Research Design and Validity Quiz

Study Notes

Validity

Construct validity assesses how well a measurement corresponds to the theoretical concept it's supposed to measure. It encompasses face validity (appearance of measuring what it claims), convergent validity (different instruments measuring the same construct yield similar results), and discriminant validity (different constructs are measured distinctly and not correlated).
Criterion-related validity evaluates how well a measure predicts the results of another measure.
Content validity assesses whether a measurement tool covers all relevant aspects of the construct being measured.
Test validity types include criterion, content, and construct.
Statistical conclusion validity investigates whether the relationship between the independent and dependent variables is statistically sound.

Research Design

Experimental Design: Allows researchers to make causal inferences about the relationship between variables. This design uses random assignment to ensure participants have an equal chance of being assigned to different treatment groups.
Within-subjects design: Each participant experiences all conditions of the experiment.
Between-subjects design: Each participant experiences only one condition of the experiment.
Solomon Four-Group Design: Involves four groups with varying combinations of pretests, treatments, and posttests, allowing for the analysis of treatment effects while controlling for pretest effects.
Time Series Design: Measures changes in a group over time.
Interrupted time series design involves repeated measures on the same subjects across different time periods.

Threats to Validity

Extraneous variables can influence the results if not controlled for.
Threats to internal validity impact the causal relationship between independent and dependent variables, such as maturation, and history effects.
Threats to external validity limit the generalizability of research findings to other settings and populations.
Controls: Methods to rule out threats to validity, including holding variables constant.

Other Important Concepts

Statistical power: The probability of correctly rejecting the null hypothesis when it is false.
Main effect: The overall impact of one independent variable on the dependent variable.
Moderator variable: Influences the relationship between the independent and dependent variable, potentially changing the strength or direction of that relationship.
Operational definitions: Precisely define a construct for scientific study.
Counterbalancing: Helps mitigate potential biases related to the order of treatments in within-subjects designs.
Test-retest reliability: Involves comparing results from the same test taken at different times.
Block randomization: Helps counteract potential biases in the order of conditions.
Contiguity: In inferring causality, the presumed cause and effect must occur close together in time and space.
Regularity: The consistency of natural laws regardless of time or location.

Data Handling

Phi coefficient: Used to gauge the strength of association between two categorical variables.
Pearson correlation: A statistical measure used to quantify the correlation between two continuous variables.
Binning: Divides continuous data into discrete categories for analysis.

Description

Test your knowledge on the various types of validity in research design, including construct, criterion-related, and content validity. Explore how these concepts impact the integrity and interpretation of research findings. This quiz is essential for understanding the foundations of effective research methodologies.