Chapter 10: Data Collection Flashcards

1
Q

Types of Error

A
sampling error
noncoverage error
nonresponse error
response error
office  error
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2
Q

Sampling Error

A

Difference between results obtained for a sample and the results we would have obtained had we gathered info from the whole population.
easy to reduce: increase sample size or calculate the margin of sampling error

most manaageable

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3
Q

Noncoverage Error

A

error due to the failure to include some elements of the defined target population in the sampling frame
a sampling frame problem.

ways to reduce: improve quality of sampling frame.

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4
Q

Nonresponse Error

A

error from failing to obtain information from some elements of the population that were selected and designated for the sample.
when data is not collected from all respondents selected for sample.
Two main sources: refusals & not-at-homes.

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5
Q

refusals

A

nonresponse error resulting because some designated respondents refuse to participate in the study
ex. cultural differences, lack of time, contacting respondents at inappropriate time, and lack of interest in subject matter.

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6
Q

not at homes

A

nonresponse error that arises when respondents are not at home when the interviewer calls.
ex. movement of landline to cellphone and caller ID
use callbacks

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7
Q

Response Error

A

error that occurs when an individual provides an inaccurate response, consciously or subconsciously, to a survey item.

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8
Q

Questions useful for considering the different ways response errors can affect individuals’ responses.

A

does the respondent understand the question.
does the respondent know the answer to the question.
is the respondent willing to provide the true answer to the question?
is the wording of the question or the situation in which it is asked likely to bias the response.

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9
Q

Office Errors

A

after data is collected.

error due to data editing,coding, or analysis errors.

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10
Q

Total error

A

total error, rather than any single type of error is the key in a research question.

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11
Q

Response rate

A

the number of completed interview with responding units divided by the number of eligible responding units in the sample.
two functions:
1allows an assessment of the potential influence of nonresponse error
2. response rate serves as an indicator of the overall quality of a data collection effort.

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12
Q

calculate response rate

A

number of completed interviews with responding units divided by number of eligible responding units in the sample

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13
Q

Web Based and Mail Surveys Response Rate

A

straightforward response rate,

take number of usable surveys divided by sample element attempted minus those addresses that were invalid.

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14
Q

Telephone Surveys with no eligibility requirement Response Rate

A

little more complicated
no eligibility requirement
attempted contacts into three groups: completed interviews, refusals, and not at homes.

RR= number of completed interviews divided by number of completed interviews+number of refusals+ number of not at homes

wrong numbers and non working numbers do not count

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15
Q

Telephone Surveys with eligibility requirement response rate

A

some householders are ineligible.
count completed interviews, refusals, not at homes and ineligible response units.
need to adjust the response rate to account for this ineligibility
RR= number of completed interviews divided by number of completed interviews + E% * (number of refusals + number of not at homes)

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16
Q

Eligibility percentage E%

A

E%= number of completed interviews/ number of completed interviews + ineligible

17
Q

Improving Response Rates

A
  • more interesting topic is to subject the better, cant change topic but can make can consider different approachers for introducing and framing the issue under study
    1. survey length
    2. guarantee of confidentiality or anonymity
    3. interviewer characteristics and training
    4. personalization
    5. response incentives
    6. follow up surveys.
18
Q
  1. discuss at least five ways in which response rates might be improved.
A

Making the data collection instrument and procedure as interesting and short as possible
Guaranteeing confidentiality or anonymity to respondents
Carefully choosing and training interviewers
Personalizing data collection forms as much as possible
Providing incentives
Sending follow up surveys.