Primary Source
Original report of a study, contains all details for replication, peer-reviewed
Secondary Source
Summarized information about a study, some peer review, not original
General Source
Provides overview, not peer-reviewed, broad information
Directional Hypothesis
Clarifies nature of differences in relationship
Non-Directional Hypothesis
Reflects differences without specifying nature
Theory
Explanation combining assumptions, hypotheses, facts to explain findings
General Theory
Broad explanations applicable to various concerns
Middle Range Theory
Explanations specific to a subject area
Assumptions
Accepted beliefs without testing
Concepts
Key ideas in a theory
Hypotheses
Propositions suggesting relationships in a model
Theoretical Model
Diagram identifying key ideas and their relationships
Conceptual Definition
General definition in research introduction
Operationalization
Defining and measuring a concept for research
Reliability
Consistency of measurement
Test-Retest Reliability
Consistency of scores when a measure is given more than once
Inter-Item Reliability
Consistency between individual items in a measure
Inter-Rater Reliability
Consistency between multiple raters
Alternate Parallel Form Reliability
Consistency between multiple forms of the same measure
Validity
Accuracy of measurement
Construct Validity
Assessment of how well an instrument measures a theoretical construct
Operationalize
Defining and measuring something not directly measurable
Sampling
Process of selecting a subset of individuals from a population
Probability Sample
Sample selected with known probability of inclusion
Non-Probability Sample
Sample selected without known probability of inclusion
Levels of Measurement
Categorization of variables based on their properties
Nominal Level
Categorical with mutually exclusive categories
Ordinal Level
Ranking along a continuum with unknown distances
Interval Level
Numerical with equal intervals, arbitrary zero
Ratio Level
Numerical with equal intervals, absolute zero
Deduction
Reasoning from general theory to specific data
Induction
Reasoning from specific data to a general theory
Dependent Variable
Response variable being measured
Independent Variable
Explanatory variable
Control Variable
Variables held constant to account for influences in research
Confounding
Unaccounted variable influencing research outcomes
Triangulation of Sources
Using diverse sources to build knowledge
Triangulation of Methods
Utilizing mixed research methods
Qualitative Interviewing Stages
Procedures for data collection in qualitative research
Trustworthiness
Rigor in design, researcher credibility, and findings believability
Credibility
Believability of analyses
Transferability
Ability to apply findings to other contexts
Dependability
Consistency and repeatability of analyses
Qualitative Coding
Process of categorizing qualitative data
Open Coding
Locating and naming themes in data
Axial Coding
Focusing explicitly on themes and adjusting
Selective Coding
Identifying cases exemplifying themes
Triangulation in Validity
Using multiple techniques for accurate findings
Prolonged Engagement
Increased time in the field for deeper understanding
Thick Description
Detailed and embedded field study description
Negative Case Analysis
Explaining cases that don't fit the hypothesis
Audit Trail
Detailed documentation of data analysis process
Conceptual Saturation
Collecting data until no new categories emerge
Member Check
Sharing data and interpretations with participants
Peer Debriefing
Presenting analyses to ensure unbiased interpretations
Explicit Documentation
Detailed record of data collection and analysis decisions
Research Ethics
Principles guiding ethical research conduct
Tuskegee
Infamous Syphilis Project influencing research ethics
Belmont Report
Statement of ethical principles for human subject protection
Research Designs
Structures for conducting research studies
Experimental Design
Controlled study with treatment and control groups
Quasi-Experimental Design
Study with treatment and control groups, non-randomized
Correlational Design
Examining relationships between variables
Descriptive Statistics
Summarizing patterns among variables
Inferential Statistics
Drawing conclusions about populations from sample data
Measures of Center
Statistics describing central tendencies
Test Statistic
Used to determine significance in hypothesis testing
Regression Models
Estimating relationships between variables
P-Value
Significance level in hypothesis testing