Week 5 Data collection & Level of measurement

Question 1

What is Data collection?

Answer 1

Process of acquiring subjects
Collecting Data
Must be clearly report

Question 2

3 Key considerations of data collection

Answer 2

1. Sample size
2. Control over extraneous factors
3. Consistency in collecting data

Question 3

Instruments/Methods to collect data

Answer 3

1. Self reports
2. Observations
3. Biophysiologic measures

Question 4

Self reports

Answer 4

Interviews, questionnaires, scale

Question 5

Disadvantage of self reports

Answer 5

Prone to response set biases

Question 6

Examples of response set biases

Answer 6

1. Social desirability
2. Extreme response
3. Acquiescence response

Question 7

Social desirability bias

Answer 7

Tendency to misrepresent attitudes/traits by giving responses that are consistent with prevailing social views

Question 8

Extreme response bias

Answer 8

Tendency to consistently express extreme attitudes/feelings no middle ground

Question 9

Acquiescence response bias

Answer 9

Tendency to agree with all questions regardless of content

Question 10

What are structured & unstructured observations?

Answer 10

Structured - follow checklist
Unstructured - happens spontaneously

Question 11

Biophysiological measures

Answer 11

Most objective
e.g BP, temperature, blood level

Question 12

What to consider when doing observations?

Answer 12

Do inter rater reliability - to be consistent in findings with other observers

Question 13

What is measurement?

Answer 13

Process of assigning numbers/values to individual’s health status, objects or situations using a set of rules

Question 14

What are the 4 levels of measurement?

Answer 14

1. Ratio
2. Interval
3. Ordinal
4. Nominal

Question 15

What are the 2 levels of variable?

Answer 15

Numerical (quantitative)
Categorical (qualitative)

Question 16

What is a nominal scale & its example?

Answer 16

Simply assigning a category name where numbers are arbitrary & have no real meaning

e.g gender (1=male, 2=female), diagnosis

Question 17

Rules of a nominal scale

Answer 17

1. Cannot be rank ordered
2. Must be exclusive & exhaustive categories

Question 18

What is an ordinal scale & its example?

Answer 18

The numbers used to identify the attribute have meaning

e.g what is the highest degree of level of education

Question 19

Rule of ordinal scale

Answer 19

Categories can be ranked
Order of the numbers matter but with unequal intervals

Question 20

What to analyse in ordinal scale?

Answer 20

Median - select number that is exactly in the middle where numbers are in value order

Question 21

What to analyse in nominal scale?

Answer 21

Mode & frequency

Question 22

What is an interval scale & its example?

Answer 22

Equal numerical distances between intervals, where numerical value means something on the real number scale

e.g temperature, likert scale scores, time

Question 23

Rules of interval scale

Answer 23

Order of numbers matter
Lacks a zero point or fixed beginning (no true zero)

Question 24

What to analyse in interval scale?

Answer 24

Mean - (addition/subtraction) average of all respondent’s answers

Question 25

What is a ratio scale & its example?

Answer 25

Highest form of measurement
Continuum of values with an absolute/true zero point

e.g weight, money

Question 26

What to analyse in ratio scale?

Answer 26

Mean - addition/subtraction/multiplication/division

Question 27

Advantages of measurement

Answer 27

1. Removes guesswork in gathering & communicating information
2. Obtains more precise information
3. Provides a language for communication & analysis

Question 28

What are the errors of measurement?

Answer 28

1. Situational contaminants
2. Response set biases
3. Transitory personal factors