Lecture+18+-+2.24.25+-+Within-groups+designs
Page 1
Overview
The page contains grading classifications: Excellent, Very Good, Good, Average, Poor.
Mention of a product taste testing link.
Page 2
Summary of Elements
Reiteration of grading classifications.
Mention of taste testing, similar to Page 1.
Link provided for product taste testing solutions.
Page 3
Recap of Relevant Content
No significant new content compared to previous pages.
Page 4
Consistency in Content
Continues the theme with similar content as previous pages including grading levels and the taste testing link.
Page 5
Important Reminders
Midterm grades will be available by Friday.
Quiz 7 submission due before midnight.
The final exam will be online, focusing on material since the second exam but with cumulative themes.
Page 6
Between and Within-groups Designs
Discusses various designs in experiments.
Topics include extraneous variables, confounds, instrumentation effects, and participant treatment.
Advantages/disadvantages of within-subjects designs are mentioned.
Page 7
Controlled Experiments: Between-groups
Definition of between-groups (also known as between-subjects or independent-groups).
Essential requirements: equivalence of groups and absence of confounds are highlighted.
Impacts on causal inference.
Page 8
Extraneous Variables Control Strategies
Discusses methods to control extraneous variables to avoid bias.
Introduces single-blind and double-blind procedures.
Page 9
Treatment of Groups
Emphasis on uniformity in treatment across experimental groups.
Importance of matching conditions to avoid introducing confounds.
Page 10
Instrumentation Effects
Discusses variations in measurement accuracy over time and their impact on results.
Page 11
Participant Attrition
Outlines systematic and non-systematic attrition from studies and their implications.
Page 12
Sensitivity of Dependent Variables
Highlights the importance of having sensitive measures to detect changes and the potential for Type II errors.
Page 13
Determining Sensitivity in Measures
Discussion of ceiling and floor effects in measuring dependent variables.
Page 14
Between-groups Advantages and Disadvantages
Lists benefits such as straightforward causal effects and comparisons.
Discusses downsides for requiring additional participant groups and potential for variances.
Page 15
Example of Controlled Experiments
Identifies the population and sample sizes used in a between-groups design.
Page 16
Within-groups Designs
Definitions and characteristics of within-subjects designs.
Notes the minimized error variability and participant requirements.
Page 17
Reducing Variability
Discusses implications of individual differences on variability in group comparisons.
Page 18
Understanding Variability Impacts
Continues the discussion of the significance of reducing individual differences for error reduction.
Page 19
Group Comparisons in Research
Analysis of variances between and within groups indicating controlled experiments aim to lower error variance.
Page 20
Effect Detection Probability
Clarifies that as error variance drops, the likelihood of detecting a real effect rises.
Page 21
Types of Within-subjects Designs
Introduces pretest-posttest and repeated-measures designs, outlining their characteristics.
Page 22
Simple Pretest-Posttest Design
Discusses a basic therapeutic study design relevant to measuring performance before and after intervention.
Page 23
Measuring Effects in Studies
Same design as previous; highlights reading program effectiveness measurement before/after treatment.
Page 24
Repeated Measures in Studies
Explanation of participants going through all conditions and collecting varied measures.
Page 25
Historical Context: Stroop Experiment
Discusses the Stroop effect as a classic example of independent and dependent variables involved in cognitive research.
Page 26
Detailed Example of Repeated Measures
Reiterate the ability to take multiple measurements from same participants across conditions.
Page 27
Similar Content Focus
Reiteration of repeated measures within individual participants to understand effects thoroughly.
Page 28
Combining Designs
Introduces cross-over design which integrates both within and between-groups designs for comparison.
Page 29
Clinical Trial Design Choices
Proposal of various experimental designs and the implications of the design choice for drug trials.
Page 30
Considerations for Drug Trials
Highlights potential design preferences for comparing new and existing treatments.
Page 31
Within-subjects Design Challenges
Discusses the potential complexities that arise from having participants involved in all independent variable conditions.
Page 32
Demand Characteristics as a Problem
Elaborates on how repeated exposure to stimuli may influence participant behavior and possible strategies to mitigate this.
Page 33
Carryover Effects Issues
Highlights practice and fatigue effects as key concerns needing careful management in experimental design.
Page 34
Patterns of Practice Effects
Discusses linear and non-linear practice effects and the necessity for counterbalancing.
Page 35
Time-related Confounds
Mentions potential external events that may influence participant performance over the course of the study.
Page 36
Study Example of Motivation's Effect
Scenario provided to analyze how time delays between tests may introduce potential confounds.
Page 37
Confounding Variables in Research Study
Discussion of how timing between tests may affect outcomes due to external factors.
Page 38
Reaction Time Study Example
Analyzes how individual learning curves can introduce practice effects in reaction time studies.
Page 39
Importance of Specific Task Performance
Clarification of how task-specific learning impacts the interpretation of study outcomes.
Page 40
Strategies for Counterbalancing
Discusses counterbalancing as a method to control for order effects while conducting experiments.
Page 41
Trial Requirements and Considerations
Emphasizes the impact of trial designs on measurement sensitivity and statistical power.
Page 42
Block Trials Discussion
Definition of block trials and their role in organizing experimental conditions effectively.
Page 43
Factors in Ordering Trials
Key considerations for the time taken by trials and their implications on participant fatigue or maturation effects.
Page 44
Complete Counterbalancing Examples
Provides an example illustrating how to use various counterbalancing techniques to control for biases in experimental conditions.