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Appendix E: Research Methods Glossary

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    122956
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    This glossary provides definitions for the research methods jargon found in this summary and for some other terms you might encounter as you learn more about research methods.

    Accuracy, level of (in sampling): The breadth of the interval in which parameters can be estimated using statistics with a given level of confidence

    Administrative data: Data collected in the course of implementing a policy or program or operating an organization

    Alternative hypothesis: See hypothesis testing

    Analytic generalizability: The extent to which a theory applies (“generalizes”) to a given case; demonstrating analytic generalizability is held by some researchers as a goal for qualitative research

    Antecedent variable: An independent variable that causes changes in the key independent variable, which, in turn, causes change in the dependent variable

    Association: A probabilistic relationship between two or more variables

    Axial coding: Organizing the themes that emerge from open coding, frequently by combining them into general themes subdivided into more specific themes and identifying additional relationships among codes, resulting in an organized set of codes that can be used in subsequent analysis of qualitative data

    Bias: The systematic distortion of findings due to a shortcoming of the research design

    Case study comparison research design: Research design in which multiple case studies are conducted and compared

    Case study research design: Systematic study of a complex case (such as an event, a program, a policy) that is in-depth, holistic, using multiple data sources/methods/collection techniques

    Case: An object of systematic observations; an entity to which we assign values for variables

    Census: (1) A sample comprised of the entire population; (2) a study in which the sample is comprised of the entire population

    Chunking: Identifying short segments of meaningful qualitative data to be coded and analyzed

    Closed-ended question: A survey or interview question that requires respondents to select from a set of predetermined responses

    Cluster sampling: A probability sampling design in which successively narrower aggregates of cases are selected before ultimately selecting cases for inclusion in the sample

    Coding: See axial coding, open coding, selective coding

    Concept: An abstraction derived from what many instances of it have in common

    Concurrent validity: A type of criterion validity describing the extent to which a variable (or set of variables intended to operationalize a single concept) relates to another variable measured at the same time as would be expected if the variable accurately measures what it is intended to measure

    Confidence, level of (in sampling): The certainty, expressed as a percentage, with which parameters can be estimated using statistics with a given level of accuracy; the percentage of times an estimated parameter would be expected to be within a given range (the level of accuracy) if calculated using data collected from a large number of hypothetical samples

    Confidence interval: The range of values we estimate a population parameter to fall in at a given level of confidence

    Content validity: An aspect of operational validity describing the extent to which the operationalization of an abstract concept measures the full breadth of meaning connoted by the concept

    Control variable: A variable that might threaten nonspuriousness when examining the causal relationship between an independent variable and dependent variable; control variables are plausibly related to both the independent and dependent variables and could thus explain an observed association between them; in an experiment or quasi-experiment, control variables are those variables held constant so that they cannot affect the dependent variable while the independent variable is manipulated

    Convenience sampling: A nonprobability sampling design in which cases are selected because they are convenient for the researcher

    Conversational interviews: Interview conducted following a very flexible protocol outlining general themes but permitting the interview to evolve like a natural conversation between the researcher and respondent

    Criterion validity: An aspect of operational validity describing the extent to which a variable (or set of variables intended to operationalize a single concept) is associated with another variable as would be expected if the variable accurately measures what it is intended to measure

    Cross sectional research design: A formal research design in which data are collected in one “wave” of data collection, with data analysis making no distinction among data collected at different times

    Data analysis: Systematically finding patterns in data

    Dependent variable: A variable with values that are dependent on the values of another variable; in a cause-and-effect relationship, the variable representing the effect

    Descriptive data analysis: Quantitative data analysis that summarizes characteristics of the sample

    Discriminate validity: An aspect of operational validity describing the extent to which the operationalization of an abstract concept discriminates between the target concept and other concepts

    Disproportionate stratified sampling: A probability sampling design in which the proportions of cases in the population demonstrating known characteristics are intentionally and strategically different for the cases in the sample, usually to permit comparisons among subsets of the sample that may otherwise have had too few cases

    Dissemination: To share the results of a study and how it was conducted widely, usually by publication

    Double-barreled question: A question, such as in an interview or survey, that is actually asking two questions at once

    Effect size: A quantitative measure of the magnitude of a statistical relationship

    Empirical research: Generating knowledge based on systematic observations

    Empirical: Based on systematic observation

    Empiricism: The stance that the only things that are “real” and therefore matter are those things that can be directly observed; not to be confused with empirical

    Experimental research design: A formal research design in which cases are randomly assigned to at least one experimental group and one control group with the researcher determining the values of the independent variables that will be assigned to each group and the dependent variable measured after (and usually before as well) manipulation of the independent variable

    External validity: The generalizability of claims generated by empirical research beyond cases directly observed

    Face validity: An aspect of operational validity describing the extent to which a variable (or set of variables intended to operationalize a single concept) appears to measure what it is intended to measure

    Fact-value dichotomy: The naïve view that fact and value are always wholly distinct categories

    Focus group: A group of individuals who share something in common of relevance to the research project who are interviewed together and encouraged to interact to allow themes to emerge from the group discourse

    Generalize: To make claims beyond what can be claimed based on direct observation, such as making claims about an entire population based on observations of a sample of the population

    Hawthorne effect: Bias resulting from changes in research participants’ behavior effected by their awareness of being observed

    Hypothesis: A statement describing the expected relationship between two or more variables 

    Hypothesis testing: A method used in inferential statistics wherein the statistical relationships observed in sample data are compared to a hypothetical distribution of data in which there is no analogous relationship to generate an estimate of how likely or unlikely the observed relationship is; the observed relationship being tested is stated as the alternative hypothesis, which is compared to the statement of no relationship, the null hypothesis

    Independent variable: A variable with values that, at least in part, determine values of another variable; in a cause-and-effect relationship, the variable representing the cause

    Inferential data analysis: Quantitative data analysis that uses statistics to estimate parameters

    Informed consent: An individual’s formal agreement to participate in a study after receiving information about the study’s risks and benefits, assurances that participation is voluntary, what participation will entail, confidentiality safeguards, and whom to contact if they have questions or concerns about the study

    Institutional Review Board: A committee responsible for ensuring compliance with ethical standards for conducting research at an institution, such as a university

    Internal validity: The truth of causal claims inferred from empirical research
    Interval scale of measurement: Describes a variable with numeric values but no natural zero

    Intervening variable: An independent variable that itself is affected by the key independent variable and then, in turn, causes change in the dependent variable

    Interview protocol: The set of instructions and questions used to guide interviews

    Latent variable: A variable that cannot be directly observed, such as an abstract concept, attitude, or private behavior

    Literature review: (1) The process of finding and learning from previous research as one of the early steps in the research process; (2) a paper that summarizes, structures, and evaluates the existing body of knowledge addressing a research question; (3) a section of a larger research report that summarizes, structures, and evaluates the existing body of knowledge being addressed by the research and locates the research being reported in that larger body of knowledge

    Logic model: A diagram depicting a program’s inputs, activities, outputs, and outcomes

    Manifest variable: A variable that can be observed and is thought to indicate the values of latent variable

    Memoing: Writing notes to document the qualitative researchers’ thought processes associated with every step of qualitative research and their evolving ideas about what is being learned during the course of data analysis

    Meta-analysis: A method of synthesizing previous research using statistical techniques that combine the results from multiple separate studies; the results of research using this method

    Mixed methods research: Research using both qualitative and quantitative data

    Natural experiment: A quasi-experimental design that capitalizes on “naturally” occurring variation in the independent variable

    Nominal scale of measurement: Describes a variable with categorical values that have no inherent order

    Nonparametric data analysis: Analysis of quantitative data using statistical techniques suitable because the data do not have an underlying normal distribution, homogeneous variance, and independent error terms

    Nonprobability sampling design: A strategy for selecting a sample in which the probability of cases being selected is either unknown or not considered when selecting cases for inclusion in the sample, with sample selection made for some other reason (see convenience sampling, purposive sampling, quota sampling, and snowball sampling)

    Nonspurious: Not attributable to any other factor

    Null hypothesis: See hypothesis testing

    Open coding: Assigning labels/descriptors/tags to “chunks” of qualitative data that note the data’s significance for addressing the research question; a first step in identifying important themes that emerge from qualitative data

    Open-ended question: A survey or interview question without any predetermined responses

    Operational validity: The extent to which a variable (or set of variables intended to operationalize a single concept) accurately and thoroughly measures what it is intended to measure

    Operationalize: To describe how observations will be made so that values can be assigned to variables for cases

    Ordinal scale of measurement: Describes a variable with categorical values that have an inherent order

    Panel research design: A formal research design in which data are collected at different points across time from the same sample

    Parameter: A quantified summary characteristic of a population

    Parametric data analysis: Analysis of quantitative data using statistical techniques suitable only because the data have an underlying normal distribution, homogeneous variance, and independent error terms

    Peer review: The process of having a research report (or other form of scholarship) reviewed by scholars in the field, usually as a prerequisite for publication

    Plagiarism: The written misrepresentation of someone else’s words or ideas as one’s own 

    Point estimate: A statistic calculated from sample data used to estimate the population parameter; usually referred to in distinction to the confidence interval

    Policy model: An explanation of how a policy is supposed to work, including its inputs, how it is intended to be implemented, its intended outcomes, and the assumptions that undergird the intended change process

    Population: Total set of cases of interest; all cases to which the research is intended to apply

    Predictive validity: A type of criterion validity describing the extent to which a variable (or set of variables intended to operationalize a single concept) predicts future change in another variable as would be expected if the variable accurately measures what it is intended to measure

    Probability sampling design: A strategy for selecting a sample in which every case in the population has a known (or knowable) nonzero probability of being included in the sample

    Proportionate stratified sampling: A probability sampling design in which the proportions of cases in the population demonstrating known characteristics are replicated in the sample

    Purposive sampling: A nonprobability sampling design in which cases are selected because they are of interest, typical, or atypical as suits the purposes of the research

    Qualitative data: Textual data

    Quantitative data: Numeric data

    Quasi-experimental research design: A formal research design similar to experimental research design but with assignment to experimental and comparison groups made in a nonrandom fashion

    Quota sampling: A nonprobability sampling design in which cases are selected as in convenience sampling but such that the sample demonstrates desired proportions of characteristics, either to replicate known population characteristics or permit comparisons of subsets of the sample

    Ratio scale of measurement: Describes a variable with numeric values and a natural zero

    Reliability: The extent to which hypothetical repeated measures of variables would generate the same values for the same cases

    Research design: 1) Generally, a description of the entire research process; 2) more narrowly, the formal research design used to structure the research, including cross-sectional, time series, panel, experimental, quasi-experimental, and case study research designs

    Response set bias: Bias resulting from a response set that leads respondents to select responses other than more accurate responses

    Response set: The set of responses that respondents may select from when answering a closed-ended question

    Sample: Subset of population used to learn about the population; the cases which are observed

    Sampling error: The difference between a statistic and its corresponding parameter

    Sampling frame: List of cases from which a sample is selected

    Secondary data: Data collected by someone other than the researcher, usually without having anticipated how the data would ultimately be used by the researcher

    Selective coding: Assigning a set of codes (such as a system of codes developed through axial coding) to “chunks” of qualitative data

    Semi-structured interviews: Interviews conducted following an interview protocol that specifies questions and potential follow-up questions but permitting flexibility in the order and specific wording of questions

    Simple random sampling: A probability sampling design in which every case in the population has an equal probability of being selected for inclusion in the sample

    Snowball sampling: A nonprobability sampling design in which one case is selected for the sample, which then leads the researcher to another case for inclusion in the sample, then another case, and so on (also called network sampling when cases are people)

    Social desirability bias: The tendency of interviewees to provide responses they think are more socially acceptable than accurate responses

    Standardized interview: Interviews conducted following an interview protocol requiring identical wording and question order for all respondents

    Statistic: A quantified summary characteristic of a sample

    Systematic sampling: A probability sampling design in which every kth case in the sampling frame is selected for inclusion in the sample where k equals the number of cases in the population divided by the number of cases desired to be in the sample

    Theory: A set of concepts and relationships among those concepts posited in a formal statement to describe or explain the phenomenon of interest

    Time series research design: A formal research design in which data are collected at different points across time from independent samples

    Unit of analysis: The entity—the whom or what—that is being studied; the entity for which observations are being recorded in a study

    Validity: Truthfulness of claims made based on research; see operational validity, face validity, content validity, discriminate validity, criterion validity, concurrent validity, predictive validity, internal validity, external validity

    Variable: Logical groupings of attributes; the category to which these attributes belong; a factor/quality/condition that can take on more than one value/state

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