Correlation and Ethical Research Principles

Correlation Regression

• Measures the strength and direction of the relationship between two variables.
• r represents the correlation coefficient, ranging from -1 to +1.
• r² represents the proportion of variance shared by the two variables.

Ethical Research

• Guided by the Tri-Council Policy Statement (TCPS).
• Core Principles:
  • Respect for persons
  • Concern for welfare
  • Justice

TCPS

• Established by three Canadian funding agencies:
  • CIHR (Canadian Institutes of Health Research)
  • NSERC (Natural Sciences and Engineering Research Council)
  • SSHRC (Social Sciences and Humanities Research Council)

Applying Ethical Principles

• Respect for persons: Informed consent, autonomy, voluntariness
• Concern for welfare: Risk-benefit analysis, confidentiality
• Justice: Equal distribution of burden and benefit

Research Ethics Board (REB)

• Reviews research proposals to ensure ethical conduct.
• Minimal risk: can be reviewed by one person.
• Greater risk: requires full board review.

Deception in Research

• Involves concealing the true purpose of the study or staging events.
• Raises ethical concerns about autonomy and informed consent.

Reliability

• Refers to the consistency and stability of a measurement.
• Types:
  • Face validity: Assesses whether a measure appears to be valid on the surface.
  • Content validity: Ensures that a measure covers all relevant aspects of the construct.
  • Measure reactivity: Occurs when participants change their behavior due to awareness of being observed.

Internal Consistency Reliability

• Measures the consistency of responses to items within a single measure.
• Methods:
  • Cronbach's alpha: Measures average correlation of each item with all other items.
  • Omega coefficient: A more robust alternative to Cronbach's alpha.
  • Split-half reliability: Correlates performance on two halves of a measure.

Complex Experiments

• Simple main effect: Analyzes the effect of one independent variable on the dependent variable at a single level of another independent variable.
• Main effect: Analyzes the overall effect of one independent variable on the dependent variable, averaged across all levels of other independent variables.

Multiple Regression

• Tests the unique contribution of multiple independent variables in predicting a dependent variable (criterion).
• Multiple correlation (R): Represents the correlation coefficient of the combined predictors on the criterion.

Partial Correlation

• Investigates the relationship between two variables while controlling for the influence of a third variable.

Reliability in Measurement

• Face validity is a measure of how well a test appears to measure what it is supposed to measure. However, it is not a reliable indicator of validity as it is based solely on appearances.
• Content validity measures how well a test or assessment captures all aspects of the variable being measured.
• Measure Reactivity refers to a situation where a participant changes their behavior due to the awareness of being observed.

Internal Consistency Reliability

• Cronbach's alpha is a measure of internal consistency reliability that calculates the average correlation between all items in a measure.
• Omega coefficient is a more desirable measure of internal consistency reliability than Cronbach's alpha.
• Split half reliability evaluates internal consistency by measuring the correlation of performance on each half of a measure.

Simple Main Effect vs. Main Effect

• A simple main effect evaluates the impact of one independent variable (IV) on the dependent variable (DV), focusing on the effect of a single level of another IV.
• A main effect refers to the overall effect of an IV on the DV, averaged across all levels of other IVs.

Ethical Research: Tri-Council Policy Statement (TCPS)

• The Tri-Council Policy Statement (TCPS) is a set of ethical guidelines for research involving human participants in Canada.
• It is developed by three agencies:
  • Canadian Institutes of Health Research (CIHR)
  • Natural Sciences and Engineering Research Council (NSERC)
  • Social Sciences and Humanities Research Council (SSHRC)

Core Principles of Ethical Research

• Respect for persons: This principle emphasizes the importance of autonomy and informed consent.
• Concern for welfare: This principle involves considering the potential risks and benefits of research, ensuring participant safety, and protecting their well-being.
• Justice: This principle ensures that research benefits are distributed equitably and that the burdens of participation are shared fairly.

Applying Core Principles of Ethical Research

• Respect for persons: Participants should be empowered to make independent decisions about their participation in research. Informed consent is crucial to ensure this.
• Concern for welfare: Risk-benefit analysis is performed to weigh potential risks against potential benefits. Confidentiality is maintained to safeguard participant privacy.
• Justice: Research should not place an undue burden on any specific group, and benefits should be distributed fairly among the population.

Research Ethics Board (REB) Actions

• Minimal risk research: This research involves minimal risk to participants and requires review by a single member of the REB.
• Greater risk research: This research involves potential risks to participants and requires full board review.

Funding Requirements for Research

• Research projects involving human participants must have REB approval.
• The research must adhere to the TCPS2 guidelines.

Deception in Research

• Deception involves:
  • Concealing the true purpose of the research.
  • Staging events or situations.

Autonomy Issues in Research

• Autonomy is compromised when participants lack the freedom to make independent decisions about their participation in research.
• Voluntarily participation is essential to uphold autonomy.

Descriptive Statistics and Correlation

• Correlation coefficient (r) measures the linear relationship between two variables.
• Coefficient of determination (r²): Represents the proportion of variance in one variable that is explained by the other variable.
• Multiple regression: Analyzes the unique contribution of several predictor variables in predicting a criterion variable.
• Multiple correlation (R): The overall correlation of multiple predictor variables on a criterion variable.
• Partial correlation: Measures the correlation between two variables, while controlling for the effects of a third variable.