Population and Samples

Let's discuss Sampling Criteria: Exclusion.

**Characteristics that can cause a person or element to be excluded from the target population.** Examples: Less than 18 years of age Diagnosis of cognitive dysfunction Unable to read or speak English

Lets discuss Sampling Criteria: Inclusion.

**Characteristics that the subject or element must possess to be part of the target population** Examples: Between the ages of 18 and 45 Ability to speak English Admitted for gallbladder surgery Diagnosed with diabetes within past month

What are two Methods of Sampling?

**Probability Sampling/Random Sampling.** Simple, stratified, cluster, systematic **Non-probability Sampling** Convenience, "quota", purposive, network, theoretical

Lets discuss Sampling Error variation exists among people.

**Random variation exists among people** You can expect differences in values when different subjects from the same sample are examined **Difference between the population mean and the mean of the sample is called the "sampling error"**

What are 3 types of Probability Sampling/Random Sampling?

**Simple:** Using a table of random numbers or other randomizing technique to select the individuals from a target population who are invited to participate in the study. **Stratified/Cluster:** Identifying key variables (gender, age, geographic location), and randomly selecting participants from a large pool of candidates that have those certain characteristics **Systematic:** Simply another strategy for achieving a random sample- starting randomly on a list and then taking ever "X" number of participants on that list.

What is Convenience sampling?

A method of selecting participants based on groups of individuals who are readily available. Non-probability sampling

Target Population

A more specific set of individuals who you are interested in studying.

Population

A particular group of individuals who are the focus of the research.

Interpretation and Generalization of the Findings related to Number of Variables.

As the number of variables increases, the sample size needs to increase. General rule: 10 to 20 participants per variable you are studying.

What are 5 types of Non-probability sampling?

Convenience sampling Quota sampling Purposive Sampling Network Sampling, aka "snowball sampling" Theoretical Sampling

Sample

Defines the selected group of people from the target population from which data are collected for a study Members of the sample can be called the subjects or participants.

What is the general rule for how many participants per variable?

General rule: 10 to 20 participants per variable you are studying.

Heterogeneous Sample

Heterogeneous sample: Represents a broader range of people in a population.

Homogeneous Sample

Homogeneous sample: As similar as possible so as to control for extraneous variables

How is Sampling Criteria defined?

Homogeneous sample: As similar as possible so as to control for extraneous variables Heterogeneous sample: Represents a broader range of people in a population.

Interpretation and Generalization of the Findings related to the Measurement Sensitivity.

How exact and specific is your measurement tool? If there is a wide range of possible scores, it may take more participants to observe/measure a change.

What are some Factors that affect who is included in a sample?

Inclusion Exclusion Refusal Rate vs. Acceptance Rate Sample Attrition and Retention Sampling Error

What is Network sampling?

Network Sampling, aka "snowball sampling": Takes advantage of social networks to get the sample. One person in the sample asks another to join the sample, and so on. Non-probability sampling

Lets discuss Sample retention.

Number of subjects who remain in and complete a study.

Interpretation and Generalization of the Findings related to Sample Size in Quantitative Studies.

Number of variables you can study Measurement sensitivity Data analysis techniques Effect sizes

Lets discuss Acceptance rate.

Percentage of subjects who consented to be in the study. 80 subjects approached and 76 accepted 76/80=0.95 = 95% acceptance rate

Lets discuss Refusal rate.

Percentage of subjects who declined to participate in the study 80 subjects approached and 4 refused 4/80=0.05 = 5% refusal rate

Interpretation and Generalization of the Findings related to the Power Analysis.

Power Analysis is a way to figure out the minimum number of people needed in your study in order to detect a difference. Minimize the chance of false-positives and false-negatives. If the study did not find the results they expected, you have to ask whether they had a large enough sample to detect a difference. "Under-powered", "Lack of power" Never will be "over-powered"!

What should Probability Sampling/Random Sampling do?

Random sampling should increases how well the sample represents the target population/

Difference between the population mean and the mean of the sample is called the ______________________.

Sampling Error

What needs to be evaluated in the context of Representativeness?

Setting Characteristics of subjects (age, gender, ethnicity, income, education) Distribution of values on variables measured in the study

What is Purposive sampling?

Similar to Quota sampling, deliberate efforts are made to include certain types of participants. Researcher may chose to include atypical participants to help clarify or illuminate certain findings in the study. Non-probability sampling

Lets discuss **Simple** Probability Sampling/Random Sampling.

Simple: Using a table of random numbers or other randomizing technique to select the individuals from a target population who are invited to participate in the study.

Lets discuss **Stratified/ Cluster** Probability Sampling/Random Sampling.

Stratified/ Cluster: Identifying key variables (gender, age, geographic location), and randomly selecting participants from a large pool of candidates that have those certain characteristics

Lets discuss **Systematic** Probability Sampling/Random Sampling.

Systematic: Simply another strategy for achieving a random sample- starting randomly on a list and then taking ever "X" number of participants on that list.

Generalization

The ability to extend the findings from the sample in the study to the larger population that the sample represents. How well the study's findings can be generalized to the broader population is influenced by the quality of the study, the size of the sample, and how well the sample represents the larger group.

Interpretation and Generalization of the Findings related to the Effect Size.

The effect is how easily the phenomenon being studied is observed. When the effect size is large, it will show up in a smaller sample. If the effect size is small, you'll need a large sample in order to see the change. Increasing the sample size typically increases the effect size.

Accessible Population

The portion of the target population to which the researcher has reasonable access.

Representativeness

The sample, the accessible population, and the target population are alike in as many ways as possible. **Need to evaluate:** Setting Characteristics of subjects (age, gender, ethnicity, income, education) Distribution of values on variables measured in the study

What is Theoretical sampling?

Theoretical Sampling: Similar to purposive sampling, participants are selected because of certain qualities that are sought after by the researcher Non-probability sampling

What is Quota sampling?

Uses convenience sampling, but with a strategy to ensure inclusion of subject types who are likely to be underrepresented in the convenience sample Goal is to replicate the proportions of subgroups present in the population Non-probability sampling

Lets discuss Sample attrition.

Withdrawal or loss of subjects from a study