Improved Estimation of Poisson Rate Distributions Through a Multimode Survey Design
Bibliographic Data
| ID | 2330996 |
|---|---|
| Authors | Marcin Hitczenko (0000-0001-9168-1515, Federal Reserve Bank of Boston, corresponding author) |
| Year | 2022 |
| Volume | 51 |
| Issue | 2 |
| Pages | 699-727 |
| Publication date | 2022-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sociological Methods & Research (JOURNAL) |
| Journal identifiers | ISSN: 0049-1241 • E-ISSN: 1552-8294 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/0049124119882465 |
| OpenAlex | W4231468147 |
| Language | EN |
| References cited | 27 |
Researchers interested in studying the frequency of events or behaviors among a population must rely on count data provided by sampled individuals. Often, this involves a decision between live event counting, such as a behavioral diary, and recalled aggregate counts. Diaries are generally more accurate, but their greater cost and respondent burden generally yield less data. The choice of survey mode, therefore, involves a potential trade-off between bias and variance of estimators. We use a case study comparing inferences about payment instrument use based on different survey designs to illustrate this dilemma. We then use a simulation study to show how and under what conditions a hybrid survey design can improve efficiency of estimation, in terms of mean-squared error. Overall, our work suggests that such a hybrid design can have considerable benefits, as long as there is nontrivial overlap in the diary and recall samples
Econometrics · Economics · Estimator · Mean squared error · Negative binomial distribution · Poisson distribution · Respondent · Statistics · Survey data collection · Variance (accounting) · Computer Science · Economic and Environmental Valuation · Mathematics · Survey Methodology and Nonresponse · Survey Sampling and Estimation Techniques
Measurement Error in Survey Data
Limits to the measurement of habitual physical activity by questionnaires
Scaling regression inputs by dividing by two standard deviations
Inference from Iterative Simulation Using Multiple Sequences
Survey Errors and Survey Costs
A comparison of recall and diary food expenditure data
Sensitive questions in surveys
Using New Technologies for Time Diary Data Collection
Measuring Household Work
| Highly cited | No |
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