Research, Chapter 12, Populations and Samples in Research

Sampling frame

A listing of every member of the accessible population eligible to participate. Subjects are selected from the sampling frame.

If the effect size is large, how large of a population do we need?

A small population is sufficient

The population from which the researcher selects the actual study sample is referred to as the: Accessible population. Scientific population. Target population. Theoretical population.

A. Accessible population

Target population

An entire set of individuals or elements who meet the sampling criteria

Homogenous sample

As similar as possible so as to control for extraneous variables will decrease credibility to generalize it to others. Better for internal validity

How do variables affect sample size?

As the number of variables increases, the sample size may increase. The inclusion of multiple dependent variables also increases the sample size needed.

In a study of children with asthma, a researcher wants to examine the impact of a school nurse being available during recess. The researcher decides to use children between the ages of 5-12, who attend a school with a school nurse and a designated time for recess. A child who is 4 years old meets: Inclusion criteria Eligibility criteria Exclusion criteria Sampling criteria

C. Exclusion criteria

Exclusion criteria

Characteristics that can cause a person or element to be excluded from the target population

Inclusion criteria

Characteristics that the subject or element must possess to be part of the target population

Systematic variation

Consequence of selecting subjects whose measurement values differ in some way from those of the population Values are similar to those of others in the sample but different in some way from those of the population as a whole Serious concern in sampling Sample size has no impact Need to be mindful when making conclusions Chances increase if don't use random sampling

Sampling in research may be defined as: Insurance that each person has a chance of being included in the study. Establishment of criteria for eligibility to participate in a study. Identification of the population in which the researcher is interested. Selection of a subset of a population to represent the whole population.

D. Selection of a subset of a population to represent the who population

A researcher wishes to evaluate the treatment effects of a new exercise therapy on the recovery after abdominal surgery. Patients who have had abdominal surgery are an example of the following? Accessible population Element of the population Sample population Target population

D. Target population

Sample

Defines the selected group of people or elements from which data are collected for a study

Probability sampling

Each person or element in a population has an opportunity to be selected for a sample Increase representativeness Decrease systematic variation Each person has an opportunity to be selected for a sample Selection is left to chance, not up to the researcher's decision 1. simple random sampling, 2. stratified random sampling, 3. cluster sampling, 4. systematic sampling

How is sample size in quantitative studies determined? (5)

Effect size Type of quantitative study conducted Number of variables Measurement sensitivity Data analysis techniques

Random variation

Expected difference in values that occurs when different subjects from same sample are examined Difference is random because some values will be higher and others lower than the average population values Larger sample decreases random variation

Generalization

Extending the findings from the sample under study to the larger population The extent is influenced by the quality of the study and consistency of the study's findings.

What are 2 ways to define sampling criteria?

Homogenous sample Heterogenous sample

Appraising the sample

Identify the sample criteria. Judge the appropriateness of the sampling criteria. Identify the sampling method.

How does retention rate related to representativeness of a sample?

If retention rate is low (like 10-20%), meaning that it tells you about the quality of the study.

Eligibility criteria

Include the list of characteristics essential for eligibility or membership in the target population. The sample is selected from the accessible population that meets the sampling criteria. Inclusion and exclusion criteria

Elements

Individual units of the population and sample

Non-probability sampling

Not every element of a population has an opportunity to be selected for a study sample Commonly used in nursing studies 1. convenience sampling, 2. quota sampling, 3. purposive or purposeful sampling, 4. network sampling, 5. theoretical sampling

Sample retention

Number of subjects who remain in and complete a study Retention rate= (number of subjects completing the study ÷ sample size) X 100 Using the example above: 76/80 X 100 = 95%

Convenience sampling

Participants are included in the sample based on being at the right place at the right time Advantages: inexpensive, accessible, and time saving Can have a convenient sample that is randomly assigned to treatment or control group Hard to control for biases

Acceptance rate

Percentage of subjects who consented to be in the study

Refusal rate

Percentage of subjects who declined to participate in the study

Order from most general to most specific population into research

Population Target population Accessible population Sample Study Element - Subject or participant

Power analysis

Power is the ability of the study to detect difference or relationships that actually exist Want to set the power at 0.08 This means that there is only a 20% chance of having a type 2 error or 80% chance that we have enough people in the sample to find significant differences

Two types of sampling

Probability (random) Non-probability (not random)

Sampling plan

Process whereby the researcher selects subjects from the accessible population. Probability sampling plans 1. Random (probability) sampling 2. Nonrandom (nonprobability) sampling

What 5 factors are part of the representative of a sample?

Random and Systematic Variation of Subjects' Values Acceptance and Refusal Rates Sample Attrition and Retention Rates Sampling Frames Sampling Methods or Plans

Simple random sampling

Randomly selecting from the sampling frame Use computer program or table of random numbers

Heterogenous sample

Represents a broad range of values Used when a narrow focus is not desirable will decrease credibility to internal validity. Better for external validity

Subjects who participate in a study of patients with inflammatory bowel disease are described as the: Accessible population. Element. Sample. Target population.

Sample

Representativeness of a sample

Sample, accessible population, and target population are alike as possible Want to evaluate in terms of setting, characteristics of subjects, and distribution of values on variables measured in the study.

Representiveness

Sample, accessible population, and target population are alike as possible Want to evaluate in terms of setting, characteristics of subjects, and variables measured

Sampling

Sampling involves selecting a group of elements from an identified population for the purpose of conducting research. The group of elements is then called the sample. A sample selected in a study should represent an identified population of people Sampling theory was developed to determine the most effective way to acquire a sample that accurately reflect the population under study

Purposeful sampling

Sampling is based on the researcher's judgment

What are the concepts related to sampling?

Selecting a group of people, events, behaviors, or other elements with which to conduct a study

Network sampling or 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.

Accessible population

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

Systematic sampling

Use a list and select every nth person on the list using a random start point

Cluster sampling

Use location to cluster subjects, sometimes it's called as multistage sampling. a researcher divides the entire population into clusters or groups, such as cities, institutions, or units, with which elements of the identified population can be linked. The researcher then selects a random sample of these clusters and proceeds to use all observations in the selected clusters in the sample.

Theoretical sampling

Used in grounded theory research Data are gathered from any individual or group that can provide relevant data for theory generation. The sample is saturated when the data collection is complete based on the researchers' expectations. Diversity in the sample is encouraged.

Measurement sensitivity

Well-developed physiological instruments are needed to measure phenomena with accuracy and precision and makes a modest sample A large variance occurs with a less well-developed tool

Sample attrition

Withdrawal or loss of subjects from a study Attrition rate = number of subjects withdrawing ÷ number of study subjects × 100 If in a study of 80 participants, 4 withdraw the attrition rate = 4/80 X 100= 5%

Quota sampling

a convenience sampling technique with an added feature to ensure the inclusion of subject types Using stratification for selecting variables to represent more of the target population Likely to include those are underrepresented in the convenience sample: females, minority groups, older adults, poor, rich, and undereducated

Effect size

is the percentage change in a variable; in correlational research, it is the numerical strength of the proposed relationship. The effect size tells us how much difference there is between groups or the strength of relationship between two variables A large effect size means that there is a considerable difference between groups

Stratified random sampling

the researcher predetermines which subgroups of the population it is necessary to sample; the researcher then decides whether these subgroups will be selected in accordance with their actual population proportions to achieve a representative sample Use when need to achieve adequate sample that represent needed variables Ensures all levels of identified variables are represented