MIDTERM 1 Flashcards
Describe the non experimental method
Both variables are measured and determined if they correlate
Why cannot causal statements be made from the non experimental method?
- No temporal precedence
- The third variable problem: extraneous variables may be causing the relationship
Types of non experimental relationships
- Positive linear
As one variable increases, so does the other - Negative linear
As one variable increases, the other decreases - Curvlinear
The direction of relationship changes at least once - No relationship
Circle scatter plot/horizontal line
What is an experimental method
Direct manipulation and controls of variables
Can describe a causal relationship between variables
Difference between an independent and dependent variable
Independent: manipulated
Dependent: measured
What is temporal precedence?
Causal variable comes first
How is causality established?
- Temporal precedence
- Covariation
- Eliminate plausible alternative explanations
Some also say the cause needs to be:
- Necessary
- Sufficient
Define Covariation
participants show a different effect between the control and experimental condition
How are alternative explanations eliminated?
- Use an experimental control
- Use random assignment so that any extraneous variables are just as likely to affect each group
How is high internal validity met?
When only the independent variable can be the cause of the results
- Temporal precedence, covariation and eliminating alternative explanations
Difference between necessary and sufficient?
Necessary: cause must be present for the effect to occur
Sufficient: cause will always produce the effect
Experimental design steps
- obtaining equivalent groups of participants
- Introducing the independent variable
- Measuring the effects of the independent variable on the dependent variable
Types of experimental designs to obtain equivalent groups
- independent group design
- repeated measures design
- match pair design
What is an independent group design?
Randomly assigning participants to experience one of the conditions (between-subject design)
Advantages and disadvantages of independent group design
Advantages:
- Avoid order effects and demand characteristics - Can use treatments with permanent effects - Similarity to "real world" setting
Disadvantages:
- Any detected difference between conditions may be attributed to group differences - Any true differences may not be detected due to low power - Need many participants - Partipant bias and experimenter expectations
How do you create equivalent groups in independent group designs?
- Random assignment
- Use matched pairs (ex. twins, IQ etc…)
- One can never be sure if matching was effective in creating equivalent groups
What is a repeated measures design?
Assigned to participate in all levels of the independent variable (within-subjects design)
- First choice as it reduces measurement error
When is a repeated measures design not possible?
When IV is a subject variable
- ex. transgenic vs. wild type mice, male vs. female
When order effects make it impossible
- ex. effects of 1 treatment is permanent (ex. surgery)
Advantages and disadvantages of a repeated measures design
Advantages:
- Fewer participants, maximize the data collected
- Sensitive to detecting differences between IV levels
- Less variance in data attributed to error
Disadvantages:
- Order effect - Demand characteristic - Participant bias - Experimental expectations
What are order Effects
The order of presenting treatments effects the dependent variable
- Practice effect
- Fatigue effect
- Contrast effect
Demand characteristics
- Any feature of a study that might inform the participant of the purpose and consequently affecting their behavior
(may deliberately act to confirm or undermine hypothesis)
Counteract demand characteristics:
- Deception - filler items - placebo
- Ask participant what they think the hypothesis is
Participant biases
Placebo effects:
- Use placebo group
- Waitlist control condition
Adaptive procedures:
- Staircase design: trials become more and more difficult if the participants gets the questions correct, incorrect = more easy
- For cognitive tasks ie. sound levels
- Randomize the order to decrease stress on animals (ie. trails don't get more and more difficult each time, the order is randomized)
Where do experimenter expectations come from?
- Treating participants in each condition differently
- Record or interpreting data differently in different conditions
How do you avoid experimenter expectations?
- Use repeated measure design
- Automated presentation of conditions and recording of data
- Double-blind experiment
Describe the types of order effects
Practice effect:
- Performance improves because of repeated practice of a task
Fatigue effect:
- Performance worsens as the participant becomes tired/bored/distracted
Contrast effect:
- The response to the second condition is altered because the conditions are contrasted (first condition can affect the experience of the second)
How do you deal with order effects?
- Counterbalancing
- Rest period may counteract the fatigue effect - Use independent group design
What is counterbalancing?
A way to deal with order effects by changing the order of IV levels
Complete counterbalancing:
- All possible orders of presentation are included in the experiment
- N! orders
Latin square:
- Each condition appears at each ordinal position
- Each condition precedes each condition once
- N orders for even N, 2N for odd N
Partial counterbalancing:
- Random order of IV
- Reverse counterbalancing (ex. ABCCBA)
What is a matched pair design?
First select pairs of participants that score equally on some variable of interest (use pretest), then use random assignment within each pair to assign to the independent variable
What is a pretest?
Test given to groups and scores of groups are compared to ensure groups were equivalent on the critical variable
What are experimental designs that include a pretest?
- Pretest-posttest design
- Solomon four-group design
When should you add a pretest and what are the disadvantages?
Add when:
- Small sample of mortality (dropout) is high
- Select appropriate participants
Disadvantages:
- Can be time consuming and awkward to administer - Can sensitize the participant to what you will be studying (can be distinguished using deception)
What is a pretest-posttest design
Measurements taken before and after the treatment
What is a posttest-only design
No pretest given, measurements only taken after the treatment
Describe a solomon four-group design
Pretest is treated as a second independent variable
- Randomly assign half of the participants to pretest or no pretest condition, then randomly assign to independent variable
What is a operational definition?
Definition of DV + IV with techniques used to measure and manipulate
Important for replication
Differences between a response, situational, and participant variable
Response variable:
Describes responses/behaviors of individuals
Can be measured in any design
Situational variable:
Describes characteristics of the situation or environment
Can be measured in any design but can only be manipulated in an experimental design
Participant variable:
Describes the characteristics that an individual brings
ex. intelligence, sex
What are the differences between measurement error, systematic error and random error?
Measurement error:
systematic error + random error
Extent that a measure is unreliable
Systematic error:
Created by faulty equipment or bias (error is always the same amount each trial)
Decreases validity
Random error:
Errors are unpredictable and cannot be reproduced.
Decreases reliability
Describe variability and reliability in terms of an operational definition
Variability:
Does the operational definition measure the concept it’s supposed to?
Reliability:
Is the operational definition based on observable, objective behaviors?
What makes a good operational definition?
Reliability and validity are the primary criteria to make a good operational definition, but it must also be:
- Absence of bias - Cost efficient - Practical - Objective - Hight acceptance
How would a hypothesis be unfalsifiable?
- No empirical evidence is obtainable
- predictions are so vague they can hardly fail
- it is upheld even though it is regulated by data by introducing new assumptions post-hoc
- no operational definition is given in prediction
What is the difference between a hypothesis and prediction?
Hypothesis:
- Statement may or may not be true
- written in present tense
- Derived from a broader theory
Prediction:
- related to specific methodological details
- written in future tense
- derived from a general hypothesis
- includes operational definitions
