Kazdin ch.2

Single-Case Research Designs

Conclusions

  • Importance of unbiased conclusions in research
  • Openness to diverse methodologies in research

Teaching Methodology

  • Focus areas:
    • Key techniques
    • Procedures and practices:
    • Selection of experimental designs
    • Participant recruitment
    • Random assignment procedures
    • Selection of measures
    • Timing of administration
    • Statistical methods
  • Practical needs of students conducting research:
    • Desire for clear steps towards study completion
    • Risk of losing sight of rationale and goals behind methodologies

Limitations of Randomization

  • Randomization importance in group experiments noted:
    • Decreases likelihood of group differences
    • Addresses assumptions required for statistical tests
  • Nuisance variables defined:
    • Factors that do not matter for the study but can influence results (e.g., socioeconomic status, age, sex, ethnicity)
  • Random assignment may not equalize groups:
    • Definition of randomization means chance variability can create differential group compositions
    • Small sample sizes heighten risk of unbalanced variables
  • Emphasis on the need to focus on the purpose of research rather than methodological practices and dogmas.

Statistical Considerations

  • Blair (2004) and Hsu (1989) noted that the target sample (N) of 20-40 in two-group studies increases chance of differences in nuisance variables leading to misinterpretation of results.

Underpinnings of Scientific Research

  • Goal: Draw valid inferences free from biases and artifacts
  • Replication significance in scientific research:
    • The necessity to reproduce findings across multiple investigations
  • Clear findings needed to eliminate alternative explanations regarding intervention effects:
    • Methodological practices assist in ruling out extraneous factors
    • Aim to accurately assess intervention impacts.

Drawing Valid Inferences

  • Key characteristics of experimentation:
    • Investigates direct influence of independent variables on dependent variables
    • Simplifies conditions to enable clear separate influence assessment
  • Functional elements in experimental design arise from:
    • Parsimony:
    • Selection of simplest explanations among competing ones
    • Examples of terms related to parsimony: economy, simplicity, and Occam's razor
  • Historical reference to William of Ockham (1287-1347) and principle focused on avoiding unnecessary complexity in explanations of phenomena.

Parsimony in Practice

  • Demonstrated through the need for simplest explanations in varied contexts (e.g., UFO sightings).
  • Importance of evaluating existing concepts before introducing new, complex ideas.

Plausible Rival Hypotheses

  • Definition and role:
    • Interpretation of results based on influences other than the studied one.
    • Not solely focused on parsimony at completion of investigations.
    • Example: Effect of a new diet on IQ; retesting as a plausible alternative hypothesis.

Threats to Validity

  • Identification of rival explanations:
    • Classifications:
    1. Internal Validity: Varied factors impacting reliability of intervention results.
    2. External Validity: Generalizability of results in different contexts.
    3. Construct Validity: Evaluation of the actual constructs leading to observed effects.
    4. Data-Evaluation Validity: How findings are interpreted through provided data.

Internal Validity (Definition & Threats)

  • Internal validity ensures results are attributable to independent variable effects:
    • Key factors include history, maturation, instrumentation, testing, and statistical regression explained in detail.
    • Discussing Instrumentation highlights potential misinterpretations of results from varying measurements.

External Validity (Definition & Threats)

  • External validity ensures findings can be generalized:
    • Review of major external threats classified as:
    • Across subjects
    • Across responses/measures
    • Across settings
    • Across timelines and change agents
    • Includes the conversation of WEIRD (Western, Educated, Industrialized, Rich, and Democratic) universities' limitations.

Construct Validity (Definition & Threats)

  • Construct validity focuses on underlying causal relationships:
    • Critical examination of interpretations made about study results.
    • Example in psychotherapy efficacy needing scrutiny on why treatment works beyond confirming effects.

Validity Evaluation Process

  • Data-Evaluation:
    • Discussions relate to data's clarity, reliability, and any potential variability obscuring findings. Threats include excessive variability, trends, insufficient data, and mixed patterns.

Methodological Priorities

  • Research cannot comprehensively navigate all validity challenges concurrently:
    • Internal threats typically prioritized; differing purposes give priority deviations.
    • Discussion about balancing between traditional laboratory studies and applied research implications.

Implications for Researchers

  • Investigators must remain aware of:
    • The potential threat implications of variability and how they destabilize unleashed research outcomes.
    • Importance of addressing proper methodologies and maintaining integrity with ethical boundaries in research.
  • Closing statement emphasizes the need for thorough awareness, accessibility of methods, and integrity in reporting findings.