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Chapter 9

This

**preview**shows pages 1-3. to view the full**14 pages of the document.**Study Guide – Chapter 9: Survey Research and Subject Recruitment

What are Opportunity and Probability Samples?

here we examine logic and limitations of the methods used to select research participants

Donald Rubin noted all studies lie on a continuum from irrelevant to relevant with respect to

answering a question

Randomized laboratory-type experiments that use opportunity samples of the first available

students in college settings have a restricted sample of participants but usually have a high

degree of control over the variables of interest

By contrast, researchers who do survey studies select potential respondents using special

sampling procedures in order to generalize their descriptive findsings to a specific larger pool (a

population) of people

If survey researchers used opprunity samples, spurious results and misleading generalizations

about the specific population of interest would seriousluy compromise scientific integrity of

their work

There is wide range of topics of interest to survey researchers

Pollsters use survey designs to map out some specified population’s opinions on important

societal issues such as the community’s fears of crime or its choice of political candidates

Similar methods are used sometimes in epidemiological research, forensic research, economic

research, and many other areas in which scientific surveys are conduction

When health officials wanted to find out about national trends in cases of tuberculosis

contracted on the job, they did scientific surveys of hospitals to count employees reported to

have TB

o As federal courts became inundated with mass torts involving asbestos cases, one

solution was to sample asbestos cases from the larger pool within a court’s jurisdiction

o Asses damages in randomly chosen cases from each of five disease categories were then

applied to each larger pool

o More recently, when researchers wanted to study the prevalence of psychological

resilience after a traumatic event they chose a probability sample of New Yorkers to

survey in the 6 months following 9/11

o Researchers reported resilience was present in two thirds of the sample and never fell

belwo one third even among highly exposed individuals with posttraumatic stress

disorder

Instead of trying to question every member of the population which is usually impossible, this

type of research focuses on a segment (sample) that is believed to be a typical of the population

How can researchers be certain that the segment is representative or typical of the population?

Ex. How can they be sure that a specific form of data from a sample is representative of a pop?

They might compare the sample with the most recent census data but it is well known that

census data are problemative because it is impossible to contact every member of the

population

Researchers who use a sample can enver be 100% sure of their generalizations

They can make reasonable guess by first developing an accurate sampling frame that defines the

target population and then relying on a carefully designed blueprint (sampling plan) to select

sample means of probability sampling

Probability sampling – implies randomness enters into selection process at some stage so that

the laws of mathematical probability apply

Probability – refers to the mathematical chance of an event’s occurring

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

o Ex. Likelihood of getting “heads” when you flip a coin once (1 in 2) or getting a 2 when

you throw a die once (1 in 6)

Survey studies can take many different forms, all using sampling plans in whicih osme method of

probability sampling determines the random selection of the households or people to be

contacted

These plans enable the researcher to assume reaspnably but with no 100% guarantee of being

correct

Practical problems may impose limits on representativeness of the sample

Even in most carefully conducted survey, not every household or person in the sample can be

reached and, of those who are actually contacted, not everyone will agree to be interview

In study of psychological resilience after the September 11, random digit-dialing approach was

used to contact members of the sample

When the number of completed and partial interviews was summed and this total was divided

by the sum of all numbers that were either eligible as residential phone numbers or of unkown

eligibility, the response rate was estimated to be 34%

What Is Meant By Bias and Instability in Survey Research?

Surey research done not only by private organziations, but by individual researchers owkring

alone or with ties to private organizations and in the US, at university based insitutes that can

implement face-to-face and telephone interviewing in national probability surveys

This research takes many different forms, all valid survey research is characterized by sampling

plans in wich every element or sampling unit in the population has a known nonzerio probability

of being selected at each draw

2 imporant statistical requirements of a probability sampling plan are a) the sample values are

unbiased and b) that there be stability in the samples

Unbiased – values produced by sample must, on average, coincide with the true values of the

population – but we can never actually be absolutely sure that this requirement has been met in

a given study unless we already know those values

Stability – means there is not much variability (or spread) in the sample values

o it’s estimated by statistical procedures such as variance and the standard deviation

sampling theory is beautiful because it can be applied not only to individual respondents but

also to teams in a population of teams or to products on an assembly line, or to any other

specified population of animate or inanimate units

bias = systematic error

print page 166 – there is a diagram and it’s above paragraph explains it

The Wine Taster

in manufacture of red wine, grapes are crushed and residue is put into huge cats in which

fermentation occurs

wine is then drawn off into barrels, where fermentation continues and product is periodficlly

sampled by the wine taster

wine taster needs to draw only a small sample in order to evaluate the quality of the wine in the

barrel

it’s the same in survey research: the more homogeneous the population, the smaller the sample

that needs to be drawn

Why Do We Not Know “For Sure” the Bias in Sampling?

Only pages 1-3 are available for preview. Some parts have been intentionally blurred.

only way to know for sure about bias in sampling results is to examine every single member of

the popoulationa nd the sample at the same time the sampling is done – if pattern replies in

same exactly matched pattern in population, we would know there was no sampling bias in

surveryed sample

practically speaking, if we already knew how everyone in a population was – we wouldn’t be

doing a sample to help us study the population

it’s sometimes thought that election forecasting allows us to detect bias in sample because we

can compare predicted voting results with actual votes however problem in this case is that we

are comparing data obtained at one point in time with the results at another point in time

a well-designed and carefully implemented selection process involving probability sampling can

usually produce data that are remarkably close to the election results

polls = people can change their minds, they can be no shows, usually polls closer to election are

thought to be more accurate but still – polls right up to day of voting disagree

How Is Simple Random Sampling Done?

Simple random sampling – the basic prototype of probability sampling. The simple tells us that

the sample is selected from an undivided population, random means that the sample is to be

cjosen by a process that will give every unti in the specified population the same chance of being

selected at each draw

In order for this to occur, the selection of one unit must have no influence on the slection of the

other units

Assumption of random sampling: we have an understanding of the existence of all the units in

the population

Procedure: draw individuals one at a time until wehave as large a sample as we need

Process of selecting units might consist of computer drawing units at random, using a table of

random digits, or even spinning a roulette wheel or drawing well-mixed capsules from an urn.

Telephone interviewing: random digit dialing is sued to include households with unlisted

numbers – area code and first three digits can be selected according to the geographic area of

interest, and then a computer program is used to randomly select the last four digits

Famous case showing hazards of inadequate randomization: Vietnam War, use of random

lottery to select conscripts for armed forces, birthdays out of urns, layers went: January, feb,

march, april, may – even though urn was shaken for hours, the layers had formed and the

ballots came out in order

Use of table of random digits can help to avoid this

2250 digits list came from a million random digits that were generated by an electronic roulette

wheel programmed to produce a random frequency pulse every tiny fraction of a second

A computer then counted the frequency of 0s, 1s, 2s, and so on – on assumption that an

impartial probability method would produce an approximately equal number of 0s, 1,s 2,s and

so on in the overall table of a million random digits – this equality was confirmed

To see how you might use this table if you wanted to do random selection in a survey, imagine

you want to interview 10 men and 10 women individually after choosing them at random from a

list of 96 men and 99 women

You would begin by numbering the population of men consecutively from 01 to 96 and the

population of women from 01 to 00

You are not ready to use the random digits – to do so, you can put your finger blindly on a

starting position

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