identify midwives’ preferences for the process and outcomes of information provision in an expanded national newborn bloodspot screening program. Design: A sample of practicing midwives completed a hybrid-stated preference survey including a conjoint analysis (CA) and discrete choice experiment to quantify preferences for the types of, and way in which, information should be provided in a newborn bloodspot screening program. Six conjoint analysis questions captured the impact of different types of information on parents’ ability to make a decision, and 10 discrete choice experiment questions identified preferences for four process attributes (including parents’ ability to make a decision). Results: Midwives employed by the UK National Health Service (n = 134) completed the survey. All types of information content were perceived to improve parents’ ability to make a decision except for the possibility of false-positive results. Late pregnancy was seen to be the best time to provide information, followed by day 3 postbirth. Information before 20 weeks of pregnancy was viewed as reducing parents’ ability to make a decision. Midwives preferred information to be provided by an individual discussion and did not think parents should receive information on the Internet. Conclusion: A hybrid stated preference survey design identified that a wide variety of information should be provided to maximize parents’ ability to make a decision ideally provided late in pregnancy or on day 3 postbirth.

scholarly journals Does Class-Based Campaigning Work? How Working Class Appeals Attract and Polarize Voters

2020 ◽  
pp. 001041402095768
Author(s):  
Joshua Robison ◽  
Rune Stubager ◽  
Mads Thau ◽  
James Tilley
Keyword(s):  
Working Class ◽  
The United States ◽  
Political Elites ◽  
Social Cleavages ◽  
Limited Effect ◽  
Ideological Position ◽  
Survey Experiments ◽  
Candidate Evaluations ◽  
Voter Decision Making

Recent elections have featured various politicians directly appealing to the working class, yet we know little about how citizens react to class appeals from candidates. We investigate this question using survey experiments conducted in the United States and Denmark. We show that symbolic class rhetoric substantially influences candidate evaluations and ultimately polarizes these evaluations across class lines. We also unpack how class appeals work and find that while they increase perceptions of representation among working class voters, they have a more limited effect on perceptions of candidates’ ideological position. Our results help explain how class affects voter decision-making and contribute to broader discussions about the role of political elites in activating social cleavages.

scholarly journals Measuring Subgroup Preferences in Conjoint Experiments

2019 ◽  
Vol 28 (2) ◽  
pp. 207-221 ◽  
Author(s):  
Thomas J. Leeper ◽  
Sara B. Hobolt ◽  
James Tilley
Keyword(s):  
Conjoint Analysis ◽  
Best Practice ◽  
Causal Interpretation ◽  
Reference Category ◽  
Subgroup Differences ◽  
Political Preferences ◽  
Randomized Design ◽  
Marginal Means ◽  
Arbitrary Sign ◽  
Multidimensional Objects

Conjoint analysis is a common tool for studying political preferences. The method disentangles patterns in respondents’ favorability toward complex, multidimensional objects, such as candidates or policies. Most conjoints rely upon a fully randomized design to generate average marginal component effects (AMCEs). They measure the degree to which a given value of a conjoint profile feature increases, or decreases, respondents’ support for the overall profile relative to a baseline, averaging across all respondents and other features. While the AMCE has a clear causal interpretation (about the effect of features), most published conjoint analyses also use AMCEs to describe levels of favorability. This often means comparing AMCEs among respondent subgroups. We show that using conditional AMCEs to describe the degree of subgroup agreement can be misleading as regression interactions are sensitive to the reference category used in the analysis. This leads to inferences about subgroup differences in preferences that have arbitrary sign, size, and significance. We demonstrate the problem using examples drawn from published articles and provide suggestions for improved reporting and interpretation using marginal means and an omnibus F-test. Given the accelerating use of these designs in political science, we offer advice for best practice in analysis and presentation of results.

Value of the Facilities and Attributes of New Heavy Rail and Bus Rapid Transit Projects in a Developing City: The Case of Lima, Peru

2003 ◽  
Vol 1835 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Manuel J. Martínez ◽  
Javier Cornejo
Keyword(s):  
No Value ◽  
Stated Preference ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Stated Preference Experiments ◽  
Operational Design ◽  
Feeder Bus ◽  
Bus Service ◽  
Heavy Rail

Preferences of heavy rail (HR) system users are studied in relation to the system’s alignment and bus connections in the context of a developing city. Stated preferences techniques are applied to estimate the monetary value of a long set of attributes of a new mass transit service: HR connected to bus rapid transit (BRT). Attributes include time, fare, bicycle storage at stations, stairways, feeder bus integration, integration with BRT, type of bus service, bus itinerary, and quality of buses. The long set of attributes deserved three stated preference experiments grouped by time and fare, characteristics of HR, and characteristics of BRT. They were linked by the common attribute of the fare. Results of the values of the attributes are presented. The value of the preference for HR is reduced to 8% when a feeder bus is not offered and the HR route does not reach downtown. The value of a feeder bus using small vehicles is higher than the value of BRT even if BRT operates with new buses and express service to downtown. Bicycle storage or escalators have no value for the prospective passenger. After the response of users to the new services is analyzed, conclusions for the operational design of the system are presented.

scholarly journals Virtual Immersive Reality for Stated Preference Travel Behavior Experiments: A Case Study of Autonomous Vehicles on Urban Roads

2018 ◽  
Vol 2672 (50) ◽  
pp. 35-45 ◽  
Author(s):  
Bilal Farooq ◽  
Elisabetta Cherchi ◽  
Anae Sobhani
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Stated Preference ◽  
Urban Streets ◽  
Stated Preference Experiments ◽  
Visual Aid

Stated preference experiments have been criticized for lack of realism. This issue is particularly visible when the scenario does not have a well understood prior reference, as in the case of research into demand for autonomous vehicles. The paper presents Virtual Immersive Reality Environment (VIRE), which is capable of developing highly realistic, immersive, and interactive choice scenarios. We demonstrate the use of VIRE in researching pedestrian preferences related to autonomous vehicles and associated infrastructure changes on urban streets in Montréal, Canada. The results are compared with predominantly used approaches: text-only and visual aid. We show that VIRE results in respondents having better understanding of the scenario and it yields more consistent results.

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