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Social Research Methods

Surveys

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Survey

Characteristics

Collecting a SMALL amount of data in STANDARDISED form from RELATIVELY LARGE NUMBERS OF INDIVIDUALS

Selection of REPRESENTATIVE SAMPLES of individuals from KNOWN POPULATIONS

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Surveys are very common

Most reported research is a survey Most calls for research want surveys done.

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References

de Vaus, D. A. (2002) Surveys in Social Research 5th ed. London: Routledge.

Aldridge, Alan, Levine, Kenneth (2001) Surveying the social world : principles and practice in survey research. Buckingham; Philadelphia, PA: Open University Press.

Fowler, Floyd J. (2008) Survey research methods 4th ed. London: Sage Publications.

Hoinville, G., Jowell, R and associates (1985) Survey Research Practice. London: Gower

Moser, C. A. and Kalton, G (1971) Survey Methods in Social Investigation. Aldershot: Gower

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Mounting a survey Initial design

including sample design and selection Questionnaire construction (incl. piloting) Fieldwork (the most efficient stage)

How to deliver? Postal, self-administered, handout, e-mail, WWW etc. In person/interview/telephone

Dealing with non-responses Editing and Coding Computer entry and editing Analysis and interpretation Write Up.

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Remote vs. Interviews

Pro Con

Often only/easiest way to get info.

Low response rate, may not be representative

efficient, low cost, fast

Ambiguities not detected

anonymous Respondents don’t treat seriously

Remote (= postal, www etc.)

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Interview

Pro Con

Can clarify questions Interviewer bias

Interviewer encourages participation/ involvement

Interviewer-respondent effects

May not be seen as anonymous. Respondents less honest

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Survey design

1. Simple Survey e.g. ad hoc sample survey (a snapshot), cross sectional survey Essentially descriptive - says what the current state of affairs is.

2. Panel Survey Collect information from same people at 2 or more points in time.

3. Rotating sample survey Repeated survey with some continuing respondents and some

new.

4. Longitudinal survey either a form of panel over a long period of time or simulated by combining simple surveys from different time

periods.

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Sampling

Why sample?

1. Population too large to take all e.g. UK population

2. Population too dispersed or difficult to contact e.g. members of swimming clubs

3. To get results quickly

Key to sampling = getting a REPRESENTATIVE sample

(compare with blood sample)

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How big a sample?

1. Less than 1/10 of the population

2. Big enough to produce acceptable sampling error(e.g. about 2,000 from large population)

3. Big enough to give reasonable numbers in subsets(e.g. 4 x 5 table = 20 cells, need 10 in each, so sample ≥ 200

4. Small enough to carry out with available resources and time.

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Types of sampling

A. Probabilityeach member of population has known and

usually equal chance of inclusion. Can make statistical inferencesB. Non-probabilityselect by non-random methods involving

human judgement. Sample may be representative but this not

known

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Most probability sampling needs a sampling frame

A list of everyone in the population + means of contacting.

N.B. problems1. Categories excluded (e.g. all students misses occasional

students)2. Inaccuracies (e.g. in when should be off list, off when

should be in)3. Sampling frame in wrong units (voters when household

needed)4. No information on population which is needed for

stratification5. No means of contact (e.g. list of church members, no

addresses)

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Types of probability sample

Simple random Systematic or quasi-random Stratified Multi-stage Cluster

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Simple random

Every member has equal chance of selection Called epsem design (Equal Probability

Selection Method) Select from sampling frame by:

a. lottery (e.g. toss coins)

b. using list of random numbers

c. computer generated random number list

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Systematic or quasi-random

Simple random sampling very inconvenient for large samples

Therefore Start from random point and then take every rth person on list

e.g. 5% sample from population of 2,000 (=N)

i.e. sample of 100 (=n)

r = N/n = 2,000/100 = 20

Therefore select every 20th person

Start from random person between 1 and 20, say 13

so take person 13, person 33, 53, 73 etc. up to 1,993 N.B. only 20 possible samples compared with billion of billions

for simple random sampling

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Stratified

Used to increase likelihood of representative sample (i.e. reduces sampling error)

Divide population into strata and ensure share of sample is from each stratum. e.g. age groups. if 13.5% of population aged 16-25 then 13.5% of

sample should be aged 16-25. Needs information on stratification factor in sampling

frame. Strata should be internally homogeneous and different

from other strata. Stratification factor should be related to issues of interest

in survey

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Disproportionate stratification

Increase chance of selecting from some strata

Adjust for this in analysis

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Multi-stage

Increases sampling error but decreases cost of sample

Increases geographical concentration Divide sampling frame into groups and select only

some groups (e.g. counties, towns) May be several stages

Sampling with probability proportional to size Adjust chance of selection within group to account for

different sizes of groups

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Cluster

Used where no final sampling frame available

Like multi-stage, select some groups, at several levels

then take ALL people in selected groups.

Like multi-stage it concentrates sample but increases sampling error.

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Non-probability sampling

Not chosen using probability methods - rather some human judgement

Most common = QUOTA sampling Samples are stratified usually by age, sex,

occupational status

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QUOTA sampling

People chosen by interviewer (not at random) from those passing by to fill quotas of e.g. so many men, so many women, so many aged 16-24 etc.

Quotas can be linked e.g. so many men aged 16-24.

N.B. no estimate of sampling error possible BUT evidence suggests good quota samples are

good representative samples

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Other kinds of non-random sampling

1.Convenience sample Friends, neighbours relations etc.

2.Snowball (or cascade) sample Friends of friends, contacts of contacts etc.

3.Purposive Collected for specific purpose or reason