Kategorier: Alle - probability - sampling - validity

af Matthew Pickard 17 år siden

373

Ch2_Sampling

Ch2_Sampling

Sampling (Trochim)

external validity

ways to improve
do study in a variety of places
use theory of proximal similarity effectively

provide data/descriptions

differences

similarities

draw good sample

keep dropout rates low

threats to
generalization
proximal similarity model

gradient of similarity

contexts

times

places

people

dimension along which your study context can be related to other potential contexts to which you might wish to generalize

sampling model

problems

impossible to sample across all times you want to generalize to

not able to draw fair or representative sample

don't know what part of population you want to generalize to

4. generalize results back to the population

3. conduct research on the sample

2. draw representative sample

1. identify population you would like to generalize to

population

population parameter
sampling frame
examples

Subtopic

phone book

statistic

sample unit

measurement

response

mean

sampling distribution

standard error

sampling error

the spread of the averages around the average of the averages

standard deviation

3 stdev = 99%

2 stdev =95%

1 stdev = 65%

Non-probability Sampling

Purposive
Snowball

sampling hard to find populations

Heterogeneity

sampling for diversity

Quota

nonproportional

proportional

Expert

sampling experts

Modal Instance

sampling most frequent/typical case

Convenience

Probability Sampling

Multistage
Systematic

may be more precise than simple random sampling

easy to do

5. Take every Kth unit

4. randomly select integer between 1 and K

3. calculate interval size (K = N/n)

2. decide on sample size (n)

1. number units in population

Cluster (AREA)

3. measure all units withing sampled clusters

2. randomly sample clusters

1. divide population into clusters (usually geographically)

Stratified
sampling fraction between strata

different

disproportionate stratifed random sample

same

proportionate stratified random sample

advantages

more statistical precision (when subgroups are homogenous)

able to represent key subgroups in population, especially minority groups

how?

homogenous subgroup

sample

Simple