Comparision of Snowball Sampling and Sequential Sampling Technique

Etikan, İlker

doi:10.15406/bbij.2016.03.00055

Cited by 356 publications

(256 citation statements)

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“…Basing on assumption means one will generate inappropriate generalization of the population [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Resultsmentioning

confidence: 99%

Sampling and Sampling Methods

Etikan¹

2017

BBIJ

Self Cite

637

316

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This article is on representation of basis and the basis selection of techniques. The representation of this two is performed either by the method of probability random sampling or by the method of non-probability random sampling. The selection of random type is done by probability random sampling while the non-selection type is by non-probability probability random sampling. This selection of techniques is talking about either without control (unrestricted) or with control (restricted) when individually the element of each sample is selected from a given totality, the drawn of sample element goes with unrestricted while all the other types of the sampling is to be considered as a restricted sampling. IntroductionThe aim of this article is to discuss about the sampling and sampling technicality. Statistical agencies prefer the probability random sampling. In business, companies, marketers mostly relay on non-probability sampling for their research, the researcher prefers that because of getting confidence cooperation from his respondent especially in the business sample survey like consumer price index. In New Zealand the proficient set on consumer price index committee advice the government on the their CPI. Non-Probability SamplingNon-probability sampling is a sampling procedure that will not bid a basis for any opinion of probability that elements in the universe will have a chance to be included in the study sample. We are going to see from diverse method of five different sampling considering the non-random designs. which are; Quota sampling, Accidental sampling, Judgemental sampling or Purposive sampling, Expert sampling, Snowball sampling, Modal instant sampling .From the listed the researcher has to deliberately select items to be sample. This type of sampling is costly in application. Types of Non-Probability Random Sampling Quota samplingThe researcher here is ease of access to his sample population by using quota sample, his tallying will be at his convenience guide by some evident of characteristic, such as sex, race, based on population of interest. The sample selection is by the convenient door of the researcher, Any person or individual mistakenly seen with the same characteristics will be asked pertaining the subject of the research for inclusion. It will flow in the same manner until the desired number is achieved. Quota sampling is of two types; first proportionate quota sampling represent the characteristics of major population by sampling a proportional total. Example if we are interested in studying population of 40 percent of females and 60 percent of males. We need a 100 size for the sample; the selection will not stop unless the target is hit before stopping. Meanwhile when the exact number of either male or female is gotten, say 40 female, the selection for the male has to continue in the same process, eventually when a legitimate female comes across, it will not be selected because there number is already completed.The major setback of purposive sampling is that you necessity to...

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“…Basing on assumption means one will generate inappropriate generalization of the population [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Resultsmentioning

confidence: 99%

Sampling and Sampling Methods

Etikan¹

2017

BBIJ

Self Cite

637

316

View full text Add to dashboard Cite

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“…Whilst this strategy enhanced successful recruitment in their study, it appeared to have contributed to the selection bias observed in the study leading to a homogenous sample of Jamaican men (Nanton & Dale, ). The risk of selection bias often associated with snowball sampling was minimised in this study by complementing it with additional recruitment strategies (Etikan et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…Snowball sampling thrives on the use of personal relationship networks to access participants who otherwise may not have been aware of, or participated in a study (Etikan, Alkassim, & Abubakar, 2016;Wohl et al, 2017). Although prone to selection bias which may result from over-representation of members of a particular participant's network (Etikan et al, 2016), snowball sampling has been widely acknowledged as useful in promoting research participation among "hard to reach" populations in a costeffective and timely manner (Richards & Morse, 2007;Sadler, Lee, Lim, & Fullerton, 2011;Wohl et al, 2017). Nanton and Dale (2011) successfully used snowball sampling to recruit African-Caribbean men with CaP (n = 16) into their qualitative study.…”

Section: Snowball Samplingmentioning

confidence: 99%

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“Hard to reach, but not out of reach”: Barriers and facilitators to recruiting Black African and Black Caribbean men with prostate cancer and their partners into qualitative research

et al. 2018

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Access and recruitment barriers may have contributed to the underrepresentation of Black African/Caribbean men and their partners in current psychosocial research related to prostate cancer survivors. Whilst some studies have explored recruitment barriers and facilitators from participants’ perspectives, little is known from researchers' point of view. This paper aimed to address this gap in the literature. Recruitment strategies included the following: cancer support groups, researchers’ networks, media advertisement, religious organisations, National Health Service hospitals and snowball sampling. Thirty‐six eligible participants (men = 25, partners = 11) were recruited into the study. Recruitment barriers comprised of gate‐keeping and advertisement issues and the stigma associated with prostate cancer disclosure. Facilitators which aided recruitment included collaborating with National Health Service hospitals, snowball sampling, flexible data collection, building rapport with participants to gain their trust and researcher's attributes. Findings highlight that “hard to reach” Black African/Caribbean populations may be more accessible if researchers adopt flexible but strategic and culturally sensitive recruitment approaches. Such approaches should consider perceptions of stigma associated with prostate cancer within these communities and the influence gatekeepers can have in controlling access to potential participants. Increased engagement with healthcare professionals and gatekeepers could facilitate better access to Black African/Caribbean populations so that their voices can be heard and their specific needs addressed within the healthcare agenda.

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“…The snowball sampling method is applied to recruit a purposive sample (i.e. stakeholders thought to be most important to the issue under study), whereby the researcher asks respondents to identify other stakeholders the researcher may contanct (Etikan et al 2016).…”

Section: Stakeholder Identificationmentioning

confidence: 99%

Stakeholder Analysis to Support Secondary Norway Spruce (Picea abies (L.) Karst.) Forest Conversion in the Ukrainian Carpathians

Pelyukh

Paletto²

2019

Acta Silvatica Et Lignaria Hungarica

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Stakeholder analysis is a crucial step in the participatory process to involve all groups of interests in sustainable forest management. This paper aims to develop a method of stakeholder analysis to identify and classify stakeholders involved in secondary Norway spruce (Picea abies (L.) Karst.) stand conversions. The method is based on a questionnaire survey and structured into three stages: (1) stakeholder identification; (2) analytical characterization of stakeholders; and (3) stakeholder aggregation. Stakeholders are classified according to their interest level and importance while considering the relationships among them (social network analysis). Stakeholder analysis is applied in the Ukrainian Carpathians, which is characterized by cultural and economic dependence on forest resources. The results highlight seven "supporters" and six "opponents" as well as three key stakeholders and four primary stakeholders. We propose involving up to three stakeholders from each homogeneous group to balance stakeholder contributions and enhance the democratization of the forest conversion decision-making process.adaptive complexity / Norway spruce / forest management / questionnaire survey / social network analysis / public participation Kivonat -Az érdekelt felek elemzése az Ukrán Kárpátok mesterségesen létrehozott norvég lucfenyő (Picea abies (L.) Karst.) erdeinek átalakításához. Az érdekelt felek elemzése kulcsfontosságú lépés az összes érdekcsoport tartamos erdőgazdálkodásba való bevonásának folyamatában. A tanulmány célja a mesterségesen létrehozott norvég lucfenyő (Picea abies (L.) Karst.) állomány átalakításában részt vevő érintettek azonosítására és osztályozására kifejlesztett módszer bemutatása. A módszer kérdőíves felmérésen alapul, és három szakaszra tagolódik: (1) az érdekelt felek azonosítása; (2) az érdekelt felek analitikus jellemzése; és (3) az érdekelt felek összesítése. Az érdekelt feleket érdekeltségi szintjük és jelentőségük alapján osztályozzuk, miközben figyelembe vesszük a közöttük fennálló kapcsolatokat (közösségi hálózatok elemzése). Az érdekelt felek elemzését az Ukrán Kárpátokban alkalmazzák, amelyet az erdészeti erőforrásoktól való kulturális és gazdasági függőség jellemez. Az eredmények hét "támogatót" és hat "ellenzőt", valamint három kulcsfontosságú és négy elsődleges érdekelt felet emelnek ki. Javasoljuk, hogy mindegyik homogén csoportból legfeljebb három érdekelt felet vonjanak be az érdekeltek közreműködésének kiegyensúlyozása és az erdő átalakításáról szóló döntéshozatali folyamat demokratizálásának elősegítése érdekében. adaptív komplexitás / norvég lucfenyő / erdőgazdálkodás / kérdőíves felmérés / közösségi háló elemzés / a nyilvánosság részvétele

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Comparision of Snowball Sampling and Sequential Sampling Technique

Cited by 356 publications

References 6 publications

Sampling and Sampling Methods

Sampling and Sampling Methods

“Hard to reach, but not out of reach”: Barriers and facilitators to recruiting Black African and Black Caribbean men with prostate cancer and their partners into qualitative research

Stakeholder Analysis to Support Secondary Norway Spruce (Picea abies (L.) Karst.) Forest Conversion in the Ukrainian Carpathians

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