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Essentials of Nursing Research chp 10
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Sampling and Data collection in quantitative studies
Terms in this set (31)
self-report
data are participants' responses to questions posed by the researcher, such as an interview; most commonly used
scale
used to make fine quantitative discriminations among people with different attitudes, traits.
response set bias
the measurement error resulting from the tendency of some individuals to respond to items in characteristic ways (e.g. always agreeing), independently of item content
population
the entire group of interest
target population
the entire population in which a researcher is interested
accessible population
the portion of the target population that the researcher can use.
sampling
selecting a portion of the population to represent the population
sample
a subset of population events
representative sample
a sample whose characteristics closely approximate those of the population
sampling bias
the systematic over-representation or under-representation of some segment of the population in terms of key characteristics
strata
subpopulation
non-probability sampling
researchers select elements by nonrandom methods in which every element usually does not have a chance to be included
convenience sampling
entails selecting the most conveniently available people as participants
quota sampling
researchers identify population strata and figure out how many people are needed from each stratum
consecutive sampling
a nonprobability sampling method that involves recruiting all people from an accessible population over a "specific time interval", or for a specified sample size
purposive sampling
based on the belief that researchers' knowledge about the population can be used to hand-pick sample members
probability sampling
involves random selection of elements from a population
random sampling
each element in the population has an equal, independent chance of being selected
simple random sampling
basic probability sampling involving the selection of sample members from a sampling frame through completely random procedures. elements are numbered and then a table of random numbers or an online random sample generator is used to draw a random sample.
stratified random sampling
the random selection of study participants from two or more strata of the population independently
systematic sampling
the selection of sample members such that every K-th (e.g. every 10th) person or element in a sampling frame is choses
sample size
the number of study participants
power analysis
a procedure for estimating either the needed sample size for a study or the likelihood of committing a Type II error
likert scale
summated rating scales/attitues. declarative statements (items) agree/disagree continuum (5-7)
visual analog scale
measures subjective experiences (pain, nausea, fatigue) to 100 mm end point = extreme limits of sensation
probability sampling, homogeneous populations, and larger samples
a representative sample can be easily achieved by
error=random
bias=systematic
some that distorts the findings in the study two kinds and distinguish
simple random sampling.
this probability sampling is not subject to bias and there's no guarantee of a representative sample but it IS random.
stratified random sampling
probability sampling that is to enhance representativeness
sampling error
differences between population values (average age of population) and sample values (the average age of sample)
response set biases
-social desirability response set bias (you pick the answer that others would choose)
-extreme response set (emotionally charged; strong runs fully love/hate no middle)
-acquiescence response set (yea-sayers; yes/no to everything: not reading survey)
biases reflecting the tendency of some people to respond to items in characteristic easy, independently of item content. name them
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