Surveys and population based studies
Download
1 / 17

Surveys and Population-Based Studies - PowerPoint PPT Presentation


  • 64 Views
  • Uploaded on

Surveys and Population-Based Studies. Definition of a "Survey"

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Surveys and Population-Based Studies' - merrill-peterson


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
Surveys and population based studies
Surveys and Population-Based Studies

  • Definition of a "Survey"

    A method of collecting information about a human population in which direct (or indirect) contact is made with the units of the study (e.g., individuals, organizations, communities, etc.) by using systematic methods of measurements like questionnaires and interview schedules. (Warwick and Lininger, 1975)

  • Examples of well-known surveys:

    • U.S. Decennial Census

    • Current Population Survey (n=60,000 HHs/mo.)

    • Health Interview Survey (n=50,000 HHs/yr.)

    • Other Examples in Groves, et al. (2004)


Nonprobability sampling
Nonprobability Sampling

  • Selection by nonrandom methods

  • Membership in the sample is ultimately left to human judgment

  • No basis for assuming stochastic behavior of sample estimates

  • One method: quota sampling


Quota sampling
Quota Sampling

  • Quota control/allocation for each interviewer:

  • Filling category is left to interviewer's discretion (i.e., judgment)


Probability sampling
Probability Sampling

  • Ultimate selection left to some randomized (i.e., chance) mechanism

  • Two types:

    • Random sampling

    • Survey sampling


Random sampling
Random Sampling

  • "Population" is infinite and abstract; distribution of measurements follows some assumed form (e.g., a normal distribution)

  • Sample is the result of independently selecting a measurement at random from the assumed distribution, with sample size as the number of selections


Random sampling1
Random Sampling

  • “Random sample” as defined by Hogg & Craig:

  • "Let X1, X2, . . ., Xn denote n mutually statistically independent

  • random variables, each of which has the same but possibly

  • unknown probability density function, f(x). The random variables

  • X1, X2, . . ., Xn are then said to constitute a random sample from

  • a distribution that has pdf, f(x).

  • Example: f(x) for the normal distribution:


Population based sampling
Population-Based Sampling

  • Population is finite (i.e., made up of a countable set of members)

  • Distribution of measurements usually does not follow a neat mathematical form

    • Ex: Number of health care visits in the past 12 months

  • Randomization used but selections may not be made independently


Probability sampling1
Probability Sampling

  • Each population element has a known and nonzero probability of being selected into the sample

  • EPSEM sample design:

    • Sample in which selection probability for each element is equal;

    • Stands for Equal Probability Selection Method.

    • Also use the term "self-weighting"


Advantages of probability sampling
Advantages of Probability Sampling

  • Statistical theory (including sampling theory) assumes this method

  • Not subject to biases of human judgment

  • Can directly measure the precision (i.e., statistical quality) of estimates produced from sample


Utility of sampling theory
Utility of Sampling Theory

  • Basis for settling on ways to estimate population parameters and the precision of those estimates

  • Basis for much of the decision making in designing the sample


Inference in population based studies

Population:

Values to be

Estimated

Analysis:

(Population Values

Estimated)

Sample Design

(Probability Sampling)

Selected Sample:

(Data Collected)

Inference in Population-Based Studies

  • Circle of inference:


Population hierarchy

Population

Member

Population Hierarchy


Population hierarchy some examples
Population Hierarchy: Some Examples

  • First grade students in NC schools

  • Residents of the United States


Components of a population based study
Components of a Population-Based Study

  • Planning

    • Study specifications

      • Target population

        vs.

      • Survey population

    • Budget considerations

    • Staff communication

    • Sample size


Components of a population based study1
Components of a Population-Based Study

  • Sampling

    • Preliminary activities

    • Search for sampling frame(s)

      • List(s) of units to be sampled

    • Develop the sample design

      • Plan to choose the sample

      • Consists of a sequence of statistical issues and decisions

    • Select the sample


Components of a population based study2
Components of a Population-Based Study

  • Data collection instrument

    • Design questionnaire and forms

    • Small-scale testing

    • Manuals for training

  • Data collection

    • Preparation (e.g., hiring and training)

    • Field operations (e.g., monitoring and supervision)

  • Manual editing/coding

    • Preparation

    • Operations


Components of a population based study3
Components of a Population-Based Study

  • Data entry

    • Preparation

    • Operations

  • Machine editing/coding and file processing

    • Preparation

    • Run edits

    • Prepare analysis work files

  • Analysis and dissemination


ad