Nur 351 Research Final - Batman

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The entire aggregation of cases in which a researcher is interested.

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Population

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Criteria that designates the specific attributes of a population, by which people are selected for inclusion in a study.

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Eligibility Criteria or Inclusion Criteria

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Criteria specifying characteristics that a study population does NOT have

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Exclusion Criteria

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An individual who participates and provides information in a study

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Study Participant

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The entire population in which a researcher is interested

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Target Population

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The cases of the target population that are accessible to the researcher as research participants

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Accessible Population

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The process of selecting a portion of the population to represent an entire population

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Sampling

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A subset of the population selected to participate in a study

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Sample

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A part of a population whose characteristics closely approximate those of the population; can only truly be achieved with probability sampling

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Representative Sample

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The systematic overrepresentation of underrepresentation of some segment of the population in terms of a characteristic relevant to the research question, affected by many things like homogeneity

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Sampling Bias

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Mutually exclusive segments of a research population based on a specific characteristic such as age groups

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Strata

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When researchers select elements by nonrandom methods; less likely to produce representative samples, but this accounts for most research samples in nursing

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Nonprobability Sampling

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A form of nonprobability sampling where the researcher uses the most conveniently available people as participants; snowball sampling is a variation; the weakest form of sampling

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Convenience Sampling

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A form of nonprobability sampling where early sampling members are asked to refer other people who meet the eligibility criteria

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Snowball Sampling (a form of Convenience Sampling)

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A form of sampling where researchers identify population strata and determine how many participants are needed from each stratum, often to ensure that diverse segments are adequately represented

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Quota Sampling

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A form of sampling that involves recruiting all of the people from an accessible population who meet the eligibility criteria over a specific time interval, or for a specified sample size

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Consecutive Sampling (a form of nonprobability sampling)

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Also known as judgmental sampling, this form is based on the belief that researchers' knowledge about the population can be used to hand-pick sample members; used by both quantitative and qualitative researchers (particularly the latter)

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Purposive Sampling

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This type of sampling involves the random selection of elements from a population; not to be confused with random assignment; the only viable method of obtaining representative samples; allows researchers to estimate the magnitude of sampling error

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Probability (Random) Sampling

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This sampling process is when each element in the population has an equal, independent chance of being selected

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Random Selection

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Using a sampling frame, this sampling method involves creating a list of population elements and selecting random members from this list; the most basic of probability sampling

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Simple Random Sampling

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A list of all random sampling population elements

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Sampling Frame

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A form of random sampling where the population is first divided into two or more strata to enhance representativeness, often dividing the population into unequal subpopulations

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Stratified Random Sampling

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Using a successive random sampling of units in a population to account for the fact that is may be impractical or impossible to account for all the elements; the first group is large groupings and then using successive stages of sampling

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Cluster Sampling

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This form of random sampling involves taking the _th case from a list, such as every 10th person, to achieve an essentially random sample

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Systematic Sampling

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This refers to the differences between the population values and the sample values

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Sampling Error

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The number of subjects in a sample; the larger, the more representative

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Sample Size

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Procedure for estimating either the needed sample size for a study or the likelihood of committing a Type 2 Error

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Power Analysis

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A form of snowball sampling used by qualitative researchers where early informants are asked to make referrals for other study participants

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Nominated Sampling

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A convenience sample used by qualitative researchers, where volunteers sometimes come forward and identify themselves as eligible partipants

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Volunteer Sample

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Deliberately selecting cases with a wide range of variation on dimensions of interest, as part of purposeful sampling in a qualitative study

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Maximum Variation Sampling

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These are cases qualitative researchers often use towards the end of data collection that fit the researchers' conceptualizations and strengthen credibility

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Confirming Cases

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These are cases qualitative researchers often use towards the end of data collection that do not fit the researchers' conceptualizations and challenge their interpretations, offering new insights about how the original conceptualization needs to be revised or expanded

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Disconfirming Cases

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This is a method of sampling that is most often used in grounded theory studies, involving decisions about what data to collect next and where to find those data to develop an emerging theory in the best way; unlike purposeful sampling, the point of this type of sampling is to discover categories and their properties

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Theoretical Sampling

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In qualitative research, this is the point at which sampling yields no new information and redundancy is achieved

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Data Saturation

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These are ethnographic research subjects who are highly knowledgeable about the culture and who develop special,ongoing relationships with the researcher and are often the researcher's main link to the "inside"; often chosen purposively

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Key Informants

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The rate of participation in a study, calculated by dividing the number of persons participating by the number of persons sampled

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Response Rate

Front 37

The measurement error resulting from the tendency of some individuals to respond to items in characteristic ways (e.g., always agreeing), independent of item content

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Response Set Bias

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A bias that can result when a nonrandom subset of people invited to participate in a study decline to participate

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Nonresponse Bias

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This refers to the sufficiency and quality of the data the sample of a qualitative study yielded

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Adequacy

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This is the degree of congruence between the sample of an original qualitative study and the people at another site where the original findings might be applied

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Fittingness

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These are participants' responses to questions posed by the researchers, as in an interview; the most common data collection approach in both qualitative and quantitative nursing studies

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Self-Report

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This is a type of qualitative self-report used when the researchers have no preconceived idea of the content or flow of information to be gathered; the aim is to eludicate respondents' perceptions of the world without imposing their own views

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Unstructured Interview

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This is a broad question asked in an unstructured interview to gain a general overview of a phenomenon, on the basis of which more focused questions are subsequently asked, like "What happened when you first learned you had AIDS?"

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Grand Tour Question

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These are interviews in qualitative research where the researchers have a list of topics or broad questions that must be addressed in an interview; a written topic guide is used to ensure all question areas are addressed

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Semi-Structured or Focused Interviews

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These are qualitative research interviews with groups of about 5 to 10 people whose opinions and experiences are solicited simultaneously, with the interviewer guiding the discussion according to a topic guide

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Focus Group Interviews

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These are narrative self-disclosures about individual life experiences; researchers ask respondents to describe, often in chronological order, their experiences regarding a specific theme

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Life History

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This is a method of obtaining data from study participants by in-depth exploration of specific factual incidents and behaviors related to the topic under study

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Critical Incident Technique

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This is a method of obtaining data by asking participants to use audio-recording devices to talk about decisions as they are being made or while problems are being solved, over an extended period

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Think Aloud Method

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__ questions are those in which the response alternatives are prespecified by the researcher.

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Close-Ended

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__ questions are those in which the participants are allowed to respond in their own words.

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Open-Ended

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A trial run used to determine whether the instrument used for data collection is useful in generating desired information

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Pretest

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This is a device that assigns a numeric score to people along a continuum, like a scale for measuring weight

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Scale

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This is a scaling technique for data collection that consists of several declarative statements that express a viewpoint on a topic, and respondents are asked how much they agree or disagree with the statement

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Likert Scale

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A scale for measuring attitudes toward a concept on a series of bipolar adjectives, such as good/bad, effective/ineffective, etc.

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Semantic Differential

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A scaling procedure used to measure certain clinical symptoms like pain or fatigue by having people indicate on a straight line the intensity of the symptom

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Visual Analog Scale (VAS)

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This type of bias reflects a tendency of some respondents to want to give answers that are consistent with prevailing social views

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Social Desirability Response Set Bias

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This type of bias reflects a tendency of some respondents to exaggerate their feelings on scales (ex. "strongly agree"), leading to distortions

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Extreme Response Set Bias

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This type of bias reflects a tendency of some respondents to agree with statements regardless of their content

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Acquiescence Response Set Bias

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This type of self-report involves brief descriptions of events or situations to which participants are asked to react; can be fictional or based on fact, structured to elicit info

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Vignettes

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In this type of self-report data collection, participants are provided a set of cards on which words or statements are written; they are asked to sort the cards along a bipolar dimension (for instance, agree or disagree)

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Q Sort

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Method of collecting data through the participation in (and observation of) a group or culture in naturalistic settings; social position of researcher determines what they will see; researcher must gain entree and then get back stage (to learn about the unstaged realities)

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Participant Observation

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A rich and thorough description of the research context and participants in a qualitative study

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Thick Description

Front 63

A method of recording in a systematic fashion the behaviors and events of interest that transpire within a setting, using categories for classifying what is observed

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Category System

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In a category system, an instrument used to record observed behaviors/phenomena

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Checklist

Front 65

This method of observational sampling provides a mechanism for obtaining representative examples of behaviors by selecting a specific time period from which to observe the behaviors

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Time Sampling

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This method of observational sampling provides a mechanism for obtaining representative examples of behaviors by selecting integral behaviors or events to observe

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Event Sampling

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This type of data measure is one performed directly within or on living organisms like blood pressure, temperature, etc

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In Vivo (Biophysiological)

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This type of data measure is one performed by extracting biophysiological material from subjects and subjecting it to analysis in labs

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In Vitro (Biophysiological)

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This is a daily record of events and conversations in a participant observation study

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Log

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This is the lowest level of measurement. This is simply giving numbers to different attributes in the same category, but the numbers do not have quantitative implications (i.e., they do not mean “more than” or “less than” another). For instance, using numbers to indicate gender.

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Nominal

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This level of measurement ranks objects based on their standing on an attribute; for instance, ranking people from shortest to tallest or lightest to heaviest is an example. Also, ranking a person’s ability to manage ADLs (1 = completely dependent, 2 = needs some assistance from another person, 3 = needs some mechanical assistance, 4 = completely independent) is an example. Does not tell us how much greater one level is to another.

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Ordinal

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This level of measurement tells us about the order of data points, and the size of the intervals in between data points. There is no true zero (for instance, the Celsius scale, or IQ tests, where differences between scores like 140-120 and 120-100 are presumed to be equivalent)

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Interval

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This level of measurement is essentially the same as a interval scale but with a true zero. For instance, weight is an example (there can be an absence of weight, and it is correct to say that 100 lbs is twice as heavy as 50 lbs).

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Ratio

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This is the true score of a measurement plus or minus the error of measurement

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Obtained Score

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This is the consistency with which an instrument measures the attribute. For instance, consider a weight scale – if you take someone’s weight every 5 minutes and you get 120 lbs, 125 lbs, 115 lbs, etc, you would question it. If you use a different scale and you get 120, 120, 120, and 119, you would consider this scale better than the first

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Reliability

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The three aspects of reliability

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Stability, internal consistency, equivalence

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This aspect of reliability simply means that the measuring instrument produces similar results on two separate occasions (you would compare the two scores using test/retest and employing a reliability coefficient to determine how close the scores are – reliability coefficients higher than 0.70 are considered adequate for test/retest reliability)

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Stability

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This aspect of reliability means that the items of an instrument are all measuring the same trait; this usually is determined using coefficient alpha or Cronbach’s alpha (the higher, the more internally consistent)

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Internal Consistency

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This aspect of reliability is the degree to which two or more independent observers agree about the scoring of an instrument; a high level of agreement means that measurement errors have been minimized; two or more interraters can review the instrument and rate it

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Equivalence

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This is the degree to which an instrument is measuring what it is supposed to measure

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Validity

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True or false - an instrument can be unreliable but still be valid

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False

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True or false - an instrument that is not valid can still be reliable

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True

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The four major aspects of validity

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Face Validity, Content Validity, Construct Validity, Criterion-Related Validity

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Aspect of validity; whether or not the instrument appears to be measuring the correct attribute.

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Face Validity

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Aspect of validity; the degree to which an instrument has an appropriate sample of items for the attribute being measured and adequately covers the domain

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Content Validity

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Aspect of validity; the degree to which the scores of an instrument match up with some external criterion, using a validity coefficient

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Criterion-Related Validity

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Aspect of validity; it is the extent to what is being measured was actually measured. To have this sort of validity, the test or measuring tool has to correlate with the theory of what is being measured. It addresses the question,"Are we measuring what we think we are measuring?"

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Construct Validity

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These evaluate the quality of new instruments used by researchers, providing information about the instrument’s reliability, validity, and other assessment criteria

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Psychometric Assessments

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This is the ability of a measure to identify a “case” correctly, that is, to screen in or diagnose a condition correctly. A measure’s sensitivity is its rate of yielding “true positives"

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Sensitivity

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This is the ability of a measure to identify noncases correctly, that is, to screen out those without the condition. A measure’s rate of finding “true negatives"

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Specificity

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This summarizes the relationship between specificity and sensitivity in a single number. It answers the question, “How much more likely are we to find that an indicator is positive among those with the outcome of concern with those for whom the indicator is negative?” It is the ratio between true positive results to false negative results.

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Likelihood Ratio

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This type of statistics is used to synthesize and describe data, using averages and percentages

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Descriptive

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Indexes that are calculated on data from a population

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Parameters

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Statistics that permit inferences about whether results observed in a sample are likely to occur in the larger population

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Inferential

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This is a systematic arrangement of numerical values from the lowest to the highest, together with a count or percentage of the number of times each value was obtained

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Frequency Distribution

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A distribution of values with two halves that are mirror images of each other

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Symmetrical Distribution

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The asymmetrical distribution of a set of data values around a central point, with one tail longer than the other (positive if to the right, and negative if to the left)

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Skewed Distribution

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A distribution with one peak

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Unimodal

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A distribution with two or more peaks

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Multimodal

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A distribution with two peaks

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Bimodal

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A symmetrical, unimodal, not very peaked distribution, often called a bell curve

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Normal distribution

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Three indexes of central tendency (index of typicalness)

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Mode, median, mean

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The number that occurs most frequently in a distribution

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Mode

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The point in a distribution that divides scores in half - the middle value

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Median

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The sum of all values in a distribution divided by the number of participants (the average) - usually the statistic reported in an interval or ratio measurement

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Mean

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This is the degree to which values on a set of scores are dispersed

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Variability

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The highest score minus the lowest score in a distribution

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Range

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The most widely used variability index, calculated based on every value in a distribution, and summarizes the average amount of difference of values from the mean

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Standard Deviation

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__ % of the scores in a normal distribution fall within 1 standard deviation from the mean.

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68

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__ % of the scores in a normal distribution fall within 2 standard deviations from the mean.

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95

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__ % of the scores in a normal distribution fall within 3 standard deviations from the mean.

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99.7

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A two dimensional frequency distribution in which the frequencies of two variables are cross-tabulated

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Contingency Table

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Index that summarizes the degree of relationship between variables, typically ranging from +1.00 (perfect positive relationship) to -1.00 (perfect negative relationship); reflects intensity and duration of relationship

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Correlation Coefficient

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An index designating the magnitude and direction of a relationship between two variables measured on at least one interval scale; also called "Pearson's r"

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Product Moment Correlation Coefficient (r)

Front 115

A two dimensional display showing the correlation coefficients between all pairs of a set of variables

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Correlation Matrix

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This is the proportion of people in a group who experienced an undesirable outcome

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Absolute Risk

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This index represents the comparison of the risk for an exposed group to an intervention to the risk of an unexposed group

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Absolute Risk Reduction (ARR) Index

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A way of expressing the chance of an event - the probability of an event occuring to the probability that it will not occur, calculated by dividing the number of people who experienced an event by the number for whom it did not

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Odds

Front 119

Taking various samples from a population and calculating the means of each; normally distributed and equals the population mean

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Sampling Distribution Of The Mean

Front 120

The standard deviation of a sampling distribution, such as the sampling distribution of the mean

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Standard error of the mean (SEM)

Front 121

The range of values within which a population parameter is estimated to lie, at a specific probability of accuracy (e.g., 95% CI)

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Confidence Interval

Front 122

The upper or lower limits of a confidence interval

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Confidence Limits

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An error created by rejecting the null hypothesis when it is true (researcher concludes that a relationship exists when in fact it does not - a false-positive)

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Type 1 Error

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An error created by accepting the null hypothesis when it is false (researcher concludes that no relationship exists when in fact it does - a false-negative)

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Type 2 Error

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This hypothesis states that no relationship exists between the independent and the dependent variable

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Null

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The risk of making a type 1 error (rejecting the null hypothesis) in a statistical analysis, established by the researcher beforehand (e.g., the 0.05 level)

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Level of significance (alpha)

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The probability of committing a type 2 error (accepting the null hypothesis) in a statistical analysis, estimated through power analyses

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Beta

Front 128

A statistic computed to assess the statistical reliability of relationships between variables (e.g., chi-squared, t)

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Test statistic

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Results of hypothesis tests that are deemed not by chance, at some specified level of probability

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Statistically significant

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Results of hypothesis tests that are deemed to be the potential result of chance fluctuation

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Nonsignificant result

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The data from a population upon which the index is applied (what most scientific questions are about)

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Parameter

Front 132

Statistics derived from analyzing two variables simultaneously to assess the empirical relationship between them

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Bivariate Statistics

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The two techniques used in statistical inferences

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Estimation of parameters; hypothesis testing

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A class of statistical tests that involve assumptions about the distribution of the variables and the estimation of a parameter

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Parametric Tests

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A parametric statistical test for analyzing the difference between two group means

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T-test

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A statistical procedure used for testing mean differences among groups on a dependent variable, while controlling for one or more covariates

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ANCOVA (Analysis of Covariance)

Front 137

A statistical procedure used for testing mean differences
among three or more groups by comparing variability between groups to variability within groups

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ANOVA (Analysis of Variance)

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A statistical test used to assess group differences in proportions; symbolized as x^2

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Chi-squared test

Front 139

Statistical procedures designed to analyze the relationships among three or more variables (e.g., multiple regression, ANCOVA)

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Multivariate Statistics

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A statistical procedure for understanding the effects of two or more independent (predictor) variables on a dependent variable

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Multiple Regression Analysis

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Part of a research article where researchers present interpretations of the results

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Discussion

Front 142

These are widely used guidelines for reporting information on clinical trials, including a flow chart for tracking participants through a trial

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CONSORT guidelines (Consolidated Standards of Reporting Trials)

Front 143

The extent to which random errors have been reduced, usually expressed in terms of the width of the confidence interval around an estimate

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Precision

Front 144

This is the measure of how strong the evidence is that the study’s null hypothesis is false (not an estimate of any quantity that is of direct relevance to practicing nurses)

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P-value

Front 145

These tell more about the precision and quantitative relevance of results than p-values

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Confidence Intervals

Front 146

A statistical expression of the magnitude of the relationship between two variables, or the magnitude of the difference between groups on an attribute of interest; refers to the magnitude of the effect under the alternate hypothesis. The effect size should represent the smallest effect that would be of clinical or substantive significance, particularly in comparing effectiveness of interventions

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Effect Size

Front 147

In quantitative studies, results that support the researcher's hypotheses

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Significant

Front 148

This is central to interpretation of results

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Inference

Front 149

These involve a careful assessment of study rigor through an analysis of validity threats and various biases that could undermine the accuracy of the results

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Credibility Assessments

Front 150

This is replication of results, through either internal or external sources, in a credibility assessment to determine study rigor

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Corroboration

Front 151

This is the examination across cases of one variable at a tim

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Univariate

Front 152

Two methods of estimating the dispersion of a distribution

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Range and Standard Deviation

Front 153

Inference and ___ are inextricably linked.

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Validity

Front 154

The three major analytical styles of qualitative research

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Template Analysis, Editing Analysis, Immersion/Crystallization

Front 155

A style of qualitative analysis where the researchers created a template to which the narrative data is applied

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Template Analysis Style

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A style of qualitative analysis where the researchers use an editing style act as interpreters who read through the data in search of meaningful segments and units and identifying category schemes and codes that can be used to organize the data

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Editing Analysis Style

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A style of qualitative analysis that involves the analyst's total immersion in (and reflection of) the text materials, resulting in an intuitive crystallization of the data; highly interpretive and subjective

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Immersion/Crystallization Style

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The most widely used procedure to organize data for a qualitative analysis

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Category Scheme

Front 159

Traditional, manual method for organizing and managing qualitative data before the advent of computer programs; involves creating a physical file for each category and then cutting out and inserting into the file all the materials for that category

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Conceptual Files

Front 160

Software used to organize and manage qualitative data, including examining the codes (but not doing the coding)

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CAQDAS (Computer Assisted Qualitative Data Analysis Software)

Front 161

The analysis of themes and patterns among the themes, primarily using a template or editing analysis style, in a qualitative study

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Content Analysis

Front 162

"An abstract entity that brings meaning and identity to a current experience and its variant manifestations. As such, it captures and unifies the nature or basis of the experience into a meaningful whole."

Often sought in qualitative research

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Themes

Front 163

A symbolic comparison, using figurative language to evoke a visual analogy

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Metaphor

Front 164

Used in qualitative studies to validate and refine themes by tabulating the frequency with which certain themes or insights are supported by the data

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Quasi-Statistics

Front 165

A common method of sequencing research for data analysis in an ethnographic study, based on the premise that language is the primary means that relate meaning in a culture

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Spradley's Research Sequence

Front 166

Units of cultural knowledge (Spradley) that are broad categories that encompass smaller categories

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Domains

Front 167

A system of classifying and organizing terms

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Taxonomy

Front 168

Three phenomenological methods of qualitative data analysis

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Colaizzi, Giorgi, Van Kaam

Front 169

An approach to analyzing ethnographic data using domain analysis, taxonomic analysis, componential analysis, and theme analysis

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Spradley

Front 170

A phenomenological approach that involves efforts to grasp the essential meaning of the experience being studied, using either a holistic approach (viewing the text as a whole), a selective approach (pulling out key statemetns and phrases), or a detailed approach (analyzing each sentence)

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Van Manen

Front 171

A methodological process in which there is continual movement between the parts and the whole of the text under analysis, used to analyze data in a hermeneutic study

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Hermeneutic Circle

Front 172

In hermeneutic analysis, a pattern that expresses the relationships among relational themes and is present in all the interviews or texts

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Constitutive Pattern

Front 173

In a hermeneutic analysis following the precepts of Benner, a strong exemplar of the phenomenon under study, often used early in the analysis to gain understanding of the phenomenon

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Paradigm Case

Front 174

A procedure used in a grounded theory analysis wherein newly collected data are compared in an ongoing fashion with data obtained earlier, to refine theoretically relevant categories

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Constant Comparison

Front 175

This is the first stage of coding in a grounded theory study, referring to the basic descriptive coding of the content of narrative materials; three levels are possible (level 1, 2, 3)

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Open Coding

Front 176

Three levels of open coding in grounded theory, each varying in degree of abstraction

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Level 1 (In Vivo), Level 2 (Condensed), Level 3 (Theoretical)

Front 177

In a grounded theory, the central phenomenon that is used to integrate all categories of the data

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Core Variable (Category)

Front 178

A level of coding in a grounded theory study that involves selecting the core category, systematically integrating relationships between the core category and other categories, and validating those relationships

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Selective Coding

Front 179

The central social process emerging through an analysis of grounded theory data; evolves over time into two or more phases

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Basic Social Process (BSP)

Front 180

A concept in grounded theory that involves comparing new data and new categories with previous existing conceptualizations

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Emergent Fit

Front 181

An alternative grounded theory method whose outcome is a full conceptual description; involves three types of coding -- open (categories are generated), axial (categories are linked with subcategories), and selective (findings are integrated and refined)

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Strauss and Corbin (Straussian) Method

Front 182

This is the degree of confidence qualitative researchers have in their data, assessed using criteria of credibility, transferability, dependability, confirmability, and authenticity

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Trustworthiness

Front 183

Lincoln and Guba's Framework

Back 183

Four criteria for developing the trustworthiness of a qualitative study: credibility, dependability, comfirmability, transferability -- later, authenticity was added

Front 184

Overriding goal of qualitative research, according to Lincoln and Guba; refers to confidence in the truth of the data and interpretations of them; part of Lincoln and Guba's Framework Credibility (Lincoln and Guba)

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Credibility (Lincoln and Guba)

Front 185

Part of Lincoln and Guba's Framework; refers to stability of data over time and over conditions

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Dependability (Lincoln and Guba)

Front 186

Part of Lincolin and Guba's Framework; refers to objectivity, that is, the potential for congruence between two or more independent people about the data's accuracy, relevance, or meaning in a qualitative study Confirmability (Lincoln and Guba)

Back 186

Confirmability (Lincoln and Guba)

Front 187

Analagous to generalizability, refers to the extent to which qualitative findings can be transferred to (or have applicability in) other settings or groups; part of Lincoln and Guba's Framework

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Transferability (Lincoln and Guba)

Front 188

Overarching goal of Whittemore and Colleague's Framework

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Validity

Front 189

The extent to which researchers fairly and faithfully show a range of different realities; part of Lincoln and Guba's Framework

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Authenticity (Lincoln and Guba)

Front 190

This is the investment of sufficient time collecting data to have an in-depth understanding of the culture, language, or views of the people or group under study, to test for misinformation and distortions, and to ensure saturation of important categories; also essential for developing trust with informants

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Prolonged Engagement

Front 191

Refers to the researchers' focus on the characteristics or aspects of a situation or conversation that are relevant to the phenomena being studied, providing depth to data collection in a qualitative, naturalistic study.

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Persistent Observation

Front 192

This involves using multiple data sources to validate conclusions in a qualitative study; three types are time, space, and person

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Data Triangulation

Front 193

A type of data triangulation involving collecting data on the same phenomenon at different points in time

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Time Triangulation

Front 194

A type of data triangulation involving collecting data on the same phenomenon in multiple sites, to test for cross-site consistency

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Space Triangulation

Front 195

A type of data triangulation involving collecting data on the same phenomenon from different types or levels of people

Back 195

Person Triangulation

Front 196

A type of data triangulation involving the use of multiple methods of data collection about the same phenomenon

Back 196

Method Triangulation

Front 197

A systematic collection of materials and documentation that would allow an independent auditor to come to conclusions about the data in a qualitative study

Back 197

Audit Trail

Front 198

A method for establishing credibility of qualitative data by providing feedback to study participants about emerging interpretations and obtaining participants' reactions

Back 198

Member Check

Front 199

A type of data triangulation where two or more researchers are used to make data collection, coding, and analytical decisions in a qualitative study to reduce bias and idiosyncratic interpretations

Back 199

Investigator Triangulation

Front 200

A strategy of investigator triangulation whereby a qualitative research team can be divided into two groups that deal with data sources separately and conduct independent inquiries through which data can be compared

Back 200

Stepwise Replication

Front 201

A type of data triangulation in qualitative research where researchers use competing theories or hypotheses in the analysis and interpretation of the data to test the validity and rule out rival hypotheses and prevent premature conceptualizations

Back 201

Theory Triangulation

Front 202

A process discussed by Lincoln and Guba by which researchers revise their interpretations by including cases that appear to disconfirm earlier hypotheses to continually refine a hypothesis or theory until it accounts for all cases

Back 202

Negative Case Analysis or Deviant Case Analysis

Front 203

A quality-enhancement strategy involving external validation whereby researchers enable sessions with peers to review and explore various aspects of the inquiry, exposing researchers to searching questions of others who are experienced in either methods, the phenomenon, or both.

Back 203

Peer Debriefing

Front 204

This refers to the process of "living" the data in a qualitative research study, a process in which researchers must try to understand their meanings, find their essential patterns, and draw well-grounded, insightful conclusions

Back 204

Incubation

Front 205

Researchers expectations about relationships among study variables. They are predictions about expected outcomes – they state relationship that is expected from research

Back 205

Theories

Front 206

A careful and objective appraisal of a study’s strengths and limitations. Usually includes review of study’s merits, recommendations regarding value of evidence, and suggestions on how study can be improved

Back 206

Research Critique

Front 207

Soundness of the evidence and the degree of inferential support the evidence yields

Back 207

Validity

Front 208

Who are considered vulnerable groups in research?

Back 208

Children, emotionally/mentally retarded, institutionalized (hospitals or prisons), pregnant women, severely ill, terminally ill or physically disabled

Front 209

Directional hypothesis (Definition and types)

Back 209

Predicts the direction of a relationship:
1. Simple: single dependent/independent variable
2. Complex: >= dependent/independent variables
3. Non-directional hypothesis: predicts existence of a relationship but not direction

Front 210

R O1 X O1

Back 210

Pretest-Posttest Design

Front 211

R X O1

Back 211

Posttest Only Design

Front 212

1. R O1 XA O2 XB O3
2. R O1 XB O2 XA O3

Back 212

Crossover Design

Front 213

A type of research theory that seeks to describe and understand key social, psychological or structural process that occurs in social settings

Back 213

Grounded Theory

Front 214

A type of research that, unlike most phenomenological research, focuses on interpreting the meaning of the experiences, rather than describing them

Back 214

Hermeneutics

Front 215

Basic units of a population from whom data is collected. Usually humans.

Back 215

Elements

Front 216

Organize in order of size, from largest to smallest:

Population, sample, target population, accessible population

Back 216

1. Population
2. Target Population
3. Accessible Population
4. Sample

Front 217

A type of sampling that involves recruiting all the people from an accessible population who meet eligibility criteria over a specific time interval or for a specified sample size. (ex: if 100 participants is the target sample size, sample the first 100 eligible participants). Reduces bias.

Back 217

Consecutive Sampling

Front 218

True or false - generalizability is equally important in quantitative and qualitative research

Back 218

False, it is not as important in qualitative research since the purpose is to uncover meanings

Front 219

A p-value is evidence against the ___

Back 219

Null hypothesis

Front 220

If the p-value is less than the commonly used level of 0.05, ____

Back 220

The null hypothesis is rejected

Front 221

Falsely rejecting a null hypothesis is called a __

Back 221

Type 1 error

Front 222

Falsely accepting a null hypothesis is called __

Back 222

Type 2 error

Front 223

Goal of Glaser and Strauss (Glaserian)

Back 223

Get into patterns (Qualitative)

Front 224

Goal of Strauss and Corbin (Straussian)

Back 224

Problem emerges from data (Qualitative)

Front 225

This is the truthfulness of an instrument; does the test measure what its suppose to measure?

Back 225

Validity

Front 226

The larger the sample size, the (less/more) representative

Back 226

More

Front 227

This is when the researchers start to notice trends and patterns at end of data collecting in a qualitative study

Back 227

Emergent issues

Front 228

This type of phenomenological study involves the validation of results by having participants “COME BACK” (return)

Back 228

Colaizzi

Front 229

This type of phenomenological study considers it inappropriate to return to participants after study is complete (“GO AWAY)

Back 229

Giorgi

Front 230

True or false - researchers attempt to prove their hypotheses.

Back 230

False - they attempt to support their hypotheses with evidence (they cannot prove it)

Front 231

Researchers want to see at least a __ % confidence interval

Back 231

95

Front 232

With a negative skewed distribution, the mean is __ than the median

Back 232

Higher

Front 233

With a positive skewed distribution, the mean is __ than the median

Back 233

Lower

Front 234

One often "rejects the null hypothesis" when the p-value is __ than the significance level α (Greek alpha), which is often __

Back 234

Less; 0.05 (conventional level)