# HPEB 818

The flashcards below were created by user Anonymous on FreezingBlue Flashcards.

1. Threats to Validity
• Construct
• External
• Internal
• Statistical Conclusion
2. Threats to Statistical Conclusion Validity
• Low Statistical Power
• Violated Assumptions of Statistical Tests
• Fishing and the Error Rate Problem
• Unreliability of Measures
• Restriction of Range
• Unreliability of Treatment Implementation
• Extraneous Variance in the Experimental Setting
• Heterogeneity of Units
• Inaccurate Effect Size Estimation
3. SCV: Low Statistical Power
An insufficiently powered experiment may incorrectly conclude that the relationship between treatment and outcome is not significant.
4. SCV: Violated assumptions of Statistical Tests
Violations of statistical test assumptions can lead to either overestimating or underestimating the size and significance of an effect.
5. SCV: Fishing and the Error Rate Problem
Repeated tests for significant relationships, if uncorrected for the number of tests, can artifactually inflate statistical significance
6. SCV: Unreliability of Measures
Measurement error weakens the relationship between two variables and strengthens or weakens the relationship among three or more variables.
7. SCV: Restriction of Range
Reduced range on a variable usually weakens the relationship between it and another variable.
8. SCV: Unreliability of Treatment Implementation
If a treatment that is intended to be implemented in a standardized manner is implemented only partially for some respondents, effects may be underestimated compared with full implementation.
9. SCV: Extraneous Variance in the Experimental Setting
Some features of an experimental setting may inflate error, making detection of an effect more difficult.
10. SCV: Heterogeneity of Units
Increased variability on the outcome variable within conditions increases error variance, making detection of a relationship more difficult.
11. SCV: Inaccurate Effect Size Estimation
Some statistics systematically overestimate or under estimate the size of an effect.
12. Ways to increase statistical power
• use matching, stratifying, or blocking
• measure, and correct for covariates
• use larger sample sizes
• use equal cell sample sizes
• improve measurement (e.g. increase range of measurements/reduce dichotomized variables, add additional waves of measurement)
• increase the strength of treatment (e.g. increase dose differential)
• Use a within-participants design
• Use homogeneous participants selected to be responsive to treatment
• Reduce random setting irrelevancies
• Ensure that powerful statistical tests are used and their assumptions are met. (e.g. transforming the data)
13. Internal Validity Definition
Inferences about whether observed variation between A and B reflects a causal relationship from A to B in the form in which the variables were manipulated or measured.
14. Threats to Construct Validity
• Construct Confounding
• Mono-Operation Bias
• Mono-Method Bias
• Confounding Constructs with Levels of Constructs
• Treatment Sensitive Factorial Structure
• Reactive Self-Report Changes
• Reactivity to the Experimental Situation
• Experimenter Expediencies
• Novelty and Disruption Effects
• Compensatory Equalization
• Compensatory Rivalry
• Resentful Demoralization
• Treatment Diffusion
 Author: Anonymous ID: 229350 Card Set: HPEB 818 Updated: 2013-08-07 00:21:10 Tags: Eval qualifying exam Folders: Description: for the quals Show Answers: