Module 4-Slides Flashcards
Design Validity
(applicable to quantitative study)
Relates to the truthfulness or accuracy of study results (Believability)
External Validity
Construct Validity
Internal Validity (for intervention studies/explanatory research)
Statistical Conclusion Validity
*Each form is cumulatively dependent on the components below it
Explanatory Research GOALS
Corresponds to 4 types of design validity
The PURPOSE of design Validity and type of Design is…
to examine issues of threats that must be controlled in the design and analysis of research
Statistical Conclusion Validity
Appropriate use of statistical procedures to assess the relationship between the IV and DV
Potential threats:
-Low statistical power (small sample size)
-Violated assumptions of statistical tests (level of measurement, frequency distribution)
-Reliability and variance (unreliable measure)
-Failure to use “intention to treat (ITT) analysis”
Intention to treat (ITT) (not Tx but statistical analysis)
Usually described a “once randomized, always analyzed”
Includes every subject who is randomized according to randomized Tx assignment
Ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization
Maintains baseline/prognostic balance generated from the original random allocation or assignment
Internal Validity
The extent to which experimental Tx (IV) really caused the observed change in the outcome measures (DV)
Potential for confounding factors (alternative causes) to interfere with the relationship between IV andDV
Internal Validity - Internal Threats
AHA TIMS
History
Maturation
Attrition
Testing
Instrumentation
Regression to the mean
Selection (assignment)
Internal Validity - Social Threats
Diffusion or imitation
Compensatory equalization
Compensatory rivalry
Demoralization
History - Did unanticipated events occur during the study that could affect the DV?
Nature of Threats:
events unrelated to the Tx of interest that influence the study’s outcome
*confounding effect of specific events, other than the experimental intervention, that occur after the introduction of the IV or between a pretest and posttest
Solution:
Control group and random assignment: to separate the effect of history
Time or Plan the study to avoid a predictable event
Apply statistical adjustment (ANCOVA)
Maturation - Were changes in the DV due to normal development or the simple passage of time?
Threat:
changes in human behavior or function OVER THE COURSE OF TIME that may influence the study results
Solution:
Use random assignment
Randomize the testing or Tx order
Apply statistical adjust.
Attrition (aka Drop-out/Mortality) - Is there a differential loss of subjects across groups?
Threat:
loss of subjects causes a reduction in sample size
cause imbalanced baseline characteristics
Solution:
Replacement of lost subjects if possible
Re-examination of data to see existing status
Statistical ITT analysis
*NO RANDOM ASSIGNMENT
Testing - Did the pretest or repeated test affect scores on the posttest?
Threat:
repeated testing on subjects that may lead to increased familiarly or inappropriate cues provided by the tester (construct validity)
Solution:
Elimination of multiple testing
Use of randomly selected experimental and control groups
Instrumentation - Did the DV change because of how it was measured?
Threat:
Problems w/the tool used to measure the variables of interest
Inappropriate selection of the tool (Measurement)
Solution:
Select appropriate technique or instrument
Calibrate instrument
User training or practice in taking measurement
Regression to the Mean - Is there evidence of regression from pretest to posttest scores?
Threat:
occurs when subjects enter a study with an extreme value (outlier) for BASELINE of outcome measure
Solution:
trim outliers
take repeated baseline measures
use a CONTROL GROUP
Assignment (Selection) - Is there bias in the way subjects have been assigned to experimental groups?
Threat:
Unequal baseline characteristics of groups that might influence the study’s outcome
Solution:
Random assignment to groups
Define inclusion and exclusion criteria adequately
Statistical adjustments (ANCOVA)