Sampling and Survey Research Podcast

1. Sampling and Survey Research Podcast • Overview of sampling • A word or two about survey research http://www.screencast.com/t/eUdVtYrFD

2. Backing- up.. Where are we in the process

3. Sampling terms Examples from area child protection services Children who are abused in the commonwealth of VA Some of the children who are abused A list of all abused children from VA DSS • Population: • The entire set of individuals or other entities to which study findings are to be generalized • Sample: • A subset of the population that is used to study the whole • Sampling Frame: • A list of all elements or other units containing the elements in a population

4. More sampling terms • Representative sample: • “looks like” the population from which it was selected in all respects that are potentially relevant to the study, • the distribution of characteristics is the same as in the total population • Unrepresentative sample: • a sample in which some characteristics are over-represented or under-represented relative to the total population • Census: • a study of the entire population • usually too expensive and time consuming to be practical • assumes a perfect response rate, which is difficult at best Same proportion of males in the sample as in the population … Same range of income level in families; same type of abuse ALSO, may be the entire population of agency clients, …..or social work students at one university, …. or all business in one state.. All children who have been abused

5. Two MAJOR/MAIN/MOST IMPORTANT sampling methods • PROBABILITY or random • every one has an equal chance to be a part of the sample • More representative of the population • Findings from representative samples are more generalizable to the population • NONPROBABILITIY or nonrandom • individuals included in sample in way other than by random sampling • Don’t know whether or not it is representative of the population • Findings from non-representative samples are NOT generalizable to the population

6. Is your sample generazible to your target population known as sample generalizability … to other populations? known as cross-population generalizability Focus of this chapter

7. What is sampling error • Sampling error: • any difference between the characteristics of a sample and the characteristics of a population from which it was drawn.

8. Methods of random sampling.. Also known as probability sampling • Simple Random Sampling • Identifies cases strictly on the basis of chance • Systematic Random Sampling • First element is selected randomly, and then every nth element is selected • Stratified Random Sampling • All elements in the sampling frame are distinguished according to their value on some relevant characteristic(s) • That characteristic forms the sampling strata • The size of each stratum in the population must be known • Elements are randomly selected from within the strata • Each element may belong to one and only one strata • Proportionate stratified sampling: Each sampling stratum represents exactly its proportion in the population • Disproportionate stratified sampling: The proportion of sampling strata are intentionally varied from what it is in the population • Cluster sampling • Useful when sampling frame is not available • Cluster: a naturally occurring, mixed aggregate of elements in a population, with each element occurring in one and only one cluster

9. Questions about Stratified Random Sampling Percentages same as in the population As many black, white, hispanic, asian as IN THE POPULATION Percentages same as EACH Other As many blacks as whites as Hispanic as asian

10. Questions about Cluster Sampling Another cluster A cluster

11. Methods of non-random sampling.. Aka non-probability sampling • Availability sampling • Also known as convenience sampling, accidental sampling, and haphazard sampling • Selection of elements is done by what is available and/or convenient to researcher • Quota sampling • Quotas: pre-set number of elements based on characteristics in a population to ensure that the sample represents those characteristics in proportion to their prevalence in the population • Purposive sampling • Each element is selected for a purpose, usually because of unique position of the sample elements • Snowball sampling • Identify one member of a population and speak to him/her and then ask that person to identify others in the population and speak to them, then ask them to identify others and so on

12. How does quota sampling differ from stratified sampling? • Stratified sampling starts with a random sample… quota sampling does NOT have a random sample approach • How does availability sampling differ from purposive sampling? • Sometimes used interchangeably.. Purposive sampling is more intentional, more specific • Availability = students at the student center; • General population, on the street • Purposive = only female students at the student center • Individuals in a nursing home

13. The idea of and terminology of sampling error Do not need to know this in detail.. Just general idea • Probability sampling theory is used to estimate how representative the sample is of the population it was drawn from .. or the amount of sampling error • Based on the ‘theory’ of normal distributions • Normal sampling distribution .. • Consider the population of social work graduate students across the country • This population has a mean (average) age of 28 • Chances are that every time you take a sample from this population, the average age of your sample may not be 28..but may be 26 or 31 or 29.. • Sampling theory says that if you take an infinite number of samples from this population, and plot each of the sample mean on a graph or bell curve, the mean age of all the samples will be 28..the REAL mean age of the population

14. Determining a Sample Size Do not need to know this in detail.. Just general idea • The less sampling error desired, the larger the sample size must be • Samples with more homogenous populations can be smaller than samples of more diverse populations • Stratified random samples can be smaller than simple random samples • If the only analysis planned for a survey sample is to describe the population in terms of a few variables, a smaller sample is required than if a more complex analysis involving subgroups is planned • If much of the analysis will focus on estimating the characteristics of subgroups within a sample, the size of the subgroups is more important than the size of the total sample • When detecting very strong relationships among variables, a smaller sample is required than if testing weaker relationships • Current practices as guidelines • National surveys: 1000-2500 • Local or regional: a few hundred

15. A WORD ABOUT SURVEY RESEARCH

16. II. WHERE IS SURVEY RESEARCH IN THE Overview of Research (Deductive) Process(Research Decision Tree) Survey research deciding about the method of data collection… it is the HOW of the research process Problem Idea Theory What How Who (variables) (methods) (sample) Data Collection Data Processing Data Analysis Discussion and Application

17. II. WHERE IS SURVEY RESEARCH IN THE Overview of Research (Deductive) Process(Research Decision Tree) Survey research deciding about the method of data collection… it is the HOW of the research process Problem Idea Theory How (methods) what is your method.. what type of research... experimental, non-experimental... ... How will you collect data Interview,questionnaire,secondary data analysis,observatio

18. Survey: A noun or a verb The process or the product • The survey as a methodology, an approach, to data collection • Different types of surveys • Issues around response rates • Writing questions to use in surveys • Design of the survey instrument (questionnaire) Survey Research is concerned with issues of measurement validity and external validity (sampling)

19. What are the different Ways to collect data Included in Survey methods Interviews (face to face… phone.. ) Questionnaire (mailed.. Electronic) Observations Secondary sources (client records, large national public domain data sets)

20. Key points re Definition of Survey Research • collects information/data • from a sample of individuals • responses to standardized questions. Everyone who is surveyed is asked the same questions Standardized questions are NOT the same thing as a standardized instrument

21. Why use survey research? • Three advantages • Versatility • Efficiency • Generalizability Know survey research as well as you know your best friend…

22. Measurement issues – the WHAT that you are studying How you are operationalizing your variables What types of problems (errors) common in survey research • Errors of observation: poor measurement of cases that are surveyed • Errors of nonobservation: omission of cases that should be surveyed • Three sources of errors of nonobservation • Nonresponse can distort the sample when individuals refuse to respond or cannot be contacted • 70% is a minimum response rate to speak to representativeness • Nonresponse rates are increasing in the US and Western Europe • Benefits of participation must outweigh the costs if you expect people to participate • Clear and interesting questions and presenting them in a well organized questionnaire will improve response rate • Coverage of the population may be inadequate due to a poor sampling frame • Sampling error (differences between the characteristics of sample members and population that arise due to chance Sampling issues.. Who you are surveying.. And are they representative of the population