Chapter 5, 8, 9 & 4

Question 1

Purpose of research

Answer 1

Collecting info reagrding target population

Question 2

Steps for sampling

Answer 2

1. Defining target population
2. Obtaining sampling frame
3. Deciding sampling design

Question 3

Coverage error

Answer 3

Differences between the target population and the sampling frame, when the sampling frame does not include all members of the population. Ex. telephone interview omits people without a phone

Question 4

Two types of coverage error

Answer 4

• Undercoverage: Belong to the population, but are not represented in the sampling frame (most problematic!!)
• Overcoverage: are not part of the target population, but are listed in the sampling frame

Question 5

Sampling designs

Answer 5

Part of research plan that indicates how cases are being selected for observation

Question 6

Sampling designs divided in 2 classes

Answer 6

• Probability sampling (4 ways): all cases are randomly selected
• Non probibility sampling: cases are non-randomly selected

Question 7

Random selection

Answer 7

Each element in a set has an equal chance of being selected. If not, it is called biased

Question 8

Simple random sample

Answer 8

Equal chance in random selection

Question 9

Sampling error/random error

Answer 9

Differences between a population characteristic (parameter) and the sampling estimate (statistic) of that characteristic

Question 10

Systematic error

Answer 10

Simple random sample only leads to representative info when the coverage error is small, if not, it is called systematic error

Question 11

Confidence interval

Answer 11

Tells us that interval estimates obtained with the procedure are likely to contain the population parameter 95% of the time

Question 12

Stratified random sampling

Answer 12

Stratification of sampling frame in group of elements that share the same characteristics (strata). Guarentees that even smaller strata will be represented in sample

Question 13

Disproportionate stratified random sampling

Answer 13

Variation of random sample. Unequal chance of selection depending on how large stratum is

Question 14

Cluster sampling

Answer 14

The population is broken down into groups of cases, called clusters

Question 15

Two ways to sample

Answer 15

• Single staged cluster sampling –> sampling with cluster level. Primary sampling units.
• Multistage cluster sampling (nested sampling). Secondary sampling units.

Question 16

Systematic selection

Answer 16

Consists of selecting every case from a complete list or file of the population, starting with a randomly chosen case from the first K cases on the list. 2 Requirements (Sampling interval & a random start)

Question 17

Sampling interval

Answer 17

The ratio of number of cases in the population to the desires sample size

Question 18

A random start

Answer 18

Refers to the process of randomly selection of the initial case between 1 and K.

Question 19

Characteristics of survey research

Answer 19

• Large scale probability sampling
• Pre-constructed questionnaire/interview protocol
• Coded answers & statistical analysis

Question 20

Descriptive surveys

Answer 20

Describe the distribution within a population of certain characteristics attitudes or experiences

Question 21

Explanatory surveys

Answer 21

Beyond description to investigate relationship between two or more variables and attempts to explain these

Question 22

Research design

Answer 22

Overall structure of a study

Question 23

Cross-sectional design

Answer 23

To represent a particular target population are gathered at one point at a time. (Single measurement + single time sampling)

Question 24

Two variations of Cross-sectional survey

Answer 24

• Contextual design: sample enough cases within particular groups to describe accurately certain characteristics.
• Social network designs: focus on the relationship or connections among social actors.

Question 25

Longitudinal designs

Answer 25

Same questions are asked at two or more points in time

Question 26

Two types of longitudinal designs

Answer 26

- Trend study: Same questionnaire, same target population, different sample. See changes on group level. - Panel studies: same questionaire, same target population, one sample with repeated measure. See changes on individual level

Question 27

Time in sample bias

Answer 27

Participation becomes routinezed to the point that respondents repeat what they have said before

Question 28

Panel conditioning

Answer 28

Due to repeates measures, stimulates attitude changes, so that respondents attitudes are no longer representative of the larger population

Question 29

Four types of errors that threaten accuracy of survey results

Answer 29

- Coverage error - Sampling error - Non response error - Measurement error

Question 30

Measurement error

Answer 30

Inaccurate responses associated with the respondent

Question 31

Types of survey research

Answer 31

- Classification (survey modes) --> interviews, questionnaire - Optimal sampling design (from realistic perspective) --> Face tot face, mail/telephone

Question 32

Types of response scales

Answer 32

Dichotomy, Rating questions, Picking/ranking scales

Question 33

Dichotomy

Answer 33

Most 'easy' one, just two options. yes/no

Question 34

Rating questions (labels/numbers)

Answer 34

- Likert scale (5 point scale) - Thermometer question ( only end labelling of response categories, in between using values) - Semantic differential (two opposites opinions)

Question 35

Picking/Ranking scale

Answer 35

- Ranking (full/partial) | - Picking (without ranking)

Question 36

Primary effect

Answer 36

More likely to choose an earlier mentioned option

Question 37

Recency effect

Answer 37

When you are more likely to choose the last given options.

Question 38

Conceptualization

Answer 38

Describe and defining of concepts that one aims at measuring/observation

Question 39

Two important aspects to the measurement process

Answer 39

- A single category (ex. male, b-grade student) | - Several values (ex. gender, exam results --> multiple items)

Question 40

Operationalizing

Answer 40

Making the concept measurable

Question 41

Index

Answer 41

Multiple item indicator. Reduce data generated by multiple indicators into a single numer or scale score --> If indicators are combined without a formal 'test' of its scale characteristics

Question 42

Reliability

Answer 42

The precision & consistency in measurement

Question 43

Validity

Answer 43

Congruence between an opearional defination and the concept it is purported to measure

Question 44

Measurement error

Answer 44

Points of departure: Classical test-theory: | X= T + Es+ Er

Question 45

Systematic measurement error

Answer 45

Validity problem

Question 46

Random measurement error

Answer 46

Reliability error

Question 47

Test-retest reliability

Answer 47

Testing/measuring the same persons/units on two seperate occasions with the same measurement. correlation 1 is perfect, should be higher than 0.8

Question 48

Split half and internal consistency

Answer 48

Multiple items measuring one single concept; one measurement

Question 49

Split half method

Answer 49

Divide items of a scale into halves. There will be a correlation between these two subsets

Question 50

Internal consistency

Answer 50

Examines the relationships among all the items (=Cronbachs alpha)

Question 51

Face validity

Answer 51

Personal judgement

Question 52

Criterion related validity

Answer 52

Applies to measuring instruments that have been developed for some practical purpose

Question 53

Construct validity

Answer 53

Emphasizes the meaning of the responses to one's measuring instrument

Question 54

4 types of construct validity

Answer 54

- Correlation with related variables - Differences between known groups - Consistency accross indicator and different methods of measurement - Correlations with unrelated variables

Question 55

Heterogeneous target (language)

Answer 55

Use common language / keep it simple

Question 56

Homogeneous target (language)

Answer 56

Use language of your targetgroup (ex. doctors)