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Deciding on the sample & sample size Gaining access to data & research ethics

Topic - 3. Deciding on the sample & sample size Gaining access to data & research ethics. Deciding on the sample & sample size. Selecting samples Population, sample and individual cases. Figure 7.1 Population, sample and individual cases. Population

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Deciding on the sample & sample size Gaining access to data & research ethics

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  1. Topic - 3 Deciding on the sample& sample size Gaining access to data &research ethics

  2. Deciding on the sample & sample size

  3. Selecting samplesPopulation, sample and individual cases Figure 7.1 Population, sample and individual cases

  4. Population • The entire group under study as defined by research objectives, sometimes called the “universe” • Sampling frame • a master list of the population from which the sample is drawn • Population  Sample frame  Sample

  5. Errors in sampling • & • How to eliminate or minimize them • Sampling frame error? • Random sample error? • Non-response error?

  6. Sampling error and sampling frame error

  7. Deciding on a suitable sample size • The greater the dispersion (variance) within the population, the larger the sample must be to provide estimation precision. • The greater the desired precision of the estimate, the larger the sample must be. • The higher the confidence level in the estimate, the larger the sample must be. • The greater the number of subgroups within a sample, the greater the sample size must be, as each subgroup must meet minimum sample size requirements.

  8. Deciding on a suitable sample size (Material, in this and the following slides is from Saunders et al. (2011) • Rule of thumb: a minimum number of 30 in each category within the overall sample. And where population in the category is less than 30, take all population in that category into the sample. • Where population is higher than 10000: To ensure 95% level of certainty (for population characteristics to be represented in sample), use the following formula: n = p% x q% x {z/(e%)}2 where n = minimum sample size p% = proportion belonging to the specified category q% = proportion not belonging to the specified category z = z value (z = 1.96 for 95% level of certainty) e = margin of error (corresponding to z-value)

  9. Deciding on a suitable sample size Worked example: Question: What should be the sample size where total population of community is 4000, and researcher is interested to study the performance of a salesperson? Solution: As per requirements of the formula given on previous slide, we need to know p (proportion belonging to the specified category) and q (proportion not belonging to the specified category). If we do not know, then we will have to carry out a pilot survey and try to know how many clients receive a visit by the salesperson per week. If such a pilot survey reveals that 12 out of 30 clients receive salesperson’s visit once a week, then this means 40 percent belong to this category, and 60 percent do not; so q = 40 and p = 60. And to ensure 95% level of certainty, z = 1.96 and e = 5. Applying the formula for sample size ‘n’: n = 40 x 60 x {1.96/5}2 = 2400 (0.392)2 = 2400 (0.154) = 369.6 (Say sample size = 370)

  10. Deciding on a suitable sample size 3. Where population is less than 10000, an adjusted minimum sample size n’ is used, where n’ is: n’ = n / {1 + (n/N)} where n = minimum sample size (calculated earlier) n’ = adjusted minimum sample size N = Total population Worked example: If population is = 4000 n’ = 369.6 / {1 + (369.6/4000)} = 369.6 / {1 + (0.092)} = 369.6 / 1.092 = 338.46 (Say sample size = 339)

  11. Deciding on a suitable sample size • Incorporating for non-response: Common reasons for non-response: a. Refusal to respond b. Inability to respond c. Inability to locate respondent So, through a pilot/preliminary survey, it seems necessary to estimate the response rate. If the response rate estimates at 30 percent, the ‘actual sample size’ abbreviated as na will be then: na = (n/re) * 100 In our previous case, n = 369.60 (for more than 10000 population) or n’ = 338.46 (for less than 10000 population); then: na = (369.60/30) * 100 = 1232 or na = (338.46/30) * 100 = 1128.2

  12. Gaining access to data &research ethics

  13. Gaining access to data Types of accessa. Physical entry (or initial access): The initial level of gaining access to an organization to conduct research. b. Continuing access: Gaining agreed research access to an organization on an incremental basis. c. Cognitive access: The process of gaining access to data from intended participants. This involves participants agreeing to be interviewed or observed, within agreed limits. This is achieved through achievement of ‘informed consent’. What is ‘informed consent’? See next slide.

  14. Participant consent informed consent: Position achieved when intended participants are fully informed about the nature, purpose and use of research to be undertaken and their role within it, and where their consent to participate, if provided, is freely given.Implied consent: Position achieved when intended participants are fully informed about the nature, purpose and use of research to be undertaken and their role within it, but their consent to participate, is inferred from their participating in the research, such as by responding to a questionnaire.

  15. Problems associated with Access • Organisations may not be prepared to allocate time and resources • Requests for access may not be of sufficient interest to organizations • Failure to reach those who can give permission (contacting wrong person) • Concerns about sensitivity and confidentiality • Perceptions about the researcher’s credibility and competence

  16. Strategies to gain access • Allowing yourself sufficient time • Providing a clear account of purpose and type of access required • Overcoming organisational concerns about granting access • Identifying possible benefits to the organization of granting access • Adopting appropriate forms of communication, like writing introductory letter & providing return-envelop OR writing email • Developing Access on Incremental basis

  17. Research ethics?The appropriateness of a researcher behaviourin relation to the rights of thosewho become the subject of or are affected by the research work.The research design should notsubject the research population to embarrassment, harm or other material disadvantage.

  18. ‘Gaining access to data’and ‘maintaining ethics’ are interrelated processes, because:The ‘requirements for informed consent’ require informing participants about:‘the nature of the research’‘the requirements of taking part in research’‘implications of taking part & participants’ rights’‘the use of data collected and the way in which it will be reported’

  19. There are ethical issues that affect the research process in general, while there are ethical issues that are specific to each stage of research. ‘Respecting privacy of participants’ means:* the right of participant not to participate* the right not to be harassed or offered inducements* the right not to be contacted at unreasonable times* the right not to answer any question or set of questions or provide any related data.* ..................*..................

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