NRSG 790: Methods for Research and Evidence Based Practice Sampling

Purpose of Sampling Sampling is the process of selecting a representative part of a population for the purpose of determining characteristics of the whole population The purpose of sampling is to be able to draw conclusions about populations from smaller samples Findings from the sample are generalized back to the population that the sample was originally selected from

Sampling Terms Population - a group of individuals from which samples are taken Target Population – population of interest, ie, Category 5 Hurricane Victims Accessible Population – population you have access to, ie, Hurricane Katrina Victims Sample – a part of a population whose properties are studied to gain information about the whole (Webster, 1985) ie, Hurricane Katrina Victims who agree to participate in your study Researchers must use samples because it is not feasible to study all members of a population

Sample Bias/Error A sample is expected to mirror the population from which it comes When it does, you have external validity – the ability to generalize findings There is no guarantee that any sample will be precisely representative of the population Unrepresentative samples are caused by making sampling errors Sampling error occur because of: One, chance – just bad luck. The main protection against this kind of error is to use a large enough sample. Two, sampling bias – design flaw. The main protection against this is a good sampling plan (probability sampling)

Types of Quantitative Samples Probability Non-Probability Simple random sampling Stratified random sampling Cluster random sampling Systematic random sampling Involves Random Selection Every one in the population has an equal chance of getting into the sample. DO NOT confuse random sampling with random assignment. Convenience sampling Snowball sampling Quota sampling Purposive sampling These are discussed in more detail in the Module and readings

Determining Sample Size Before deciding how large a sample should be, you have to define your study population. For example, victims of Hurricane Katrina Then determine your sampling frame a list of all the residents in New Orleans Power Analysis is a procedure that is performed to tell you how many from this list you need to include in your study to achieve valid results See the Power Analysis Topic in the Module for details

Check Your Understanding What type of sampling technique does this is describe: A researcher recruits 60 participants from a clinic population. The researcher then randomly assigns the participants into the intervention and control group.

Answer Convenience sampling (non probability) this is when the most convenient participants are chosen from a population for observation The researcher does not randomly select the sample Do not be confused by what the researcher does after s/he recruits the participants – assignment to groups

Check Your Understanding What type of sampling technique does this is describe: A researcher has a list of 100 patients. S/he wants a sample of 25 people S/he randomly selects a starting point and takes every 4th person on a patient list

Answer Systematic (probability) - Simple Random each person in the population has an equal chance of being selected The researcher calculated a sampling interval and has a random starting point. A simple random sample is free from sampling bias

Check Your Understanding What type of sampling technique does this is describe: A researcher divides her sampling frame into BNS, MS, and PhD students She wants to have equal amount of each level of education

Answer Quota (non probability) taking a tailored sample that’s in proportion to some characteristic or trait of a population The researcher does not randomly select the sample The researcher divides the list into strata and then takes equal amounts from each stratum.

Check Your Understanding What type of sampling technique does this is describe: A researcher randomly selects a state in the United States, then randomly selects a county in the state, and then randomly selects a census tract in the county to study low income families.

Answer Cluster (probability) - making multiple random selections A cluster sample is obtained by selecting clusters from the population on the basis of simple random sampling. The researcher randomly selected the sample Cluster sampling is susceptible to sampling bias