What is a Case Study? John Gerring Purpose of this paper -Ambiguous definition of what this research method is -To provide a narrower and more useful concept for the purposes of methodological discussion -Help to define the conditions under which this method would be the most useful

Definitions Unit Case Case Study Method A spatially bounded phenomenon observed at a single point in time or over some time period Case Comprised of several variables, each built upon an observation Case Study Method An intensive study of a single unit with an aim to generalize across a larger set of units Case Study vs. Cross-Unit Study Method Case study – an intensive study of a single unit with an aim to generalize across a larger set of units (differentiate from cross-unit study in its way of defining cases) Case study - Constructs cases from a single unit while remaining attentive to inferences that span similar units outside the formal scope of investigation Cross-Unit study method - construct cases across units exemplifying the principle causal inference

Cross-country Time-series Regression Analysis Unit – countries Case – country-year Observations are collected for each case on a range of variables

Preferred conditions Case studies are generally more useful when: Inferences are descriptive rather than causal Propositional depth over breadth & boundedness (Internal) case comparability is given precedence over (external) case representativeness Insight into causal mechanisms is more important than insight into causal effects The strategy of research is exploratory, rather than confirmatory Useful variance is available for only a single unit/smaller number of units Descriptive -Form descriptive inferences -Implicitly comparative -Asserts that the unit under study (A) is like/unlike other similar units (B & C) -More complicated might assert a classificatory relationship, such that A falls into a certain typological relationship with B and C Depth -Because focus of a case study research so tight, often produce inferences with poorly-defined boundaries Comparability -Single-unit studies provide cases that are likely to be comparable to one another -But they fall short in their representativeness (the degree to which causal relationships evidenced by that single unit may be assumed to be true for a larger set of units) -Trade-off between comparability and representativeness Causal mechanisms -Single-unit analysis is better at identifying causal mechanisms (when put tgt general knowledge of the world with empirical knowledge of how X and Y interrelate) -Becos its characteristic style of evidence-gathering (over-time and within-unit variation) is likely to provide clues into what connects a purported X to Y -Through things like process tracing (which will be explained more in detail later)

Cases, Numbers, Models: International Relations Research Methods A Review of Chapters 2-5

Comparative Advantages Stronger construct validity Ability to measure the indicators that best represent the theoretical concept we intend to measure Better at generating new theories Making inferences regarding causal mechanisms Unobservable structures that operate in specific contexts to generate the phenomena that we observe in the physical or social world Historical explanation of cases Addressing complex causal relations Construct validity -Versus external validity (ability to apply findings across a wide population of cases) Generating new theories -Data mining for statistical methods may be limited in identifying new methods (only look at potentially relevant variables that have already been identified) Causal mechanisms -High level of detail and continuity in explaining an individual historical case  unlike the ‘manipulation account’ of causal inference -E.g. Statistical analysis of non-experimental data in humans that smoking cigarettes increase the likelihood of contracting lung cancer Historical explanations -Statistically significant correlation is NOT sufficient -Closer to the writing of history than other political science methods (theoretical assumptions and elegant theories)

Possible Pitfalls Be wary of case selection biases Confirmation bias: ignoring cases that contradict the hypothesis Increased potential for indeterminacy Indeterminacy: inability to exclude all but one explanation of a case on the basis of the available process tracing evidence from that case Potential lack of independence of cases Confirmation bias -Cases selected on the dependent variable can test whether a variable is necessary for the selected outcome -Confirmation bias – selecting only those cases whose independent and dependent variables vary as the favored hypothesis suggest and ignoring cases that appear to contradict the theory -Selecting cases based on extreme values of the variable OR on the availability of evidence OR on cases’ ‘intrinsic’ historical importance Indeterminacy -One version is the ‘degrees of freedom’ problem, where there are more independent variables than cases, so that it becomes impossible to find coefficient estimates for the variables -When researcher has many independent variables but only one or a few observations on the dependent variable Lack of independence of cases -’Galton’s problem’ – danger that reseracher will fail to identify a lack of independence between cases -But depends on the objectives of the research study and process tracing will usually pick it out

Within-Case Methods of Analysis Process Tracing Historical explanation Calls for full continuity and completeness Congruence Testing Tests whether the predicted value of the dependent variable is congruent with the actual outcome in the case Counterfactual Analysis Inverts the standard mode of inference in which we try to test empirically assertions Process tracing Focuses on whether the intervening variables between a hypothesized cause and observed effect move as predicted by the theories under investigation  Detective at crime scene Requires full continuity/completeness Inductive or deductive or both Possible to develop a hypothesis from a case then test it against different evidence in the same case Possible pitfalls – measurement error, omitted variables Congruence testing Tests whether the predicted value of the dependent variable, in view of the values of the case’s independent variables, is congruent with the actual outcome in the case Less conclusive cos lack precise models of the value that the individual variables, individually & collectively, should produce in the dependent variable Able to rule out proposed necessary/sufficient conditions Counterfactual analysis Inverts the standard mode of inference in which we try to test empirically assertions Limitations – danger of confirmation bias and spuriousness Must reconcile the asymmetry  provides a check on confirmation bias rather than an open license to rewrite history

Chap 3: International Political Economy Single case designs Least-likely case study Foreign Policy and Interdependence in Gaullist France, Edward Morse Most-likely case study Dependency Theory Method of Difference Most-similar and Least-similar case comparisons Structured, focused comparison Single Case Designs iv. The least-likely (theory confirming) case study When the researcher selects an extreme case that is highly unlikely to confirm it, and finds that even this case does so E.g. Edward Morse’s thesis in Foreign Policy and Interdependence in Gaullist France – increasing modernization and interdependence transform foreign policy, making it less nationalistic and more cooperative  France (Charles de Gaulle’s nationalism) v. The most-likely (theory infirming) case study If the theory failed even in a most-likely case, this evidence would provide strong support for the expectation that it will fail even more clearly in less hospitable circumstances E.g. Dependency theory – dependency of a less developed country on the world capitalist system retards its development  evidence that Cuba did not experience improvement Method of Difference A) Mill’s Methods and Most-Similar and Least-Similar Case Comparisons -Least-similar cases – E.g. teenagers are difficult in both tribal and industrialized societies -Most-similar case/Method of ‘controlled comparison’ – functional equivalent of a controlled experiment Does not work well in the presence of equitinality (when the same outcome can arise through different pathways/combinations of variables) Work well when the causal relations being investigated must be deterministic regularities involving conditions that by themselves are either necessary or sufficient for a specified outcome (1) all variables that contributed causally to the outcome would hae to be identified (2) cases that represent the full range of all logically and socially possible causal paths must be available for study (3) B) Structured, focused comparison of cases and the development of typological theories Method: 1) specifies the research problem and the class of events to be studied 2) defines the independent, dependent and intervening variables of the relevant theories 3) selects the cases to be studied and compared 4) decides how best to characterize variance in the independent and dependent variables 5) formulates a detailed set of standard questions to be applied to each case

Chap 4: Qualitative Research Design in International Environmental Policy Challenges in IEP Lack of consensus on what constitutes policy effectiveness Research steps Selecting cases and observations Linking data to propositions Generalizing to other cases -Picked steps of the research process that made a particularly pertinent point c) Selecting cases and observations -Theoretically ‘hot’ questions cannot be answered using politically ‘hot’ cases  because these cases have not yet produced data that could be used in service of this question -Selecting observations that show other potentially explanatory variables did not vary  compare observations rather than cases d) Linking data to propositions -Variables must be operationalized to correspond well to the relevant theoretical constructs -Proxies – correspond reasonably well + readily observed (e.g. ‘environmental vulnerability’  ozone depletion  skin cancer rates + CFC consumption) f) Generalizing to Other cases Most QER studies document the association between an IV and a DV for only a single value of any given CV (which is likely to be different in many cases to which the researcher might want to generalize) E.g. study of how NGO activism influences the chances of regime formation  QER develop clearer sense of exactly how the NGOs fostered regime formation but cannot claim that ‘NGOs play a major role in regime formation’ Increase external validity by: adding cases & observations in which CVs have different values (1) select hard cases (2) select cases & observations that take advantage of the types of variation examined in past studies

Chap 5: International Security Studies Methodological challenges Endogeneity: where the values our explanatory variables take on are sometimes a consequence, rather than a cause, of our dependent variable Concepts of democracy and peace Produces contradictory & inconclusive results The Democratic Peace: Layne v. Owen Focus on the challenges that discovered in the field of International Security Studies, which are hopefully illustrative of the methodological challenges highlighted earlier 1. Methodological challenges in the use of case studies Case selection bias & endogeneity Endogeneity – where the values our explanatory variables take on are sometimes a consequence, rather than a cause, of our dependent variable Direction of causality difficult to ascertain – E.g. democracy and peace 2. The utility of case studies for studying international security Single case studies ‘Essence of Decision: Explaining the Cuban Missile Crisis’ Structured-focused comparisons 3. Limits of the case study method The Democratic Peace Focus shifted from whether such correlation exist to why it exists Case study method, which examined the decision-making processes in historical studies) helped explain why such a peace might exist and why democracy mattered Criticize that it explains only patterns and trends of inter-state behavior, not individual foreign policy choices Produce contradictory results Layne – ‘near misses’ was due to balance of power, not democratic peace Owen – ideas embedded in liberal democracies provide the causal mechanisms that prevent democracies from going to war against one another

Research Design: Qualitative, Quantitative, and Mixed Methods Approaches A Review of Chapters 5 – 10

Author Info and Target Audience John W. Creswell Over 30 years as Professor of Educational Psychology, University of Nebraska – Lincoln Author of 11 books and founding co-editor of Journal of Mixed-Methods Research Target Audience: “This book is intended for graduate students and faculty who seek assistance in preparing a plan or proposal for a scholarly journal article, dissertation, or thesis.”

Chapter 5: The Introduction Differences among quantitative, qualitative, and mixed methods introductions The deficiency model for writing an introduction How to design a good narrative hook How to identify and write a research problem How to summarize literature about a research problem Distinguishing among different types of deficiencies in past literature Considering groups that may profit from your study

Differences among quantitative, qualitative, and mixed methods introductions In a qualitative project, the author will describe a research problem that can best be understood by exploring a concept or phenomenon. In a quantitative project, the problem is best addressed by understanding what factors or variables influence an outcome. The mixed methods approach can employ either the qualitative or the quantitative approach, or some combination.

The deficiency model for writing an introduction The deficiencies model of an introduction is a general template for writing a good introduction. It consists of five parts: The research problem Studies that have addressed the problem Deficiencies in the studies The significance of the study for a particular audience The purpose statement A separate paragraph can be devoted to each part, for a total of about two pages.

How to design a good narrative hook The first sentence of a study serves to pique interest and convey a distinct research problem or issue. One way to get a reader’s attention is to use a narrative hook, words that serve to draw, engage, or hook the reader into a study. Writers can ask themselves: What effect did this sentence have? Would it entice a reader to read on? Was it pitched at a level so that a wide audience could understand it?

How to identify and write a research problem Write an opening sentence that will stimulate interest Avoid direct quotations (open to misinterpretation) and idiomatic or trite expressions Consider numeric information for impact Clearly identify the research problem leading to the study Indicate why the problem is important Frame the problem in a manner consistent with the approach Identify if it’s a single problem, or multiple problems

How to summarize literature about a research problem Refer to literature by summarizing groups of studies, with the intent to establish broad areas of research. To deemphasize single studies, place the in-text references at the end of a paragraph or at the end of a summary point about several studies. Review research studies that use qualitative, quantitative, and mixed methods approaches. Find recent literature to summarize. Cite older studies If they are valuable because they have been widely referenced by others.

Distinguishing among different types of deficiencies in past literature Cite several deficiencies to make the case even stronger for a study. Identify specifically the deficiencies of other studies (e.g., methodological flaws, variables overlooked) Write about areas overlooked by past studies, including topics, special statistical treatments, significant implications, etc. Discuss how a proposed study will remedy these deficiencies and provide a unique contribution to the scholarly literature.

Considering groups that may profit from your study Three to four reasons that the study adds to the scholarly research and literature in the field. Three to four reasons about how the study helps improve practice. Three to four reasons as to why the study will improve policy.

Chapter 6: The Purpose Statement A script for writing a qualitative purpose statement Considering how the script would change depending on your qualitative strategy of inquiry A script for writing a quantitative purpose statement Considering how the script would change depending on your quantitative strategy of inquiry A script for writing a mixed methods purpose statement Considering how the script would change depending on your mixed methods strategy of inquiry

A script for writing a qualitative purpose statement The purpose of this _____ (strategy of inquiry, such as ethnography, case study, or other type) study is (was? will be?) to _____ (understand? describe? develop? discover?) the ______ (central phenomenon being studied) for _____ (the participants, such as the individual, groups, organization) at _____ (research site). At this stage in the research, the _____ (central phenomenon being studied) will be generally defined as _____ (provide a general definition).

…in a qualitative phenomenology study …in a case study Considering how the script would change depending on your qualitative strategy of inquiry …in a qualitative phenomenology study …in a case study …in an ethnography …in a grounded theory study

A script for writing a quantitative purpose statement The purpose of this _____ (experiment? survey?) study is (was? will be?) to test the theory of _____ that _____ (compares? relates?) the _____ (independent variable), controlling for _____ (control variable) for _____ (participants) at _____ (the research site). The independent variable(s) _____ will be defined as _____ (provide a definition), and the control and intervening variable(s), _____, (identify the control and intervening variables) will be defined as _____ (provide a definition).

…in a published survey study …in a dissertation survey study Considering how the script would change depending on your quantitative strategy of inquiry …in a published survey study …in a dissertation survey study …in an experimental study

A script for writing a mixed methods purpose statement The intent of this concurrent mixed methods study is to _____ (content objective of the study). In the study, _____ (quantitative instrument) will be used to measure the relationship between _____ (independent variable) and _____ (dependent variable). At the same time, the _____ (central phenomenon) will be explored using _____ (qualitative interviews or observations) with _____ (participants) at _____ (research site). The reason for combining both quantitative and qualitative data is to better understand this research problem by converging both quantitative (broad numeric trends) with qualitative (detailed views) data.

…in a concurrent mixed methods purpose statement Considering how the script would change depending on your mixed methods strategy of inquiry …in a concurrent mixed methods purpose statement …in a sequential mixed methods purpose statement …in a transformative concurrent mixed methods purpose statement

Chapter 7: Research Questions and Hypotheses A script for writing a qualitative central question Considering how this script would change depending on the qualitative strategy of inquiry A script for writing quantitative research questions and hypotheses Considering how this script would change depending on the quantitative strategy of inquiry and the different types of hypotheses A model for presenting descriptive and inferential quantitative questions and hypotheses Scripts for writing different forms of research questions into a mixed methods study

A script for writing a qualitative central question (1/2) Ask one or two central questions followed by no more than five to seven subquestions. Relate the central question to the specific qualitative strategy of inquiry. Begin the research questions with the words what or how to convey an open and emerging design. Focus on a single phenomenon or concept. Use exploratory verbs that convey the language of emerging design. Use open-ended questions.

A script for writing a qualitative central question (2/2) _____ (How or What) is the _____ (“story for” the narrative research; “meaning of” the phenomenon for phenomenology; “theory that explains the process of” for grounded theory; “culture-sharing pattern” for ethnography; “issue” in the “case” for case study) of _____ (central phenomenon) for _____ (participants) at _____ (research site).

Considering how this script would change depending on the qualitative strategy of inquiry …in an ethnography …in a case study

A script for writing quantitative research questions and hypotheses (1/2) The use of variables in research questions or hypotheses is typically limited to three basic approaches: Compare, Relate, or Describe. The most rigorous form of quantitative research follows from a test of a theory. The independent and dependent variables must be measured separately. To eliminate redundancy, write only the research question or hypotheses, not both, unless the hypotheses build on the research question.

A script for writing quantitative research questions and hypotheses (2/2) Does _____ (name the theory) explain the relationship between _____ (independent variable) and _____ (dependent variable), controlling for the effects of _____ (control variable)? The null hypothesis might be: There is no significant difference between _____ (the control and experimental groups on the independent variable) on _____ (dependent variable).

Directional hypothesis Nondirectional hypothesis Considering how this script would change depending on the quantitative strategy of inquiry and the different types of hypotheses Null hypothesis Directional hypothesis Nondirectional hypothesis

Descriptive questions and hypotheses seek to describe something. A model for presenting descriptive and inferential quantitative questions and hypotheses Descriptive questions and hypotheses seek to describe something. Inferential questions and hypotheses seek to draw inferences from a sample to a population.

Scripts for writing different forms of research questions into a mixed methods study Write separate quantitative questions or hypotheses and qualitative questions. Write separate quantitative questions or hypotheses and qualitative questions and follow them with a mixed methods question. Write only a mixed methods question that reflects the procedures or the content (or write the mixed methods question in both a procedural and a content approach), and do not include separate quantitative and qualitative questions.

Chapter 8: Quantitative Methods A checklist for survey research to form topic selection of a survey procedure Steps in analyzing data for a survey procedure A complete survey methods discussion A checklist for experimental research to form sections for an experimental procedure Identifying the type of experimental procedure that best fits your proposed study Drawing a diagram of experimental procedures Identifying the potential internal validity and external validity threats to your proposed study

A checklist for survey research to form topic selection of a survey procedure Is the purpose of a survey design stated? Are the reasons for choosing the design mentioned? Is the nature of the survey (cross-sectional vs. longitudinal) identified? Are the population and its size mentioned? Will the population be stratified? If so, how? How many people will be in the sample? On what basis was this size chosen? What will be the procedure for sampling these individuals (e.g., random, nonrandom)? What instrument will be used in the survey? Who developed the instrument? What are the content areas addressed in the survey? The scales? What procedure will be used to pilot or field test the survey? What is the timeline for administering the survey? What are the variables in the study? How do these variables cross-reference with the research questions and items on the survey? What specific steps will be taken in data analysis to: Analyze returns? Check for response bias? Conduct a descriptive analysis? Collapse items into scales? Check for reliability of scales? Run inferential statistics to answer the research questions? How will the results be interpreted?

Steps in analyzing data for a survey procedure Report information about the number of members of the sample who did and did not return the survey. Discus the method by which response bias will be determined. Discuss a plan to provide a descriptive analysis of the data for all independent and dependent variables in the study. Identify the statistical procedure for the use of scales. Identify the statistics and software used in the study. Present the results in tables or figures, and interpret the results from the statistical test.

A complete survey methods discussion The survey design The population and sample Instrumentation Variables in the study Data analysis and interpretation

A checklist for experimental research to form sections for an experimental procedure Who are the participants in the study? What is the population to which the results of the participants will be generalized? How were the participants selected? Was a random selection method used? How will the participants be randomly assigned? Will they be matched? How? How many participants will be in the experimental and control group(s)? What is the dependent variable or variables (i.e., outcome variable) in the study? How will it be measured? Will it be measured before and after the experiment? What is the treatment condition(s)? How was it operationalized? Will variables be covaried in the experiment? How will they be measured? What experimental research design will be used? What would a visual model of this design look like? What instrument(s) will be used to measure the outcome in the study? Why was it chosen? Who developed it? Does it have established validity and reliability? Has permission been sought to use it? What are the steps in the procedure (e.g., random assignment of participants to groups, collection of demographic information, administration of pretest, administration of treatment(s), administration of posttest)? What are potential threats to internal and external validity for the experimental design and procedure? How will they be addressed? Will a pilot test of the experiment be conducted? What statistics will be used to analyze the data (e.g., descriptive and inferential)? How will the results be interpreted?

Identifying the type of experimental procedure that best fits your proposed study In pre-experimental designs, the researcher studies a single group and provide an intervention during the experiment. In quasi-experimental designs, the researcher used control and experimental groups but does not randomly assign people to them. In true experimental designs, the researcher randomly assigns the participants to treatment groups. In single subject design, the researcher observes a single individual over time.

Drawing a diagram of experimental procedures X represents an exposure of a group to an experimental variable or event, the effects of which are to be measured O represents an observation or measurement recorded on an instrument Xs and Os in a given row are applied to the same specific persons. Xs and Os in the same column, or placed vertically relative to each other, are simultaneous The left-to-right dimension indicates the temporal order of procedures in the experiment (sometimes indicated with an arrow) The symbol R represents random assignment Separation of parallel rows by a horizontal line indicates that comparison groups are not equal by random assignment. No horizontal line between groups displays random assignment of individuals to treatment groups.

Strategies for establishing validity for qualitative studies Internal validity threats are experimental procedures, treatments, or experiences of the participants that threaten the researcher’s ability to draw correct inferences from the data about the population. External validity threats arise when experimenters draw incorrect inferences from the sample data to other persons, settings, and past and future situations. Also: Statistical conclusion validity and construct validity.

Chapter 9: Qualitative Procedures A checklist for qualitative research to form topic sections of a quantitative procedure The basic characteristics of qualitative research Determining how reflexivity will be included in a proposed study The differences between types of data collected in qualitative research Distinguishing between generic forms of data analysis and analysis within strategies of inquiry Different levels of analysis in qualitative research Strategies for establishing validity for qualitative studies

A checklist for qualitative research to form topic sections of a quantitative procedure Are the basic characteristics of qualitative studies mentioned? Is the specific type of qualitative strategy of inquiry to be used in the study mentioned? Is the history of, a definition of, and applications for the strategy mentioned? Does the reader gain an understanding of the researcher’s role in the study (post historical, social, cultural experiences, personal connection to sites and people, steps in gaining entry, and sensitive ethical issues)? Is the purposeful sampling strategy for sites and individuals identified? Are the specific forms of data collection mentioned and a rationale given for their use? Are the procedures for recording information during the data collection procedure mentioned (such as protocols)? Are the data analysis steps identified? Is there evidence that the researcher has organized the data for analysis? Has the researcher reviewed the data generally to obtain a sense of the information? Has coding been used with the data? Have the codes been developed to form a description or to identify themes? Are the themes interrelated to show a higher level of analysis and abstraction? Are the ways that the data will be represented mentioned – such as in tables, graphs, and figures? Have the bases for interpreting the analysis been specified (personal experiences, the literature, questions, action agenda)? Has the researcher mentioned the outcomes of the study (developed a theory, provided a complex picture of themes)? Have multiple strategies been cites for validating the findings?

The basic characteristics of qualitative research Natural setting Researcher as key instrument Multiple sources of data Inductive data analysis Participants’ meanings Emergent design Theoretical lens Interpretive Holistic account

Determining how reflexivity will be included in a proposed study Reflexivity means that researchers reflect about how their biases, values, and personal background, such as gender, history, culture, and socioeconomic status, shape their interpretations formed during a study.

The differences between types of data collected in qualitative research Observations Interviews Documents Audio-Visual Materials Every type of data collection has advantages and disadvantages

Different levels of analysis in qualitative research Interpreting the Meaning of Themes/Descriptions Interrelating Themes/Descriptions Themes Description Validating the Accuracy of the Information Coding the Data Reading Through All Data Organizing and Preparing Data for Analysis Raw Data (Transcripts, Field Notes, Images, etc.)

Strategies for establishing validity for qualitative studies Triangulate different data sources Use member checking to determine accuracy of findings Convey findings using rich, thick description Clarify bias Present negative or discrepant information Spend prolonged time in the field Use peer debriefing to enhance accuracy Use an external auditor to enhance accuracy

Chapter 10: Mixed Methods Approaches Understanding a definition of mixed methods research How timing, weight, mixing, and theory relate to a mixed methods design The differences among the six models for mixed methods inquiry How to draw a mixed methods procedure using appropriate notation The different writing structures for mixed methods research

Understanding a definition of mixed methods research Trace a brief history of its evolution. Define mixed methods research by incorporating a definition that focuses on combining both qualitative and quantitative research and methods Briefly discuss the growth of interest in mixed methods research. Note the challenges this form of research poses for the inquirer.

How timing, weight, mixing, and theory relate to a mixed methods design Weighting Mixing Theorizing No Sequence Concurrent Equal Integrating Explicit Sequential – Qualitative First Qualitative Connecting Implicit Sequential – Quantitative First Quantitative Embedding

The differences among the six models for mixed methods inquiry (1/3) The sequential explanatory strategy is characterized by the collection and analysis of quantitative data first, followed by the collection and analysis of qualitative data that builds on the results of the quantitative phase. The sequential exploratory strategy involves a first phase of qualitative data collection and analysis, followed by a second phase of quantitative data collection and analysis that builds on the results of the first qualitative phase.

The differences among the six models for mixed methods inquiry (2/3) The sequential transformative strategy is a two-phase project with a theoretical lens (e.g., gender, race, social science theory) overlaying the sequential procedures. Concurrent triangulation has the researcher collecting both quantitative and qualitative data concurrently, then comparing the two databases to identify if there is convergence, divergence, or some combination.

The differences among the six models for mixed methods inquiry (3/3) Concurrent embedded strategy has one data collection phase, during which both quantitative and qualitative data are collected simultaneously. Concurrent transformative approach is guided by the researcher’s use of a specific theoretical perspective as well as the concurrent collection of both quantitative and qualitative data.

How to draw a mixed methods procedure using appropriate notation A “+” indicates a simultaneous or concurrent form of data collection A “” indicates a sequential form of data collection Capitalization indicates weight or priority “Quan” and “Qual” are used instead of the full words, to show equality A QUAN/qual notation indicates the qualitative methods are embedded within a quantitative design Boxes highlight the quantitative and qualitative data collection and analysis

The different writing structures for mixed methods research For a sequential study, researchers typically organize quantitative data and analysis first, followed by qualitative data and analysis. In a concurrent study, qualitative and quantitative data is presented separately, but the analysis is combined. In a transformative study, the structure begins with advancing the advocacy issue then using either sequential or concurrent structure to organize the content.