Sociology Research Methods Final

Front 1

Content Analysis - How to formulate the research question

Back 1

1. Decide unit of analysis
2. develop sampling plan
3. construct coding categories and recording sheet
4. coding and inter coder reliability
5. data collection and analysis

Front 2

Content Analysis- Limitations

Back 2

- fallacy of misplaced concreteness
- unit of analysis
- validity and reliability
- missing data

Front 3

Reliability

Back 3

extent which the same technique applied again to the same subject will give the same result

Front 4

Aspects of Reliability

Back 4

-Stability across time
- representative across populations
- equivalence (questions measure same thing)

Front 5

How to improve reliability

Back 5

- Conceptualization (appropriate definition
- Increase level of measurements (interval/ratio)
-Multiple indicators (more questions)
- pretest, pilot studies, and replication

Front 6

Validity

Back 6

extent to which our measure reflects what we think or what we want to be measuring

Front 7

Face Validity

Back 7

measure that relates to what we are interested in finding out even if it doesn't encompass the concept

Front 8

Criterion validity

Back 8

predictive nature of a test

ex. success in college measure with SAT scores

Front 9

Construct Validity

Back 9

measure logically related to another variable as you thought it would be

ex) researching happiness,, measure financial stability

Front 10

Content Validity

Back 10

how much a measure covers a range of meaning
- was the full range of dimensions related to a concept covered?

ex) measuring prejudice but only measure race

Front 11

Internal Validity

Back 11

addresses the true cases of outcomes in your study

strong internal validity = reliable measures of IV

Front 12

History effect

Back 12

specific events occurred between 1st and 2nd measure in addition to IV (external factors)

Front 13

Maturation Effect

Back 13

internal changes in the subject

Front 14

Testing effect

Back 14

effect of pretest on posttest, knowing the questions

Front 15

Instrumentation effect

Back 15

researcher changing test

Front 16

Selection bias (effect)

Back 16

bias of different individuals selected for each condition

Front 17

Mortality effect

Back 17

people drop out of study

Front 18

regression to the mean (effect)

Back 18

more tests = closer to the mean

Front 19

External Validity

Back 19

how well you can generalize your study to the population

Front 20

Levels of measurement

Back 20

Nominal- different categories
Ordinal - different categories, ranked (grades)
Interval - different categories, ranked, meaningful distance between (temp)
ration - different categories, ranked, meaningful distance, true zero

Front 21

Principles of good measurement

Back 21

Mutually exclusive, exhaustive, unidimensionality

Front 22

Types of Scales

Back 22

Likert
Thurstone
Bogardus Social Distance
Semantic

Front 23

Population

Back 23

theoretical group of cases of interest

Front 24

Parameter

Back 24

characteristics of cases true to population

Front 25

Sample

Back 25

Cases chosen for study, usually from sampling frame

Front 26

Sampling frame

Back 26

list as many cases as possible

Front 27

Statistics

Back 27

characteristics of cases true to the sample

should represent parameters

Front 28

Sampling Elements

Back 28

Units of Analysis

Front 29

Non-probability sample

Back 29

Convenience
quota
purposive
snowball
deviant case - sample extreme cases
sequential - same until saturation
theoretical - generating theories, not findings

Front 30

Probability sample

Back 30

Simple Random sample
- random table # generator
-sampling distribution
- central limit theorem
- confidence interval

Front 31

Experimental Design

Back 31

1. start with causal hypothesis
2. modify one specific aspect of a situation that is closely connected to the cause
3. compare outcomes

Front 32

Experimental Design - Matching

Back 32

assigning people to groups due to a variable that the researcher think is really important to take into consideration as it might be related to the DV

Front 33

Experimental Design - Random Assignment

Back 33

people assigned to different treatment groups to ensure the group attributes for the different treatments will be roughly equivalent and therefore any effect observed between groups can be linked to the treatment ad is not a result of the characteristics of the subjects

Front 34

Experimental Design type

Back 34

One shot case study - treatment then examination (no pretest, no control)
One group pretest posttest design
Pretest/posttest control group design
Posttest only control group design

Front 35

What is asked in a survey?

Back 35

Behavior,
-attitudes/beliefs/opinions
-characterists
-expectations
-self classification
-knowledge

Front 36

Survey Design

Back 36

1 - hypothesis, type of survey, write questions, response categories, layout
2 - how to record data, pilot test
3 - decide population, sampling frame, sample size, sample
4 - find respondents, interviews, record data
5 - Analyze Data
6 - Report Data

Front 37

Survey Questions to Avoid

Back 37

-slang
-ambiguous
-emotional language
- double-barreled
-leading
-beyond knowledge
-false premises
- distant future intentions
-double negatives
-overlapping response categories

Front 38

Survey with Sensitive Topics

Back 38

-create comfort and trust
-use enhanced phrasing
-establish desensitizing context
-anonymous methods

Front 39

Social Desirability Bias

Back 39

tendency of respondents to answer in a manner viewed favorably by others

Front 40

Contingency Questions

Back 40

asked to gauge if respondent is qualified or experience enough to answer

Front 41

Layout Design Issues

Back 41

Format - matrix, horizontal vs vertical

Length

Mail in response rate

Front 42

Types of Survey

Back 42

-Mail - low response rates, quick, not personal
-Telephone - invasive, quick, direct, can re-explain question
-face to face - personal, give more time, more trust, slow, expensive
-Internet - need access, issue of true identity, quick, cheap, wide spread, no time or geography boundries

Front 43

Interview Bias

Back 43

- errors by respondent
- interviewer error
- intentional subversion
- influence by interviewer's expectations
- failure to probe
- influence on the answers

Front 44

Coding
-manifest (from respondent)
-latent (inferred)

Back 44

- 4 methods - code sheet, direct entry, optical scan, bar code

cleaning data - possible code cleaning, contingency cleaning