SAMPLING & DATA COLLECTION

Question 1

Define POPULATION

Answer 1

Well-defined group with specific characteristics

All the individuals the researcher is interested in studying.

Question 2

Define SAMPLE

Answer 2

Subset of overall population

Set of elements that make up population

Question 3

Define CONVENIENCE SAMPLE.

Answer 3

All members of the population with the relevant characteristics who can be readily found (and consent).

Question 4

Define SNOWBALL SAMPLING

Answer 4

A participant refers the researcher to more potential participants, who may then refer researcher to further potential participants (snowballing).

Question 5

Define PURPOSIVE SAMPLING

Answer 5

An intentional (purposeful) approach is made by the researcher to select participants with specific characteristics or participants within a specific area.

Question 6

Define QUOTA SAMPLING

Answer 6

A sample gathered to represent population as closely as possible. E.g. 40% of population is male so try to make sure 40% of sample is male.

Question 7

Define SIMPLE RANDOM SAMPLING

Answer 7

Participants allocated ‘randomly’ to the study or part of a study: ‘pulled out of a hat’ chosen by computer.

Question 8

Define STRATIFIED RANDOM SAMPLING

Answer 8

Members of the population allocated to groups according to characteristics important to the study and then subjects randomly chosen from these groups.

Question 9

Why are ELIGIBILITY CRITERIA so important?

Answer 9

Characteristics specific to allow generalisability of findings.

Question 10

What are the MAIN purposes of SAMPLING?

Answer 10

Increase efficiency of a study

Maintain representativeness of sample

Question 11

Name the two MAJOR headings under which sampling falls:

Answer 11

Probability

Non-probability

Question 12

What type of samples are PROBABILITY suited to?

Answer 12

Simple random sample
Cluster random sample
Systematic sample

Question 13

What type of samples are NON-PROBABILITY suited to?

Answer 13

Quota
Purposive sample
Convenience sample

Question 14

What are the advantages of random sampling?

Answer 14

No researcher bias.

Maximise representativeness

Question 15

What is the aim of stratified random sampling?

Answer 15

increase representativeness

Question 16

What are the disadvantages of non-probability sampling?

Answer 16

less rigorous
limits generalisability
not representative

Question 17

Name 4 qualitative data collection methods

Answer 17

in-depth interviews: may be structured, semi-structured or unstructured

focus groups: involve multiple participants discussing an issue

Secondary data/document review: diaries, written accounts of past events, photographs

Observations: may be on site, or under lab conditions, e.g. where participants are asked to role-play a situation to show what they might do.

Question 18

How is trustworthiness/rigor assured in qualitative research?

Answer 18

credibility (truthfulness)
auditability (consistency)
transferability (fittingness/applicability)
confirmability (no bias or distortion)

Member checking; audit trails; triangulation

Question 19

Why is rigor so important?

Answer 19

Need to know methods can be trusted and have confidence in results and using them to apply to your clinical practice.

Question 20

List 4 quantitative data collection methods

Answer 20

physiologic/laboratory-based: clinical/experimental trials

observations: observing and recording well-defined events (such as counting the number of pts. waiting in ED at specified time of day)

Questions & self-report scales - questionnaires: Administer surveys with closed-ended questions

Interviews: face-to-face and telephone interviews

Question 21

Define reliability and validity in relation to measurement error.

Answer 21

Reliability means a measure that can be relied upon consistently to give the same result if the aspect being measured has not changed.

Validity reflects how accurately the measure yields information about the true or real variable being measured. A measure is valid if it measures correctly and accurately what it is intended to measure.

Question 22

Descriptive statistics allow researchers to:

Answer 22

Describe, organise and summarise raw data

Question 23

Inferential statistics allow researchers to:

Answer 23

Estimate how reliably they can make predictions and generalise their findings based on the data.

Question 24

The purpose of descriptive statistics is to:

Answer 24

Organise and summarise the data.

Question 25

Name 4 levels of measurement in quantitative data analysis and briefly define each of these:

Answer 25

Nominal: discrete categories

Ordinal: relative ranking

Interval: specific numerical distance between scores - treated as equal; continuous

Ratio: as above but has absolute zero

Question 26

Name and briefly describe the 3 most common measures of central tendency:

Answer 26

Mean: average score
Median: middle score
Mode: most common score

Question 27

Briefly define cross-sectional studies:

Answer 27

Collect all data at one point in time
Longitudinal studies collect data at different points in time
Retrospective studies collect data on past events
Prospective studies collect data as they occur

Question 28

What is an independent variable?

Answer 28

Manipulated variable (cause)
Used to predict outcome of interest i.e. dependent variable

Question 29

What is a dependent variable?

Answer 29

Measured variable (effect)
Consequence/presumed effect that changes with change in independent variable

Question 30

Name two types of validity and briefly define each.

Answer 30

Internal validity: does the independent variable accurately measure what it says it will measure. Asks whether independent variable really made the difference - refers to the causal relationship

External validity: deals with the problem of generalisability of findings to other populations and other environmental conditions