Methodology Selection Decision Tree

Use this decision tree to identify which research methodology best fits your dissertation. Answer each question honestly based on your research questions, data availability, and disciplinary norms. This is a starting point for discussion with your advisor, not a final determination.

Step 1: What Do You Want to Know?

What type of question are you trying to answer?

Option A: I want to measure, count, or test relationships between variables (how much, how many, to what extent, what predicts).

→ Go to Step 2A: Quantitative Path

Option B: I want to understand experiences, meanings, or processes in depth (how, why, what is it like).

→ Go to Step 2B: Qualitative Path

Option C: I need both breadth and depth -- my research questions require numbers AND meaning.

→ Go to Step 2C: Mixed Methods Path

Step 2A: Quantitative Path

What is your primary research goal?

Compare groups:Testing whether groups differ on a variable (e.g., treatment vs. control)

Experimental or Quasi-Experimental Design

Tests: t-test, ANOVA, ANCOVA, MANOVA

Sample: Typically 30+ per group

Predict outcomes:Identifying which variables predict or explain an outcome

Correlational / Predictive Design

Tests: Multiple regression, logistic regression, path analysis

Sample: 10-15 participants per predictor variable (minimum)

Describe a population:Measuring attitudes, behaviors, or characteristics of a group

Survey / Descriptive Design

Tests: Descriptive statistics, chi-square, correlation

Sample: Varies by analysis; typically 100+ for surveys

Analyze existing data:Using publicly available or archival datasets

Secondary Data Analysis

Sources: NCES, CDC, Census, institutional databases

Note: May simplify IRB process (exempt or expedited review)

Step 2B: Qualitative Path

What is the focus of your inquiry?

Lived experience:How individuals experience a specific phenomenon

Phenomenology (or IPA)

Data: In-depth interviews (60-90 min each)

Sample: 4-10 participants (IPA) or 5-25 (descriptive phenomenology)

Process or change:How a process unfolds or how people respond to change over time

Grounded Theory

Data: Interviews, observations, documents; iterative sampling

Sample: 15-30+ (until theoretical saturation)

Culture or group:How a cultural group shares values, behaviors, or practices

Ethnography

Data: Extended observation, field notes, interviews, artifacts

Sample: 1 cultural group; prolonged engagement (months to years)

Bounded system:Understanding a specific case, program, event, or organization in depth

Case Study

Data: Multiple sources (interviews, documents, observations)

Sample: 1-5 cases

Patterns in text:Identifying themes across qualitative data without a specific methodological tradition

Thematic Analysis

Data: Interviews, focus groups, documents, open-ended survey responses

Sample: 6-30+ depending on data type

Step 2C: Mixed Methods Path

How will you combine quantitative and qualitative data?

Sequential explanatory:Collect quantitative data first, then use qualitative data to explain or elaborate on the results

Explanatory Sequential Design (QUAN → qual)

Example: Survey 200 teachers, then interview 10 whose responses were outliers

Sequential exploratory:Collect qualitative data first to explore, then use findings to build a quantitative instrument or test

Exploratory Sequential Design (QUAL → quan)

Example: Interview 12 patients, use themes to develop a survey, administer to 300

Concurrent:Collect both types of data simultaneously and integrate during analysis

Convergent Design (QUAN + QUAL)

Example: Administer survey AND conduct interviews during the same data collection phase

Factor	Quantitative	Qualitative	Mixed Methods
Research questions	How much? How many? What predicts?	How? Why? What is the experience?	Both types
Sample size	Larger (30-300+)	Smaller (4-30)	Varies by strand
Data type	Numbers, scores, measurements	Words, images, observations	Both
Analysis	Statistical tests (SPSS, R, STATA)	Coding and themes (NVivo, Atlas.ti)	Both approaches
Timeline	Often shorter data collection	Often longer data collection	Longest overall
Generalizability	Higher (if sample is representative)	Lower (transferability instead)	Moderate
Committee expectations	Statistical expertise required	Philosophical grounding required	Both; advisor with mixed methods expertise ideal

Step 1: What Do You Want to Know?

Step 2A: Quantitative Path

Step 2B: Qualitative Path

Step 2C: Mixed Methods Path

Quick Reference: Methodology Comparison

Before You Decide: Key Questions to Discuss With Your Advisor