FIELD METHODS (MIDTERMS)

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Description and Tags

RRL TO QUANTITATIVE

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81 Terms

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literature review

To determine if a topic is worth studying, narrow the scope, identify gaps, and form a foundation for research design.

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research topic

The subject matter of the study (few words/short phrase) that becomes the central idea to explore.

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3 strategies for developing a topic.

(1) Draft a concise working title (≤12 words),

(2) Pose topic as a research question,

(3) Check feasibility (participants/resources).

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Availability of participants; access to resources (time, data, software).

Adds to knowledge, elevates underrepresented voices, advances social justice, has broader appeal, aligns with career goals.

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Adds to knowledge, elevates underrepresented voices, advances social justice, has broader appeal, aligns with career goals.

What questions decide if a topic should be researched?

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Integrate (summarize),

Criticize (point flaws),

Bridge (connect topics),

Identify issues (highlight debates/gaps)

Cooper’s four formats for using literature

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RRL in qualitative

may place lit at intro, separate chapter, or end (inductive)

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RRL in qualitative

usually structured, separate chapter early to test theory.

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Steps for conducting a literature review (7 steps).

1) Identify keywords,

2) Search databases,

3) Locate ~50 reports,

4) Skim/select central works,

5) Design literature map,

6) Draft summaries,

7) Assemble review and highlight themes/gaps.

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literature map

A visual diagram that groups literature and shows where the proposed study fits—how it adds/extends research

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abstract (5 components)

Problem/issue, purpose/aim, data collection (who/where/type), results/findings, practical implications/audience.

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APA (most common in psych), Chicago; consistency in style (citations, headings, tables) is essential.

What are key style manuals to consider?

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Definition of terms

Clarity, consistency, precision, scientific accuracy. Define when first used; quantitative usually has a separate section.

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Broad syntheses → reputable journal articles → books → recent conference papers → dissertations → cautious use of online sources.

literature selection — order of importance

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Use of theory- Quantitative

tests hypotheses from theory (often early).

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Use of theory- Qualitative

may generate theory (grounded) or use a lens (ethnography).

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Use of theory- Mixed

can both test and generate; may use social justice frameworks.

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“theory” in quantitative research

An interrelated set of constructs/propositions specifying relationships among variables to explain phenomena.

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Micro: small time/space (e.g., face work).

Meso: link micro and macro (organizations).

Macro: explain large aggregates/societies.

What are micro-, meso-, and macro-level theories?

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Early section titled “Theoretical Perspective” or integrated where it best guides hypotheses and data collection.

common placements of theory in a paper

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theoretical-perspective section include?

Name and origin,

application topics,

central propositions/hypotheses,

and how the theory applies to IV→DV in the study.

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“theoretical lens” in qualitative research

An orienting perspective (e.g., feminist, critical race) shaping questions and analysis with often transformative aims.

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Early integration of framework, community involvement, advocacy stance, addressing power/inequities, ethical inclusion across process.

Mixed-methods participatory-social-justice framework — key features?

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nine core arguments in proposal

1) What readers need to understand,

2) What readers need to know,

3) What you propose to study,

4) Setting & people,

5) Methods,

6) Analysis plan,

7) Validation,

8) Ethical issues,

9) Preliminary practicability evidence

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Franklin’s three-stage writing model

1) Outline,

2) Draft and rearrange,

3) Edit/polish sentences

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writing habit

Write daily, small regular sessions,

track progress,

break tasks into manageable pieces,

share drafts with peers

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Readability

Umbrella: core idea;

Big: specific ideas under umbrella;

Little: reinforce big thoughts;

Attention: keep reader engaged and organized.

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ethical steps before study

Consider codes of ethics,

apply to IRB,

obtain permissions,

select unbiased site,

negotiate authorship for publication.

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Ethical considerations during data collection

Identify beneficial problem,

disclose purpose,

avoid pressure,

respect cultural norms,

minimize disruption,

provide benefits,

avoid deception (or debrief),

respect power imbalances.

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introduction

Create interest, state the problem, place study in context, reach audience, clarify research purpose/significance.

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Deficiencies Model's five steps for introductions

1) State problem,

2) Review past research,

3) Identify deficiencies (gaps),

4) Show significance/audience,

5) State purpose.

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research problem

A narrative hook,

clear problem statement,

justification (many refs),

alignment with method,

and clear scope.

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Qualitative introduction

explore phenomenon, personal/first-person style, use when concept immature. (Explore)

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Quantitative introduction

explain relationships, objective style, theory-focused. (Explain)

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Mixed study introduction

combine both—depends on emphasis. (Expand)

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Start broad (related topics), then narrow to your focus—use the inverted triangle approach.

What to do when literature is scarce?

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purpose statement

A sentence/paragraph conveying why the study will be conducted and what it intends to accomplish (aim/objective).

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addressing the problem in an intro

Give broad summaries (categories/trends), position your study in dialogue, prioritize empirical studies, and use inverted triangle if literature is sparse.

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qualitative purpose statement

Central phenomenon, participants, site, strategy of inquiry, action verbs (explore/understand), nondirectional language, delimit scope.

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quantitative purpose statement

State theory/model, identify IVs/DVs (and order them IV→DV), specify strategy (survey/experiment), participants and site

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mixed methods purpose statement

Overall intent, info about both strands, type of mixed design (convergent/explanatory/exploratory sequential), and rationale for mixing

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Convergent design

collect qual + quant concurrently and compare.

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Explanatory sequential design

quant first, then qual to explain (and vice-versa)

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Qualitative research questions: central vs subquestions

1–2 central broad questions; 5–7 subquestions for details/interview prompts; open-ended wording; indicate participants and site.

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quantitative research questions/hypotheses

Focus on variables and relationships; order IV before DV; base on theory; write clear null (H₀) and alternative (H₁) hypotheses; specify direction if directional.

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quantitative questions: descriptive, relationship, comparison

Descriptive: frequency/distribution.

Relationship: association controlling for mediators.

Comparison: group differences in DV.

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mixed methods research questions

Separate sections for quantitative questions/hypotheses, qualitative questions, and the mixed-methods integration question (how results inform each other).

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Surveys

Describe trends, attitudes, opinions; test associations; answer descriptive, relationship, and predictive questions.

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survey forms of data collection

Mail, telephone, Internet, personal interviews, group administration. Internet is common but has trade-offs.

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Cross-sectional: one time point.

Longitudinal: multiple time points to observe change/predict.

Cross-sectional vs longitudinal surveys

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Population: full group of interest;

sample: subset studied. Describe identification and access (frames)

population vs sample

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sampling designs

Single-stage (direct sampling),

multistage/cluster (sample groups then individuals)

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sampling methods

Random (equal probability),

systematic (every Xth after random start),

nonprobability/convenience (availability)

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stratification

Divide population by known traits and sample proportionally to ensure subgroup representation—improves representativeness.

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power analysis

Estimates sample size to detect effects; requires effect size, alpha (Type I, often .05), beta/power (Type II, often .20/power .8). Done before data collection

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instruments

Name of instrument used, source, whether original/modified, sample items, scales, reliability (Cronbach’s α), and validity evidence (content, predictive, construct)

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Cronbach’s α around .7–.9 is optimal.

What α range is considered acceptable for internal consistency?

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pilot test

Before study. To check content validity, clarity, format, internal consistency, and participant fatigue; specify number of testers and revision plans.

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survey instrument

Cover letter, demographics, attitudinal/behavioral/factual items, closing instructions; appropriate scaling (Likert vs categorical)

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1) Advance-notice letter;

2) Survey sent 1 week later;

3) Follow-up postcard 4–8 days after;

4) Final personalized mail to nonrespondents 3 weeks later.

Total ~4 weeks.

four-phase mailed survey administration timeline

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data analysis plan

1) Report responses (n, %),

2) Assess response bias,

3) Descriptives (means, SDs), handle missing data,

4) Scale scoring & reliability,

5) Inferential statistics (justify tests),

6) Present/interpret results (tables/figures).

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response bias

Wave analysis, respondent vs nonrespondent comparisons

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inferential reporting elements

Test statistics, p-values, effect sizes, and confidence intervals; justify test choice based on measurement scale and distribution.

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results

Relate findings to research questions/hypotheses and prior studies, discuss theoretical/practical implications, limitations, alternative explanations, and future research.

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experiment

Systematic manipulation of IV(s), control of extraneous variables, and (ideally) random assignment to infer causality.

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experimental method plan

Participants & design, procedure, measures/instruments, manipulation checks, random assignment, control vs treatment groups.

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pre-experimental designs

One-shot case study (A X O), One-group pretest–posttest (A O₁ X O₂), Static group comparison (A X O / B O)

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quasi-experimental designs

Nonequivalent control-group, interrupted time-series (single-group or control-group versions)

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Examples of true experimental designs

Pretest–posttest control-group (R O X O / R O O),

Posttest-only control-group (R X O / R O),

Solomon four-group

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Single-subject design example

A–B–A design: baseline (A), treatment (B), withdrawal (A) to observe change/return to baseline.

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participant recruitment description

How recruited (flyers, email), inclusion/exclusion criteria, compensation, selection process

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study quasi-experimental

When there is no random assignment or only partial randomization.

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matching and random assignment used for

To achieve group equivalence and reduce selection bias (random assignment best for internal validity).

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validity threat

Internal, external, statistical conclusion, and construct validity threats.

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internal validity threats (participant-related)

History, maturation, regression to mean, selection, mortality (attrition)

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treatment-related internal threats.

Diffusion of treatment, compensatory rivalry, resentful demoralization.

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procedure-related internal threats.

Testing effects (pretest influences posttest), instrumentation changes.

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External validity threat

Person (sample not representative), Setting (artificial environment), Time (results specific to time/context)

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statistical conclusion validity

Threats from low power, violations of assumptions, leading to incorrect inferences about statistical significance

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construct validity

Whether variables are properly defined and measured—poor operationalization weakens conclusions.