Editing Snowball sampling (section)

==Improvements==

Snowball sampling is a recruitment method that employs research into participants' social networks to access specific populations. According to research mentioned in the paper written by [[Kath Browne]],<ref>{{cite journal | last1=Browne| first1= Kath | title= Snowball sampling: using social networks to research non-heterosexual women| journal= International Journal of Social Research Methodology | year= 2005| volume= 8 | issue= 1| pages= 47–60 | doi= 10.1080/1364557032000081663 | s2cid= 143873466 }}</ref> using social networks to research is accessible. In this research, Kath Browne used social networks to research non-heterosexual women. Snowball sampling is often used because the population under investigation is hard to approachable either due to low numbers of potential participants or the sensitivity of the topic. The author indicated the recruitment technique of snowball sampling, which uses interpersonal relations and connections within people. Due to the use of social networks and interpersonal relations, snowball sampling forms how individuals act and interact in focus groups, couple interviews and interviews. As a result, snowball sampling not only results in the recruitment of particular samples, use of this technique produces participants'accounts of their lives. To help mitigate these risks, it is important to not rely on any one single method of sampling to gather data about a target sector. In order to most accurately obtain information, a company must do everything it possibly can to ensure that the sampling is controlled. Also, it is imperative that the correct personnel is used to execute the actual sampling, because one missed opportunity could skew the results.

===Respondent-driven sampling===
A new approach to the study of hidden populations. It is effectively used to avoid bias in snowball sampling. Respondent-driven sampling involves both a field sampling technique and custom estimation procedures that correct for the presence of homophily on attributes in the population. The respondent-driven sampling method employs a dual system of structured incentives to overcome some of the deficiencies of such samples. Like other chain-referral methods, RDS assumes that those best able to access members of hidden populations are their own peers.<ref>{{Cite web |title=What is Respondent Driven Sampling ? |url=http://www.respondentdrivensampling.org/reports/RDSsummary.htm |access-date=2022-11-17 |website=respondentdrivensampling.org}}</ref>

===Peer Esteem Snowballing (PEST)===
Peer Esteem Snowballing is a variation of snowball sampling, useful for investigating small populations of expert opinion. Its proponents<ref name="Dimitrios">{{cite journal| author= Dimitrios C. Christopoulos |year=2010 |title= Peer Esteem Snowballing: A methodology for expert surveys}}</ref> argue that it has a number of advantages relative to other snowballing techniques:
# reduces the selection bias inherent in initial seed samples for a snowball by advocating for a nominations phase that objectively identifies contact seeds for the first wave; 
# by analysing network data it provides an estimate of the population size, unbiased by any researcher defined population boundary; 
# by reporting the estimate of the sample size vis a vis the population, it provides a measure of relative significance (optimal sampling data can be reported in this context); 
# through a network analysis of referrals it allows for identifying clusters of experts that may be instrumental in explain variations in their response profile; 
# allows for a referrals nominations strategy that, in certain cases, could improve response rates, while the nominations strategy acts as an ultimate validation of expertise for informants and therefore improves content validity.