Excerpts from the report Introduction: As response rates decline, the costs associated with how the survey will be designed, conducted and analyzed to ensure the creditability of results increase. Data collection becomes more difficult and costly, and questions are raised about the best way to address the increased nonresponse bias due to low participation rates. The following report provides an in-depth overview of NASS’s subsampling design to address nonresponse in the 2017 Census of Agriculture. The theory and methodology of subsampling in the survey methodological literature is presented, as well as examples of large, nationally representative sample surveys and censuses that use subsampling to improve response and quality metrics. ...
The National Agricultural Statistics Service (NASS) surveys agricultural operations to provide timel...
The development of large sample surveys creates new opportunities for analysis of subpopulations tha...
This paper summarizes past, current, and future work to control and measure nonsampling errors in th...
Nonsampling errors present major problems in sample surveys. While sampling errors can be estimated ...
Increasing nonresponse rates in federal surveys and potentially biased survey estimates are a growin...
The National Agricultural Statistics Service’s (NASS) primary purpose is to provide timely, accurate...
This paper describes the use of classification trees to predict survey refusals and inaccessibles. D...
The National Agricultural Statistics Service uses its annual June Area Survey (JAS) as the vehicle t...
The National Agricultural Statistics Service (NASS) surveys farmers and ranchers across the United S...
The 2002 Census of Agriculture adjusted for whole-farm nonresponse by dividing the potential farms o...
In order to target nonrespondents proactively, the National Agricultural Statistics Service (NASS) b...
In this dissertation I provide new theory and methodology to address three important problems in sam...
Each year, the National Agricultural Statistics Service (NASS) conducts the June Area Survey (JAS), ...
USDA’s National Agricultural Statistics Service (NASS) conducts the annual Agricultural Resource Man...
The National Agricultural Statistics Service (NASS) surveys farmers and ranchers across the United S...
The National Agricultural Statistics Service (NASS) surveys agricultural operations to provide timel...
The development of large sample surveys creates new opportunities for analysis of subpopulations tha...
This paper summarizes past, current, and future work to control and measure nonsampling errors in th...
Nonsampling errors present major problems in sample surveys. While sampling errors can be estimated ...
Increasing nonresponse rates in federal surveys and potentially biased survey estimates are a growin...
The National Agricultural Statistics Service’s (NASS) primary purpose is to provide timely, accurate...
This paper describes the use of classification trees to predict survey refusals and inaccessibles. D...
The National Agricultural Statistics Service uses its annual June Area Survey (JAS) as the vehicle t...
The National Agricultural Statistics Service (NASS) surveys farmers and ranchers across the United S...
The 2002 Census of Agriculture adjusted for whole-farm nonresponse by dividing the potential farms o...
In order to target nonrespondents proactively, the National Agricultural Statistics Service (NASS) b...
In this dissertation I provide new theory and methodology to address three important problems in sam...
Each year, the National Agricultural Statistics Service (NASS) conducts the June Area Survey (JAS), ...
USDA’s National Agricultural Statistics Service (NASS) conducts the annual Agricultural Resource Man...
The National Agricultural Statistics Service (NASS) surveys farmers and ranchers across the United S...
The National Agricultural Statistics Service (NASS) surveys agricultural operations to provide timel...
The development of large sample surveys creates new opportunities for analysis of subpopulations tha...
This paper summarizes past, current, and future work to control and measure nonsampling errors in th...