Loading in 5 sec....

Survey Methodology Sampling, Part 2PowerPoint Presentation

Survey Methodology Sampling, Part 2

- By
**kalli** - Follow User

- 189 Views
- Updated On :

Download Presentation
## PowerPoint Slideshow about '' - kalli

**An Image/Link below is provided (as is) to download presentation**

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

Random digit dialing

- Delineate the geographic boundaries of the sampling area
- Identify all of the exchanges used in the geographic area
- Identify the distribution of prefixes with the sampling area
- Example: There may be 8 exchanges, but you may find that 3 of them are used for nearly two-thirds of residential lines.

Random digit dialing

- You may stratify based on the distribution of prefixes
- Ex. Take more samples of the 3 exchanges that account for the most residential lines

- Try to identify vacuous suffixes
- These are suffixes not yet assigned or assigned in large groups to a business
- Usually consider suffixes in 100s
- ex. 0000-0099, 0100-0199

Random digit dialing

- May randomly select the four-digit suffixes
- ex. use a random-numbers table

- Alternatively, you may use a plus-one approach
- When you reach residence, use the number as a seed, and add fixed digits (one or two) to get the next sample

Random digit dialing

- What are the advantages and disadvantages of the random method?
- What are the advantages and disadvantages of the plus-one method?

Random digit dialing

- Provides a nonzero chance of reaching any household within a sampling area that has a telephone line regardless of whether the number is listed
- Is the probability of reaching every household equal?
- No. Households with more than one phone line will have a greater probability than households with one phone line.
- Adjust for unequal probability by weighting

Random Digit Dialing

- Advantages: Inexpensive and easy to do
- Disadvantages: 1. Large number of unfruitful calls2. Will exclude individuals without phones3. May be difficult to ascertain geographic area

Cluster sampling

- Each member of the study population is assigned to a group or cluster, then clusters are selected at random and all members of a selected cluster are included in the sample
- Clusters are often naturally-occurring groupings such as schools, households, or city blocks (Henry, 1990)

Multistage sampling strategy

- Underlying concept is similar to cluster sampling
- Clusters are selected as in the cluster sample, then sample members are selected from the cluster members by simple and random sampling
- Clustering may be done at more than one stage (Henry, 1990)

School example

- Assume 20,000 students; 40 schools
- Desired sample size=2,000 students (i=10)

Possible Approaches

- Select all schools, list all students, and select 1/10 of students (SRS)
- Select 1/2 of schools, then select 1/5 of students (multistage)
- Select 1/5 of schools, then select 1/2 of students (multistage)
- Select 1/10 of schools, then collect data on all students in those schools (cluster)

Area probability sampling

- Geographic basis
- Divide a total geographic area into exhaustive, mutually exclusive subareas
- Sample subareas
- List all housing units within selected subareas
- Sample from list or collect data from entire list (Fowler, 1993)

Example

- City has 400 blocks with a total of 20,000 housing units
- Sample size is 2,000 housing units (i=10)

Approaches

- Sample 80 blocks, list housing units, then sample 1/2 of the housing units
- Sample 40 blocks, list housing units, then sample all of them

Area probability sampling proportional to size

- Choose a cluster size for the last stage of sampling (for example, 10 housing units)
- Estimate the number of housing units on each block
- Order the blocks so that similar ones are contiguous
- Create a cumulative count of housing units

- Determine the interval between clusters (I=i*cluster size)
- Choose a random start between 1 and I.
- Proceed through cumulative count, selecting every Ith block
- List units on the selected block and select cluster size (ex. 10)(Fowler, 1993)

- What if your estimate of the number of housing units on the block was wrong?Use (cluster size/estimated units on block) for each block
- Result is 10/43 for block 1, 10/87 for block 2, and 10/99 for block 3.

Respondent selection block was wrong?

- Once you have selected a housing unit, how do you select the individual respondent?
- Who is the best person to provide the desired information?
- For self-reporting surveys, we use probability sampling to select the respondent.

- Ascertain the number of eligible individuals in the housing unit
- Number them
- Randomly select a respondent
- You may need to weight the response by the number of eligible individuals in the housing unit

Nonprobability sampling designs unit

- Convenience: select cases based on their availability for the study
- Most similar/dissimilar cases: select cases that are judged to represent similar conditions or, alternatively, very different conditions
- Typical cases: select cases that are known beforehand to be useful and not to be extreme

Nonprobability sampling designs unit

- Critical cases: select cases that are key or essential for overall acceptance or assessment
- Snowball: group members identify additional members to be included in sample

Nonprobability sampling designs unit

- Quota: interviewers select sample that yields the same proportions as the population proportions on easily identified variables(Henry, 1990)

Terminology unit

- Universe
- Population
- Survey population
- Sampling frame
- Sampling unit
- Observation unit

Download Presentation

Connecting to Server..