Experimental Designs and Quantitative Data

Experimental Designs

  • Experimental designs are valuable for inferring causality.
  • Involve manipulating an independent variable and observing its impact on a dependent variable.
  • Two types: between subjects and within subjects.

Between Subjects Design

  • Participants are assigned to two or more groups (e.g., treatment and control).
  • Also known as between-groups design.
  • Random allocation helps ensure groups are similar at the start, reducing the risk of other factors explaining differences.
  • Participants don't get to choose their group, which can lead to dropouts.
  • Single-blind study: participants don't know their group assignment.
  • Double-blind study: neither participants nor researchers know group assignments.
  • More groups require larger sample sizes.
  • Power analysis: calculation to determine the number of participants needed in each group.

Within Subjects Design

  • The same participants are measured more than once on the dependent variable.
  • Common example: pre-post design, measuring a variable before and after an intervention.
  • Reduces variability caused by individual differences.
  • Longitudinal data: collecting data over time from the same participants.
  • Single-case experimental design (SCED): focuses on whether an intervention works for a specific individual.
  • SCEDs account for individual responses, unlike typical pre-post designs that aggregate data.

Drawbacks of Within Subjects and Longitudinal Designs

  • Practice effects: participants may improve simply due to familiarity with the task.
  • Maturation: performance may change naturally over time.
  • History effects: external events (e.g., a pandemic) can influence results.
  • Attrition: participants dropping out over time can reduce reliability.

Types of Quantitative Data

  • Four categories: observational behavioral data, self-report data, informant reports, and life outcome data.

Observation of Behavior (B Data)

  • Data collected from direct observation of behavior.
  • Examples: reaction time.
  • Often considered more objective.

Self Report

  • Individuals provide information about themselves (thoughts, feelings, behaviors, attitudes).
  • Collected through questionnaires, surveys, interviews, or focus groups.
  • Strength: direct access to inner experience.
  • Limitations: recall bias and social desirability bias.

Informant Reports

  • Information provided by someone who knows the person well.
  • Useful for cross-checking self-reports or when working with children.

Life Event Data

  • Objective outcomes that link psychological variables to real-world events.
  • Examples: GPA, employment history, medical records.
  • Provide context for interpreting psychological findings.