Related Experiment Video
Updated: Aug 7, 2026
06:54
Methods for Presenting Real-world Objects Under Controlled Laboratory Conditions
Published on: June 21, 2019
Test-retest reliability of willingness to pay
1Department of Community Health Sciences, University of Calgary, Canada. ashiell@ucalgary.ca
Summary
Assessing willingness to pay reliability showed acceptable, but not substantial, results. Participant responses varied significantly over time, indicating potential shifts in stated willingness to pay.
Area of Science:
- Health Economics
- Behavioral Economics
- Psychometrics
Background:
- Establishing reliable willingness to pay (WTP) values is crucial for economic evaluations in healthcare.
- Existing methods require rigorous assessment of their test-retest reliability within population samples.
Purpose of the Study:
- To evaluate the test-retest reliability of a specific method for eliciting willingness to pay values.
- To identify sources of variation and potential biases in willingness to pay assessments over time.
Main Methods:
- A survey was conducted with a randomly selected population sample using face-to-face interviews.
- Willingness to pay for a hypothetical intervention was assessed on three occasions over 5 weeks.
- Intraclass correlation and generalizability analysis were used to assess reliability.
Main Results:
- The test-retest reliability of the willingness to pay method was found to be acceptable, but not substantial.
- A statistically significant shift in mean willingness to pay values occurred between the first and second assessments.
- Participants represented the greatest source of variation, with a notable time-participant interaction suggesting answer changes.
Conclusions:
- The assessed willingness to pay method demonstrates acceptable, though not ideal, test-retest reliability.
- Participant variability and potential changes in responses over time are significant factors influencing the stability of willingness to pay values.
- Further research may be needed to refine methods for capturing stable willingness to pay in population studies.
Related Concept Videos
01:29Reliability and Validity
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
01:09Wilcoxon Signed-Ranks Test for Matched Pairs
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
01:19Testing a Claim about Standard Deviation
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
01:21Wilcoxon Rank-Sum Test
The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a nonparametric test used to determine if there is a significant difference between the distributions of two independent samples. This test is designed specifically for two independent populations and has the following key requirements:
00:57Behrens–Fisher Test
The Behrens-Fisher test is a statistical method designed to address the Behrens-Fisher problem, which arises when comparing the means of two normally distributed populations with unequal variances. Unlike the Student's t-test, which assumes equal variances, the Behrens-Fisher test allows for mean comparison without this restrictive assumption. This flexibility makes it particularly valuable in scenarios where two independent samples exhibit normality but lack variance homogeneity.
This test is...
This test is...
01:21Friedman Two-way Analysis of Variance by Ranks
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures from...