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NUR3300 > Exam 2 Quantitative Sampling > Flashcards

Exam 2 Quantitative Sampling Flashcards

1
Q

Population

A

group meeting a specific description

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2
Q

Target population

A

everyone who meets the criteria (very specific criteria for study)

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3
Q

accessible population

A

those who meet the criteria and who can be accessed by the researcher (who researcher has access to)

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4
Q

Sample

A

selected portion of group you are studying

-small, specifically selected to be in study

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5
Q

Elements

A

individual or basic units to be studied

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6
Q

subjects/participants

A

human elements to be studied

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7
Q

Sampling plan

A

how you will select the sample (number, eligibility, process) written description

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8
Q

What is representativeness?

A

the sample looks enough like the population to be able to GENERALIZE the sample findings to others in the population

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9
Q

How must the sample similar to the population

A

on important characteristics

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10
Q

Inclusion criteria

A

characteristics that the subject MUST possess to be in the study.

Based on notable characteristics of the target population

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11
Q

Exclusion criteria

A

characteristics that the subject MUST NOT possess

reduces questions about impact of extraneous variables on the results

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12
Q

sampling bias

A

over or under selection of subjects on any of the significant variables

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13
Q

sampling error

A

errors made in the conclusions because of sampling bias

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14
Q

Clinically relevant findings

A

Overall picture must be one closely resembling

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15
Q

Probability sampling

A

Every element(person) in the accessible population has an equal chance of being selected for inclusion in the study

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16
Q

3 conditions:

A

accessible population must be identifiable (must be able to make a list)

All elements in the accessible population must be listed (sampling frame)

Elements are chosen by random selection

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17
Q

Selection method is determined by:

A

research purpose, question, and design

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18
Q

Types:

A

simple, stratified, cluster, and systematic random sampling

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19
Q

Randomization

A

outcome of random sampling methods

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20
Q

What does randomization reduce threat of?

A

selection bias

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21
Q

Less selection bias

A

ensures a greater likeness between the sample and the target population on the focal characteristics

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22
Q

Common methods:

A
  • Draw names out of a hat
  • Use a table of random numbers
  • Flip a coin-heads in, tails out
  • Throw dice-anyone getting an even number is in, odd number is out
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23
Q

Simple random sampling

A

everyone in the accessible population has an equal chance for inclusion

24
Q

process:

A

-get a list of the accessible population
-assign everyone on the list a number
-randomly select from the list
…whatever it takes to remove brain’s ability to pick

25
Q

Difficult?

A

if it’s a large group, or when one cannot make a sampling frame
-to use when one does not know who will be admitted to the unit/hospital/etc meeting the focal characteristics

26
Q

stratified random sampling

A

select the relevant strata
(must be mutually exclusive)
-divide the population into subgroups or strata based on some important feature.
-decide on how many from each strata
-use random sampling to select that number from each strata

27
Q

Difficult?

A

when accessible population for one strata makes it small or difficult to find

28
Q

Cluster or multistage sampling

A

clusters narrow down large unwieldy population (Still RANDOM)

  • Identify important characteristics
  • look for logical subsets (clusters) of the large population
  • randomly select your clusters and sub-clusters
  • randomly select subjects from you clusters
29
Q

systematic sampling

A

create a list of the accessible population
-divide the number of people available by the number of subjects needed to get ‘k’
example: 500 people/50 needed=10
-draws every ‘kth’ element
example: the above answer of 10
means every 10th person on the list
-randomly pick a starting point on your list\
-select every kth person (10th person) until you have your sample.

30
Q

nonprobability sampling

A

less likely to give you a representative sample

-increased seelction bias

31
Q

when use nonprobability?

A

when sampling frame cannot be determined

32
Q

types:

A

convenience, quota, purposive or judgement, snowball, theoretical, expert

33
Q

Convenience sampling

A

Use any subjects

  • whatever is available to you
  • volunteers
    ex: mall surveyors
34
Q

Convenience sampling: control sampling bias

A

collecting data on subject characteristics and then making comparisons of those characteristics

35
Q

Quota sampling

A
  • similar to stratified random sampling WITHOUT the random selection steps
  • decide on variables of interest
  • decide on the strata to select from
  • conveniently select from each strata (instead of randomly select)
36
Q

Purposive sampling

A
  • base selection on specific criteria

- inclusion relies on researcher’s judgment

37
Q

When is it used?

A

More often used in qualitative than quantitative designs but may be used in quantitative descriptive studies

38
Q

Snowball sampling

A

A type of purposive sampling

39
Q

How are subjects obtained?

A

By referral

40
Q

How is this useful?

A

Helps to obtain key people or those who might be difficult to find under normal circumstances

41
Q

Theoretical sampling

A

Used mostly when trying to develop an explanation of a phenomena

42
Q

Two step process

A
  • Collect data
  • develop initial explanation (theory)
  • purposefully identify additional subjects to determine if the explanation (theory) continues to hold up
43
Q

Expert sampling

A

Use when looking for consensus on an issue

44
Q

When to use?

A

Creating research tools

It helps measure content validity

45
Q

Sample size

A

Samples that are homogeneous (similar) on the desired characteristic do not need to be as large as samples that are heterogeneous (dissimilar) on the desired characteristic.

46
Q

How does reliability/validity effect sample size

A

The more reliable and valid the tools, the smaller the sample size needed

47
Q

General rules of thumb for sample size:

A

Minimum of 30 for one group study

  • if doing group comparisons, need at least 30 in each group
  • if more than one I.V., need at least 10 for each I.V.
48
Q

Also need to consider for sample size:

A

Refusal rate since not everyone will want to participate

  • consider your likely “drop out” or attrition rate
  • consider “power” of your study
49
Q

Statistical power

A

looks at your assurance that you are correct in rejecting the null hypothesis

  • need to consider your alpha (significance lvl), your effect size, and desired power level
  • if you set your alpha at .05, you are looking for a 95% chance of correctly rejecting the null hypothesis
  • must decide if you think the I.V. will have a large, medium, or small impact or effect on the D.V.
  • generally wish a power level of at least .8
  • use your alpha, effect size, and desired power to calculate the number of subjects you need for each individual statistical procedure used in the study
50
Q

Recruitment and retention

A

IRB approval required before approaching any potential subject

51
Q

How can you recruit?

A

By using personal contact on the unit, contact manager or staff member on the unit, flyers, ads on radio or TV…etc…

52
Q

Requirements for recruitment

A

All printed documents must be at maximum of 5th grade level in appropriate language

  • incentives should not be bribes
  • determine who meets likely the criteria
  • be professional, personable, and patient
  • explain exactly how they will participate such as in person, survey monkey, mail in responses, etc…
  • provide for informed consent
  • have informed consent form signed if needed
53
Q

Do you always need a SIGNED informed consent form?

A

NO

54
Q

Informed consent must include:

A
  • title of study
  • invitation to participate
  • basis of subject selection
  • purpose of study
  • explanation of procedures
  • benefits and risks
  • alternatives to participation
  • financial obligations
  • confidentiality assurances
  • HIPAA disclosure of how their data will be protected
  • subject withdrawal procedures
  • offer to answer questions with contact information provided
  • consent statement
  • identification of researchers
  • signature and date, if required
55
Q

Who are the Vulnerable Populations?

A
  • Pregnant women
  • Fetuses
  • Children
  • Elderly
  • Mentally challenged
  • Prisoners
  • Other marginalized individuals based on socioeconomics, ethnicity, gender, education, etc.

NUR3300 (20 decks)

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