Essential Research Methods & Ethical Principles

Research Ethics: Core Principles & Case Studies

Ethical Violations: Critical Case Studies – Examples to understand in detail:

• The Little Albert Study – Classical conditioning of fear in a child without informed consent; no debriefing; potential long-term harm; lack of parental protection; poor beneficence and justice.

• The Bobo Doll Study – Exposed children to aggressive behavior; lack of parental consent (in early days); potential modeling of harm; possible psychological distress.

• The Stanford Prison Experiment – Psychological harm; lack of informed consent for extreme conditions; poor withdrawal rights; deception.

Belmont Report Principles

• Respect for Persons (Autonomy, Informed Consent)

• Beneficence (Maximize Benefits, Minimize Harm)

• Justice (Fairness in Distribution of Benefits/Risks)

• Integrity (Honesty, Transparency)

Single Factor Experimental Designs

• Key Characteristics

  • Two or More Levels: One Independent Variable (IV) with two or more levels.

  • Between-Subjects Design: Each participant experiences only one level.

  • Within-Subjects Design: Each participant experiences all levels.

• More than two levels allows testing for non-linear relationships.

• Statistical Analysis

  • Analysis: t-test for two levels, ANOVA for three or more levels.

Factorial Designs & Interactions

• Main Effect: The effect of one Independent Variable (IV) ignoring the other(s).

• Interaction Effect: The effect of one IV depends on the level of another IV.

  • Graphing Tip

    • If lines are not parallel on a graph, a possible interaction exists.

• Example: Drug dosage by Age group – effectiveness changes differently for young versus old participants.

Quasi-Experimental vs. Correlational Studies

• Quasi-Experimental Studies

  • Possesses Independent Variable (IV) and Dependent Variable (DV), but lacks random assignment. Often utilizes naturally occurring groups.

• Correlational Studies

  • Measures variables to identify relationships, but involves no manipulation. Cannot infer causation.

• Key Distinction

  • Quasi-experimental designs can test cause-effect hypotheses more directly than correlational studies, but potential confounds remain.

Ecological Validity in Experimental Design

• Ecological Validity: How well study results generalize to real-world settings.

• Role of Design: Field experiments generally offer higher ecological validity than lab experiments, but with less control over extraneous variables.

NHST & Bayesian Statistics Fundamentals

• NHST Logic (Null Hypothesis Significance Testing)

  1. Assume the null hypothesis (H₀) is true.

  2. Collect data and calculate the p-value.

  3. If p < α (alpha level), reject H₀.

• Statistical Errors

  • Type I Error: Rejecting H₀ when it is actually true (false positive).

  • Type II Error: Failing to reject H₀ when it is actually false (false negative).

• Bayesian Statistics

  • Updates the probability of a hypothesis given new data; focuses on degrees of belief rather than simply rejecting or accepting a null hypothesis.

Effective Survey Construction Principles

• Clear, concise wording.

• Avoid double-barreled and leading questions.

• Use a neutral tone.

• Closed vs. Open Questions: Choose based on specific data needs.

• Pilot test the survey to ensure clarity and effectiveness.

Observational Research Methods

• Naturalistic Observation

  • Observe participants in their natural setting without interference.

  • Pros: High ecological validity.

  • Cons: Low control over variables, potential for reactivity.

• Participant Observation

  • Researcher actively joins the group being studied.

  • Pros: Provides rich, detailed data and deep contextual understanding.

  • Cons: Potential for observer bias, significant ethical concerns.

Qualitative & Quantitative Research

• Qualitative Research

  • Explores how and why phenomena occur; typically inductive, uses smaller samples, and yields rich, descriptive data.

• Quantitative Research

  • Tests specific hypotheses; typically deductive, uses larger samples, and involves numerical analysis.

• Complementary Use

  • Mixed-methods approaches combine both to strengthen findings and provide a more comprehensive understanding.

Advanced Research Techniques

• Functional Magnetic Resonance Imaging (fMRI)

  • Measures brain activity by detecting changes in blood flow. Offers high spatial resolution but relatively low temporal resolution.

• Physiological Measures

  • Includes measures like heart rate, skin conductance, and hormone assays, linking behavior to underlying physiological states.