Alternative Sampling Designs

Alternative Sampling Designs

Simple Random Sampling

Stratified Random Sampling

Cluster Sampling

1. Divide the population into non-overlapping areas or clusters

- Each cluster contains a wide variety of elements and the cluster is a miniature or microcosm of the population.

- Internally heterogeneous (the different with stratification)

- Commonly involves geographical locations (states, towns, companies, etc.)

2. Choose a number of clusters

3. Select element randomly from clusters

Two-stage sampling: if the clusters are too large, a second sets of clusters is taken from each original clusters

Advantages: convenient & lower cost

- The cost of sampling from the entire population is reduced

- Cluster sampling is less costly than simple/stratified random sampling if the cost of obtaining a frame is high or the cost of obtaining observations increases as the distance separating the elements increases.

Systematic Sampling (1-in-k systematic random sampling)

Randomized Response Sampling

- People often refute to give correct answers to sensitive questions that may embarrass them or be harmful to them is some way.

- Define

o Group A = people who have the characteristic of interest (giving false information)

o Group B = people who do not have the characteristic

o p =proportion of group A in the population (we want to estimate p without asking each person directly whether or not he/she belongs to group A (i.e. Have you given false information?)

-