Examples of using Non-probability sampling in English and their translations into Greek
{-}
-
Colloquial
-
Official
-
Medicine
-
Ecclesiastic
-
Financial
-
Official/political
-
Computer
Non-probability sampling includes a huge variety of designs(Baker et al. 2013).
The alternative to probability sampling is non-probability sampling.
In general, there is a cost-error trade-off with non-probability sampling being lower cost but higher error.
But, non-probability sampling has a terrible reputation among social scientists and statisticians.
Thus, it appears that probability vs non-probability sampling offers a cost-quality trade-off(Figure 3.6).
The digital age is making probability sampling in practice harder andis creating new opportunities for non-probability sampling.
Third era 2000- present Non-probability sampling Computer-administered Surveys linked to other data.
Moving beyond quota sampling, more modern approaches to controlling the non-probability sampling process are now possible.
In other words, in non-probability sampling methods not everyone has a known and nonzero probability of inclusion.
Despite these debates,I think there are two reasons why the time is right for social researchers to reconsider non-probability sampling.
However, well-done non-probability sampling can produce better estimates than poorly-done probability sampling. .
However, as I will describe below,changes created by the digital age mean that it is time for researchers to reconsider non-probability sampling.
Figure 3.6: Probability sampling in practice and non-probability sampling are both large, heterogeneous categories.
These newer methods are different enough from the methods that caused problems in the past that I think it makes sense to think of them as“non-probability sampling 2.0.”.
A complementary strategy for working with non-probability sampling is to have more control over the data collection process.
These newer methods are different enough from the methods that caused problems in the past that I think it makes sense to think of them as“non-probability sampling 2.0.”.
Because of these long-term trends,I think that non-probability sampling will become increasingly important in the third era of survey research.
At the same time that there has been growing difficulties for probability sampling methods,there has also been exciting developments in non-probability sampling methods.
In the future, I expect that non-probability sampling will get better and cheaper while probability sampling will get worse and more expensive.
In particular, probability sampling has been getting hard to do in practice, and non-probability sampling has been getting faster, cheaper, and better.
There are a variety of styles of non-probability sampling methods, but the one thing that they have in common is that they cannot easily fit in the mathematical framework of probability sampling(Baker et al. 2013).
Going forward, if you are trying to decide between using a probability sampling approach and a non-probability sampling approach you face a difficult choice.
The simplest example of a partially controlled non-probability sampling process is quota sampling, a technique that goes back to the early days of survey research.
Although things arenot totally settled yet, I expect that the third era of survey research will be characterized by non-probability sampling and computer-administered interviews.
In fact, non-probability sampling is associated with some of the most dramatic failures of survey researchers, such as the Literary Digest fiasco(discussed earlier) and the incorrect prediction about the US presidential elections of 1948(“Dewey Defeats Truman”)(Mosteller 1949; Bean 1950; Freedman, Pisani, and Purves 2007).
Although both approaches were used in the early days of sampling, probability sampling has come to dominate, andmany social researchers are taught to view non-probability sampling with great skepticism.
Non-probability sampling methods have a terrible reputation among social researchers and they are associated with some of the most dramatic failures of survey researchers, such as the Literary Digest fiasco(discussed earlier) and“Dewey Defeats Truman,” the incorrect prediction about the US presidential elections of 1948(figure 3.6).
Although things are not yet settled, I expect that the third era of survey research will be characterized by non-probability sampling, computer-administered interviews, and the linkage of surveys to big data sources(table 3.1).
First, unadjusted non-probability samples can lead to bad estimates;?