Examples of using Probability sampling in English and their translations into Dutch
{-}
-
Colloquial
-
Official
-
Ecclesiastic
-
Medicine
-
Financial
-
Computer
-
Ecclesiastic
-
Official/political
-
Programming
After 2007 all longitudinal data shall be based on probability sampling.
However, perfect probability sampling basically never happens in the real world.
Currently, the dominant theoretical approach to representation is probability sampling.
Figure 3.6: Probability sampling in practice and non-probability sampling are both large, heterogeneous categories.
The first era of survey research was characterized by area probability sampling and face-to-face interviews.
In the future, I expect that non-probability sampling will get better and cheaper while probability sampling will get worse and more expensive.
Some people find it surprising that this is true even when there is perfectly executed probability sampling.
Classic book-length treatment of standard probability sampling and estimation are Lohr(2009)(more introductory)
was characterized by random digit dialing(RDD) probability sampling and telephone interviews.
The main difference between probability and non-probability sampling is that with probability sampling everyone in the population has a known probability of inclusion.
2007 shall be based on probability sampling and half on quota samples. .
When data are collected with a probability sampling method that has been perfectly executed,
allowing transition periods for Germany during which it moves to full use of probability sampling for both cross-sectional and longitudinal data.
Germany shall supply data of which 25% shall be based on probability sampling and 75% shall be based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008.
For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data(data for years 2005 and 2006) based on probability sampling and two thirds based on quota samples. .
Thus, rather than thinking of probability sampling as a realistic model of what actually happens in the world, it is better to think of probability sampling as a helpful, abstract model,
Probability samples are those where all people have a known, non-zero probability of inclusion, and the simplest probability sampling design is simple random sampling where each person has equal probability of inclusion.
Probability samples and non-probability samples are not that different in practice;
These new approaches can be used with either probability samples or non-probability samples. .
In the same way that researchers weight responses from probability samples, they can also weight responses from non-probability samples. .
First, as probability samples have become increasingly difficult to do in practice, the line between probability samples and non-probability samples is blurring.
Although the weighting of the probability sample and of the non-probability sample are the same mathematically(see technical appendix),
The trick of sample matching is to select samples from a dirty panel in a way that produces samples that look like probability samples.
estimates from well-conducted non-probability samples are probably better than estimates from poorly-conducted probability samples.
This strong theoretical guarantee is why advocates of probability samples find them so attractive.
In particular, they used post-stratification, a technique that is also widely used to adjust probability samples that have coverage errors and non-response.
So that you can compare your estimates to those derived from a probability sample, please copy the question text
The reason that this assumption is needed for probability samples in practice is that probability samples have non-response, and the most common method for
Sometimes researchers have found that probability samples and non-probability samples yield estimates of similar quality(Ansolabehere
Both non-probability samples and probability samples vary in their quality, and currently it is likely the case that most estimates from probability samples are more trustworthy than estimates from non-probability samples. .