Unit 3: Ch. 10 Flashcards
population
the aggregate of cases in which a researcher is interested
“aggregate” = everybody in the population
sample
the selection of the portion of the population
-subgroup of the population
"N" = entire sample "n" = subgroup of entire sample
eligiblity criteria
characteristics that define the population
Types:
- inclusion criteria
- exclusion criteria
inclusion criteria
characteristics that you want your sample to have for being in the study (what qualifies them to be in the study)
ex: postpartum study - you want to study only first time adolescent moms ages 14-19
exclusion criteria
characteristics that your sample may have that keeps them out of the study (things that disqualify them/exclude them from being in the study)
ex: pregnancy complications such as preeclampsia - if any of the moms in the study had preeclampsia, that excludes them from being in the study
strata
subpopulation of the population (“layers”)
ex: dividing one group further into subgroups
sometimes males and females in each group
target population
entire population of interest
ex: every adolescent mother in the US
accessible population
proportion of the target population who is actually accessible to the researcher
ex: target population is every adolescent in the US but the researcher can only access the ones within 40 miles
representative sample
a sample whose key characteristics closely approximate the population
-want your sample to be as representative of the whole population as possible
ex: our class is representative of BSN students general but our class is NOT representative of the whole university in general (b/c there are various majors at MU)
representative sampling is most easily achieved with…? (3)
- probability sampling
- homogenous sample/population
- larger samples
probability sample
random selection or random assignment
homogenous sample/population
where population is alike on key characteristics
larger samples
more of whatever the characteristic is that you’re looking for
-but you don’t want your sample to be too large (largeness has its limits)
sampling bias
the systematic over- or underrepresentation of segments of the population on key variables when the sample is NOT representative
happens when the sample is NOT representative
sampling bias slants your results one way or the other so that the results aren’t actually what you think they are
what are 2 sampling designs in quantitative studies?
- nonprobability sampling
2. probability sampling
nonprobability sampling
involves nonrandom selection; 5 types exist
- Convenience sampling: people who meet the inclusion and exclusion criteria but they’re people who are convenient for the researcher to access
- ex: collecting data at a clinic - the convenience sample would be whoever shows up at the clinic that day
- The most common type of sampling used in nursing; most vulnerable to bias. - Snowball sampling: people in the study help you recruit others to be in your study
- used more in qualitative studies - Quota sampling: recruitment of a certain subgroup based on certain characteristics to represent the sample (may have a number in mind of how many people you need)
- keep sampling until you reach your quota - Consecutive sampling: recruitment of people from the accessible population who meet the eligibility criteria for a certain period of time
- Purposive sampling: recruitment of participants based on personal judgment of the researcher about who will be the most informative; used a lot in qualitative studies
probability sampling
involves random selection of subjects and each subject has an equal, independent chance of being selected; 4 types exist
- Simple Random sampling: selection of sample via a random procedure
- ex: pulling names out of a hat - Stratified Random sampling: subdivisions of the population according to some characteristic
- ex: race, gender - Cluster sampling: multi-stage sampling in which large clusters/groups are selected with successive subsampling of smaller groups
- ex: going to do a study. Randomly selects 5 states out of 50 that you want to get your sample from. In each of those 5 states, randomly select 1 city to collect sample. Within each city, select a single hospital; within each hospital, select a single unit to actually collect the data from - Systematic sampling: where every 5th, 10th, nth person is selected (researcher decides how many)
Snowball and purposive sampling are mostly used in ____ studies.
qualitative
What are the 5 types of nonprobability sampling?
- convenience sampling
- snowball sampling
- quota sampling
- consecutive sampling
- purposive sampling
What are the 4 types of probability sampling?
- simple random sample
- stratified random sampling
- cluster sampling
- systematic sampling
sample size
defined as the number of study participants in the final sample
- sample size adequacy: need a sample that’s the perfect size
- sample size needs can and should be estimated through a power analysis
power analysis
purpose of a power analysis is to determine the appropriate sample size
sample size too small: sample may not have characteristics you need
sample size too big: the characteristics you’re looking for will eventually emerge b/c the sample is too big
The basic decision in the types of data collection is the use of?
- new data
2. existing data
new data
collected specifically for research purposes (primary data, primary analysis)
existing data
records (e.g. pt charts)
historical data
existing data set (secondary analysis)
it’s ok to use existing data in qualitative studies
what are the 3 types of data collection methods?
- self reports
- observation
- biophysiologic measures
self-reports
Participants themselves report on whatever it is. These data are collected with formal instruments such as questionnaires or interviews. There are some things that only the participant can tell you what it is.