PSYC 365 Developmental Chapter 2

Chapter 2: Research Methodology Review

Operational Definitions

• Definition: Statements of procedures used to define research variables, which clarify how variables are measured.

• Importance:

  • Facilitate replication of studies.

  • Ensure accuracy and consistency in research findings.

• Example:

  • JMU study on sandwich sales involves defining what constitutes a "sandwich."

    • Different interpretations lead to inconsistent data collection (e.g., Professor A vs. Professor B).

    • Highlights challenges with vague constructs in psychology (e.g., intelligence, well-being).

Reliability and Validity

• Reliability:

  • Refers to the consistency of responses across different measurements.

  • Example: Similar scores on a personality test administered on different days.

• Validity:

  • Concerns the accuracy of a measure—are we assessing what we intend to?

  • Good measure should be both reliable and valid.

  • Illustration:

    • Bull's Eye Analogy:

      • Clustering of dots in the center indicates both reliability and validity.

      • Clustering off-center indicates reliability without validity.

• Continuum Concept:

  • Reliability and validity are not binary; they exist on a continuum.

Significance in Research

• Statistical vs. Practical Significance:

  • Statistical significance indicates results are likely not due to chance (e.g., GPA comparison).

  • Practical significance considers whether findings are meaningful; small differences may not be meaningful despite statistical significance.

• Effect Size:

  • A measure of the magnitude of the difference between groups; influences practical significance.

Importance of Sampling

• Representative Sampling:

  • Impacts generalizability of findings; narrow or homogenous samples limit applicability to broader populations.

  • Example: JMU intervention to reduce binge drinking may not apply to other demographics.

• Implication for Research:

  • Findings from a specific sample (e.g., psych majors) may not generalize to others (e.g., business majors).

Replication in Research

• Definition:

  • Repeating studies to assess the reliability of findings.

  • Repeated studies under varying conditions increase confidence in results.

• Replication Crisis:

  • Many studies cannot be duplicated, raising concerns over research validity.

  • Influences include the pressure to publish significant results rather than replicable findings.

  • Push for open science and publication of null results to reduce bias in literature.

  • Brian Nosek and the Center for Open Science advocate for transparency in research.

Study Designs

Experiments & Quasi-Experiments:

• Experiment:

  • Allows for causal inferences by manipulating an independent variable and comparing effects.

• Quasi-Experiment:

  • Tries to establish causation without random assignment; dependent on pre-existing groups, limiting certainty.

Correlational Studies

• Definition:

  • Examine the relationship between variables without implying causation.

• Correlation Coefficient:

  • Indicates direction (positive or negative) and strength (range from 0 to 1).

  • Strength and direction examples illustrated with correlation types (positive/negative).

Time Span Designs

• Cross-Sectional Design:

  • Data collected from different groups at one time to assess group differences (e.g., cognitive ability across ages).

• Longitudinal Design:

  • Data collected from the same group over time, observing changes (e.g., cognitive development in one cohort).

• Sequential Design:

  • Combines cross-sectional and longitudinal, allowing examination of age and cohort effects simultaneously.

• Microgenetic Design:

  • Examines short-term development of traits observing frequent sessions (e.g., strategies in math problem solving).

Practice Activity

• Activity in Canvas:

  • Review abstracts to determine study types, variables, and time spans to enhance understanding.