Chapter 9 - Examining Populations and Samples in Research Flashcards
a particular group of individuals or elements to be studied (ex: patients with heart failure or intravenous catheters)
population
all elements that meet the sampling criteria for inclusion in a study
target population
portion of the target population to which the researcher has reasonable access
accessible population
the selected group of people or elements with which to conduct a study; should represent an identified population of people
sample
extending the findings from the sample under study to the larger population
generalization
process of selecting a group of people, events, behaviors, or other elements that are representative of the population being studied
sampling
list of the characteristics essential for membership in the target population
sampling criteria
characteristics that the study participant or element must possess to be part of the target population (ex: “In this study, the sampling criteria may include adults 60 years of age or older, ability to speak and read English, and undergoing a surgical replacement of one knee joint.”)
inclusion sampling criteria
characteristics that can cause a people who meets the inclusion criteria to be excluded or removed from the target population (ex: “Those patients with a history of previous joint replacement surgery, diagnosis of dementia, or diagnosed with a debilitating chronic muscle disease will be excluded.”)
exclusion sampling criteria
the sample, accessible population, and target population are alike in as many ways as possible
representativeness
The expected difference in values that occurs when different participants from the same sample are examined. As sample size increases, this decreases, resulting in more values closer to the mean, which improves representativeness.
random variation
A consequence of selecting study participants whose measurement values differ in some specific way from those of the population. Usually expressed as a difference in the average values between the sample and population. Most of the variation from the mean is in the same direction.
systematic variation, or systematic bias
each person or element in a population has an opportunity to be selected for a sample; all the subsets of a population have a chance to be represented in the sample
higher generalizability
probability sampling (random sampling)
a list of every member of the population, using the sampling criteria to define eligibility
sampling frame
sampling method that involves random selection of subjects from the sampling frame for a study
most commonly used for quantitative research
simple random sampling
sampling method used when the researcher knows some of the variables in the population that are critical to achieving representativeness; the sample is divided into strata or groups using these identified variables
most commonly used for quantitative research
stratified random sampling
sampling method in which a frame is developed that included a list of all groupings (e.g., states, cities, institutions, or organizations) that could be used in a study; a randomized sample of these states, cities, institutions, etc, can then be used in the study.
most commonly used for quantitative research
cluster sampling
sampling method used when an ordered list of all members of the population is available; every __th individual from the list is selected, using a randomly selected starting point
most commonly used for quantitative research
systematic sampling
sampling method in which not every element of the population has an opportunity for selection; this approach decreases a sample’s representativeness of a target population but is commonly used in nursing studies because of the limited number of patients available for research
nonprobability sampling (nonrandom)
sampling method that involves including subjects in a study because they happened to be in the right place at the right time
most commonly used for quantitative research
convenience sampling
convenience sampling method with an added strategy to ensure the inclusion of subjects who are likely to be underrepresented in the convenience sample, such as women, minority groups. The goal of this sampling method is to replicate the proportions of subgroups present in the target population
most commonly used for quantitative research
quota sampling
sometimes referred to as judgmental or selective sampling
involves the conscious selection by the researcher of certain subjects or elements to include in a study
most commonly used for qualitative research
purposeful or purposive sampling
sometimes referred to as snowball, chain, or nominated sampling
sampling method that takes advantage of social networks and the fact that friends tend to hold characteristics in common; subjects meeting sample criteria are asked to assist in locating others with similar characteristics
most commonly used for qualitative research
network sampling
sampling method often used in grounded theory research to develop a selected theory through the research process
most commonly used for qualitative research
theoretical sampling
number of individuals participating in the study
sample size
When do questions occur about the adequacy of the sample size in quantitative studies?
Questions about the adequacy of the sample size occur only when no significant difference is found. If the study was designed to make comparisons and significant differences were found, the sample size was adequate.
used to evaluate the adequacy of the sample size in quantitative studies
power analysis
the ability of a study to detect differences or relationships that actually exist in the population; aka the ability to reject a null hypothesis correctly
power
What is the minimum acceptable level of power for a study?
The minimum acceptable level of power is 0.8, or 80%. This power level results in a 20% chance of a Type II error, in which the study fails to detect existing effects (differences or relationships).
the extent to which the null or statistical hypothesis is false or, stated another way, the strength of the expected relationship between two variables or differences between two groups
easier to detect with larger samples
effect size
factors that affect what makes an adequate sample size in QUANTitative studies
- effect size (when effect size is large, detecting it is easier and can be done with a smaller sample)
- type of studies (quasi-experimental and experimental studies use smaller samples more often that descriptive and correlational studies)
- control (as control, reliability, and validity increase, the sample size can be decreased)
- number of variables (as the number of variables increases, the sample size may need to decrease)
- measurement sensitivity (as accuracy and precision decrease, the sample size needed to obtain significance increases)
- data analysis techniques (the power of the analysis technique increases as precision in measurement increases)
When is the number of participants in a qualitative study adequate?
When the newly collected data begins to be the same as what as already been collected (saturation)
factors that affect what makes an adequate sample size in QUALitative studies
- scope of the study (broad scope = needs larger sample)
- nature of the topic (difficult to define & awkward to discuss = needs larger sample)
- quality of information (high data quality = fewer participants needed)
- study design (multiple interviews are conducted with subjects = higher data quality)
site or location used to conduct a study
based on purpose of study, accessibility of sites, and number/types of participants available in site
research setting
an uncontrolled, real-life situation or environment; researcher does not manipulate or change the environment for the study (ex: participant’s home)
natural or field setting
environment that is manipulated or modified in some way by the researcher
partially controlled setting
an environment structured for the purpose of conducting research, reducing the influence of extraneous variables (ex: laboratories, research centers, test centers in hospitals)
highly controlled setting
