Примери за използване на Nonresponse на Английски и техните преводи на Български
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Almost all real surveys have nonresponse;
Nonresponse bias was the second main problem with the Literary Digest poll.
Essentially all surveys suffer from nonresponse.
Readers interested in item nonresponse should see Little and Rubin(2002).
In this section, I will focus on unit nonresponse;
Eq. 3.7 shows that nonresponse will not introduce bias if any of the following conditions are met.
The trick to making estimates when there is nonresponse is to use auxiliary information.
In unit nonresponse, some people that are selected for the sample population don't respond to the survey at all.
If the people who respond are different from those who don't respond,then there can be nonresponse bias.
These extra efforts did in fact produce a lower rate of nonresponse, but they added to the cost substantially.
Nonresponse rates are much higher in commercial telephone surveys- sometimes even as high as 90%(Kohut et al. 2012).
Bethlehem(1988) offers a derivation of the bias caused by nonresponse for more general sampling designs.
These long-term trends in nonresponse mean that data collection is more expensive and estimates are less reliable.
Bethlehem(2010) extends many of the above derivations about post-stratification to include both nonresponse and coverage errors.
Nonresponse rates are much higher for commercial telephones surveys, sometimes even as high as 90%(Kohut et al. 2012).
For more on using post-stratification to adjust for nonresponse, see Smith(1991) and Gelman and Carlin(2002).
Figure 3.5: Nonresponse has been increasingly steadily, even in high-quality expensive surveys(National Research Council 2013; B. D. Meyer, Mok, and Sullivan 2015).
I will start by introducing probability sampling,then move to probability sampling with nonresponse, and finally, non-probability sampling.
These long-term trends mean that the nonresponse rate can now exceed 90% in standard telephone surveys(Kohut et al. 2012).
These techniques using auxiliary information are particularly important because, as I will show later,auxiliary information is critical for making estimates from probability samples with nonresponse and from non-probability samples.
In item nonresponse, some respondents don't answer some items(e.g., sometimes respondents don't want to answer questions that they consider sensitive).
For more on other other weighting methods for adjusting for nonresponse, see Kalton and Flores-Cervantes(2003), Brick(2013), and Särndal and Lundström(2005).
The limitations of an obsession with reducing error are illustrated by the landmark project of Scott Keeter and colleagues(2000)on the effects of expensive field operations on reducing nonresponse in telephone surveys.
The two most common reasons for unit nonresponse are that the sampled person cannot be contacted and the sample person is contacted but refuses to participate.
In conclusion, this section has provided a model for probability sampling with non-response andshown the bias that nonresponse can introduce both without and with post-stratification adjustments.
These increases in nonresponse threaten the quality of estimates because the estimates increasingly depend on the statistical models that researchers use to adjust for nonresponse.
In addition to post-stratification,other techniques for working with non-probability samples- and probability samples with coverage errors and nonresponse- include sample matching(Ansolabehere and Rivers 2013;???), propensity score weighting(Lee 2006; Schonlau et al. 2009), and calibration(Lee and Valliant 2009).