Post-Stratification and Calibration—A Synthesis

By Li‐Chun Zhang. 2000

54 citations recorded by the source corpus.

Subfields: Statistics and Probability, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/fdbf7e7c9f04834998d53ac92d4b1ac7f837fafd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

1. E. Flores
2. H. K. Cordell
3. C. Betz
4. Gary T. Green
5. J. Escobal

In Water Science and Technology

1. E. Flores
2. H. K. Cordell
3. C. Betz
4. Gary T. Green
5. J. Escobal

Citations in the corpus

• Technical Note No. 3. An Assessment of the Young Lives Sampling Approach in Peru. (2008, background): “Post-Stratification can improve the accuracy of survey estimates both by reducing biases and by increasing precision (Zhang 2000).”
• Recreation and the Environment as Cultural Dimensions in Contemporary American Society (2002, methodology): “This type of weighting procedure, referred to as post-strati cation (Holt & Smith, 1979), is the most widely accepted method for adjusting sample proportions to mirror population distributions (Zhang, 2000).”