Chapter 10 Flashcards

1
Q

The aggregate of cases in which a researcher is interested

A

Population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Selection of a portion of the population (a sample) to represent the entire population

A

Sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Subpopulations of a population (e.g., male/female)

A

Strata

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

The entire population of interest

A

Target Population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

The portion of the target population that is accessible to the researcher, from which a sample is drawn.

A

Accessible population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

A sample whose key characteristics closely approximate those of the target population—a sampling goal in quantitative research.

A

Representative sample

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

HOw is representative sampling achieved?

A

Probability sampling
Homogeneous populations
Larger samples

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

The systematic over- or under-representation of segments of the population on key variables when the sample is not representative.

A

Sampling bias

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Differences between sample values and population values.

A

Sampling error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Involves random selection of elements: each element has an equal, independent chance of being selected

A

Probability sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Does not involve selection of elements at random

A

Non-probability sample

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Examples of non-probability sampling

A

Convenience sampling
Snowball (network) sampling
Quota sampling
Purposive sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Use of the most conveniently available people
Most widely used approach by quantitative researchers
Most vulnerable to sampling biases

A

Convenience Sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Referrals from other people already in a sample
Used to identify people with distinctive characteristics
Used by both quantitative and qualitative researchers; more common in qualitative.

A

Snowball Sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Convenience sampling within specified strata of the population.
Enhances representativeness of sample.
Infrequently used, despite being a fairly easy method of enhancing representativeness.

A

Quota Sampling

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Involves taking all of the people from an accessible population who meet the eligibility criteria over a specific time interval, or for a specified sample size
A strong nonprobability approach for “rolling enrollment” type accessible populations
Risk of bias low unless there are seasonal or temporal fluctuations

A

Consecutive Sampling

17
Q

Sample members are hand-picked by researcher to achieve certain goals.
Used more often by qualitative than quantitative researchers.
Can be used in quantitative studies to select experts or to achieve other goals.

A

Purposive

18
Q

Types of Probability Sampling

A

Simple random sampling
Stratified random sampling
Cluster (multistage) sampling
Systematic sampling

19
Q

Uses a sampling frame – a list of all population elements
Involves random selection of elements from the sampling frame
Not to be confused with random assignment to groups in experiments!
Cumbersome; not used in large, national surveys

A

Simple Random Sampling

20
Q

Population is first divided into strata, then random selection is done from the stratified sampling frames
Enhances representativeness
Can sample proportionately or disproportionately from the strata

A

Stratified Random Sampling

21
Q

Successive random sampling of units from larger to smaller units (e.g., states, then zip codes, then households)
Widely used in national surveys
Larger sampling error than in simple random sampling, but more efficient

A

Cluster Sampling

22
Q

Sample Size Qualifications

A

The number of study participants in the final sample.
Sample size adequacy is a key determinant of sample quality in quantitative research.
Sample size needs can and should be estimated through power analysis for studies seeking causal inference.

23
Q

Examples of Records, Documents, and Available Data

A

Hospital records (e.g., nurses’ shift reports)
School records (e.g., student absenteeism)
Corporate records (e.g., health insurance choices)
Letters, diaries, minutes of meetings, etc.
Photographs

24
Q

Major Types of Data Collection Methods

A

Self-report

Observation

Biophysiologic measures

25
Q

Advantages of Questionnaires

A

Lower costs
Possibility of anonymity, greater privacy
Lack of interviewer bias

26
Q

Advantages of Interviews

A

Higher response rates
Appropriate for more diverse audiences
Opportunities to clarify questions or to determine comprehension
Opportunity to collect supplementary data through observation

27
Q

used to make fine quantitative discriminations among people with different attitudes, perceptions, traits

A

Scales

28
Q

Likert Scales

A

Consist of several declarative statements (items) expressing viewpoints
Responses are on an agree/disagree continuum (usually 5 or 7 response options).
Responses to items are summed to compute a total scale score.

29
Q

Semantic Differential Scales

A

Require ratings of various concepts.
Rating scales involve bipolar adjective pairs, with 7-point ratings.
Ratings for each dimension are summed to compute a total score for each concept.

30
Q

Visual Analog Scale (VAS)

A

Used to measure subjective experiences (e.g., pain, nausea) – see a lot in peds
Measurements are on a straight line measuring 100 mm
End points labeled as extreme limits of sensation

31
Q

Response Set Biases

A

Biases reflecting the tendency of some people to respond to items in characteristic ways, independently of item content

32
Q

Response Set Bias Examples

A

Social desirability response set bias
Extreme response set
Acquiescence response set (yea-sayers)
Nay-sayers response set

33
Q

Evaluation of Self-Reports

A

Strong on directness
Allows access to information otherwise not available to researchers
But can we be sure participants actually feel or act the way they say they do?

34
Q

phenomena Amenable to Research Observation

A
Activities and behavior
Characteristics and conditions of individuals 
Skill attainment and performance
Verbal and nonverbal communication
Environmental characteristics