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Methods & Measurement > Chapter 5, 8, 9 & 4 > Flashcards

Chapter 5, 8, 9 & 4 Flashcards

Social Research - Approaches and Fundamentals

1
Q

Purpose of research

A

Collecting info reagrding target population

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2
Q

Steps for sampling

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

Coverage error

A

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

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4
Q

Two types of coverage error

A
  • 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
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5
Q

Sampling designs

A

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

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6
Q

Sampling designs divided in 2 classes

A
  • Probability sampling (4 ways): all cases are randomly selected
  • Non probibility sampling: cases are non-randomly selected
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7
Q

Random selection

A

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

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8
Q

Simple random sample

A

Equal chance in random selection

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9
Q

Sampling error/random error

A

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

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10
Q

Systematic error

A

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

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11
Q

Confidence interval

A

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

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12
Q

Stratified random sampling

A

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

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13
Q

Disproportionate stratified random sampling

A

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

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14
Q

Cluster sampling

A

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

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15
Q

Two ways to sample

A
  • Single staged cluster sampling –> sampling with cluster level. Primary sampling units.
  • Multistage cluster sampling (nested sampling). Secondary sampling units.
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16
Q

Systematic selection

A

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)

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17
Q

Sampling interval

A

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

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18
Q

A random start

A

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

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19
Q

Characteristics of survey research

A
  • Large scale probability sampling
  • Pre-constructed questionnaire/interview protocol
  • Coded answers & statistical analysis
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20
Q

Descriptive surveys

A

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

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21
Q

Explanatory surveys

A

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

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22
Q

Research design

A

Overall structure of a study

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23
Q

Cross-sectional design

A

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

24
Q

Two variations of Cross-sectional survey

A
  • 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.
25
Q

Longitudinal designs

A

Same questions are asked at two or more points in time

26
Q

Two types of longitudinal designs

A
  • 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
27
Q

Time in sample bias

A

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

28
Q

Panel conditioning

A

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

29
Q

Four types of errors that threaten accuracy of survey results

A
  • Coverage error
  • Sampling error
  • Non response error
  • Measurement error
30
Q

Measurement error

A

Inaccurate responses associated with the respondent

31
Q

Types of survey research

A
  • Classification (survey modes) –> interviews, questionnaire
  • Optimal sampling design (from realistic perspective) –> Face tot face, mail/telephone
32
Q

Types of response scales

A

Dichotomy, Rating questions, Picking/ranking scales

33
Q

Dichotomy

A

Most ‘easy’ one, just two options. yes/no

34
Q

Rating questions (labels/numbers)

A
  • Likert scale (5 point scale)
  • Thermometer question ( only end labelling of response categories, in between using values)
  • Semantic differential (two opposites opinions)
35
Q

Picking/Ranking scale

A
  • Ranking (full/partial)

- Picking (without ranking)

36
Q

Primary effect

A

More likely to choose an earlier mentioned option

37
Q

Recency effect

A

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

38
Q

Conceptualization

A

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

39
Q

Two important aspects to the measurement process

A
  • A single category (ex. male, b-grade student)

- Several values (ex. gender, exam results –> multiple items)

40
Q

Operationalizing

A

Making the concept measurable

41
Q

Index

A

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

42
Q

Reliability

A

The precision & consistency in measurement

43
Q

Validity

A

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

44
Q

Measurement error

A

Points of departure: Classical test-theory:

X= T + Es+ Er

45
Q

Systematic measurement error

A

Validity problem

46
Q

Random measurement error

A

Reliability error

47
Q

Test-retest reliability

A

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

48
Q

Split half and internal consistency

A

Multiple items measuring one single concept; one measurement

49
Q

Split half method

A

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

50
Q

Internal consistency

A

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

51
Q

Face validity

A

Personal judgement

52
Q

Criterion related validity

A

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

53
Q

Construct validity

A

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

54
Q

4 types of construct validity

A
  • Correlation with related variables
  • Differences between known groups
  • Consistency accross indicator and different methods of measurement
  • Correlations with unrelated variables
55
Q

Heterogeneous target (language)

A

Use common language / keep it simple

56
Q

Homogeneous target (language)

A

Use language of your targetgroup (ex. doctors)

Methods & Measurement (2 decks)

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