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Abstract Details
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Activity Number:
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35
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #301221 |
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Title:
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OPTIMIZING CATI WORKLOAD TO MINIMIZE DATA COLLECTION COST
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Author(s):
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Ghulam Hussain Choudhry*+
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Companies:
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Statistics Canada
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Address:
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Floor 17, R.H. Coats Bldg., , Ottawa, ON, K1A0T6, CANADA
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Keywords:
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Linear and logistic regression models ;
Optimum CATI schedule ;
Non-linear programming ;
Cost-savings
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Abstract:
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One of the main increasing challenges for Statistics Canada is to collect cost-effective data while maintaining a high level of quality. Paradata research has been useful in improving the current data collection processes and practices. The research carried out with paradata suggested that collection resources are currently not always optimally allocated with respect to the assigned workload and the corresponding expected productivity for computer-assisted telephone interview (CATI) surveys. In this paper, models to predict the probability that a telephone call would result in a completed questionnaire as a function of time of day, and resources spent to date were developed. The parameters estimated from these models are used as input to optimize call scheduling. The potential cost savings of this approach is illustrated by applying the theory to a large scale household survey.
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Authors who are presenting talks have a * after their name.
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