Monthly Sample Size Prediction for the Current Population Survey
Abstract Number:
2753
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
John Jones (1), Brian Shaffer (2), Timothy Trudell (3)
Institutions:
(1) US Census Bureau, DSSD, N/A, (2) US Census Bureau, N/A, (3) N/A, N/A
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
Abstract
The Current Population Survey (CPS) conducts data collection monthly using an eight-panel rotating sample. Field operations and headquarters both require a predictable sample size for planning purposes. However, various factors impact the sample size of each panel; among these factors are growth in the frame which gets added to the panels differently across time, attrition in the frame which causes a decrease in the eligible sample size across time, and post-census frame improvements which reduce that decrease in our eligible sample. In our research, we first discuss the components of the CPS sample size. Next, we attempt to model these components so that we can extrapolate the sample size months ahead. Lastly, we compare our extrapolations to observed sample sizes to evaluate the quality of our predictions.
Key words: Sample Frames, Modeling
Keywords:
Sample Frame|Modeling| | | |
Sponsors:
Survey Research Methods Section
Tracks:
Data Analysis/Modeling
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