Replication Data for: Relaxing the No Liars Assumption in List Experiment Analyses
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The analysis of list experiments depends on two assumptions, known as 'no design effect' and 'no liars'. The no liars assumption is strong and may fail in many list experiments. I relax the no liars assumption in this paper, and develop a method to provide bounds for the prevalence of sensitive behaviors or attitudes under a weaker behavioral assumption about respondents' truthfulness toward the sensitive item. I apply the method to a list experiment on the anti-immigration attitudes of California residents and on a broad set of existing list experiment datasets. The prevalence of different items and the correlation structure among items on the list jointly determine the width of the bounds estimates. In particular, the bounds tend to be narrower when the list consists of items of the same category, such as multiple groups or organizati' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["item count technique","list experiment","sensitive question"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The analysis of list experiments depends on two assumptions, known as 'no design effect' and 'no liars'. The no liars assumption is strong and may fail in many list experiments. I relax the no liars assumption in this paper, and develop a method to provide bounds for the prevalence of sensitive behaviors or attitudes under a weaker behavioral assumption about respondents' truthfulness toward the sensitive item. I apply the method to a list experiment on the anti-immigration attitudes of California residents and on a broad set of existing list experiment datasets. The prevalence of different items and the correlation structure among items on the list jointly determine the width of the bounds estimates. In particular, the bounds tend to be narrower when the list consists of items of the same category, such as multiple groups or organizati' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The analysis of list experiments depends on two assumptions, known as 'no design effect' and 'no liars'. The no liars assumption is strong and may fail in many list experiments. I relax the no liars assumption in this paper, and develop a method to provide bounds for the prevalence of sensitive behaviors or attitudes under a weaker behavioral assumption about respondents' truthfulness toward the sensitive item. I apply the method to a list experiment on the anti-immigration attitudes of California residents and on a broad set of existing list experiment datasets. The prevalence of different items and the correlation structure among items on the list jointly determine the width of the bounds estimates. In particular, the bounds tend to be narrower when the list consists of items of the same category, such as multiple groups or organizati
item count technique; list experiment; sensitive question