Part II Surveys

Question 1

What is a survey?

Answer 1

• Standardized, cross-sectional approach to data collection of info on individuals and households through questioning/measurement of systematically identified samples

Question 2

4 steps of a survey

Answer 2

1. Sample design
2. measurement
3. Survey operations (fieldwork)
4. Statistical analyses and interpretation

Question 3

What is sampling error and how does it compare to random error?

Answer 3

Error in the estimate due to the fact that only part of the population is included in the sample
- component of random error

Question 4

Sample design has two aspects:

Answer 4

1. Selection process (rules and operations by which some members of the pop are included in the sample)
2. Estimation process (computing the sample statistics)

Question 5

Elements or elementary units

Answer 5

Elements of a population are the units for which information is sought (i.e., individuals)

Question 6

Sampling units

Answer 6

Contain the elements (e.g., households)

• Useful for when a list of the elements does not exist
• May contain only one element (element sampling) or several element (cluster sampling)

Question 7

Sampling frame

Answer 7

List of target population from which the sample is actually drawn

Question 8

Enumeration rule

Answer 8

Rule by which elementary units are to be associated with each enumeration

Question 9

Observational units

Answer 9

Units from which the observations are obtained (i.e., respondents; e.g., mothers of children)

Question 10

Sampling fraction

Answer 10

Probability with which the elements are sampled

Question 11

Model sampling

Answer 11

Sampling based on broad assumptions about the distribution of the vx in the pop

• arbitrary and informal samples
• assume that the important characteristics are distributed either uniformly or randomly

e. g., Haphazard/Fortuitous sampling (whatever comes to hand)
e. g., Judgment sampling (expert’s choice for typical units)

Question 12

Probability sampling

Answer 12

• Every element has a known and nonzero probability of being sampled
• statistical inferences to pop values can be made

Question 13

Simple random sampling

Answer 13

Assign number, select n numbers by random process

• Requires a list of elements
• Difficult to assess subgroups
• Difficult for samples spread geographically

Question 14

Equal probability of selection method sampling

Answer 14

• Elements have equal probabilities of being selected
  e. g., 10% prob regardless of language

Non-EPSEM sampling: non-equal probability of selection

Question 15

Systematic sampling

Answer 15

• Approximation of SRS, so widely used
• Random starting point on list, then select every nth unit
• Can be done as sample frame is constructed

Question 16

Stratified sampling

Answer 16

• Divide sampling frame in subgroups
• Sampling done separately within each stratum
• Proportionate (same fraction in each stratum) vs disproportionate

Question 17

Dis/Advantages of stratified sampling

Answer 17

Advantages (over SRS)

• Precision
• Estimates for each strata
• nothing to lose

Disadvantages

• Requires identification of every enumeration unit by stratum before sampling
• only for easily available criteria

Question 18

Cluster sampling

Answer 18

• Elements included into larger sampling units (e.g., generally geographical areas)
• Decreases variability, decreases precision
• Easier to construct sampling frames
• Lower cost

Question 19

Sample size adjustments

Answer 19

1. For design effect (when the standard error is higher than for SRS)
2. Expected response rate
3. Proportion of eligibles

Question 20

Conservative and less conservative approach to response rate?

Answer 20

Conservative: consider all refusals and non-contacted individuals as eligible

Less conservative: consider that the proportion of ineligible among refusals is the same as in the responders

Question 21

3 types of nonresponse

Answer 21

1. Refusals
2. Non-reachable
3. Selective non-response

Question 22

Refusals

Answer 22

• Often impossible to know eligibility
• Selection bias if differential refusal
• If non-diff: decreased n, increased sampling error, increased standard error, decreased precision

Question 23

Non-reachable

Answer 23

• Impossible to know eligibility
• Selection bias if differential
• If non-diff: decreased n, increased sampling error, increased standard error, decreased precision
  (SAME AS REFUSALS)

Question 24

Selective non-response

Answer 24

• Refusing to answer specific questions
• If large number missing, possibility of bias (25% over, exclude)
• Imputation methods