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4 Goals of psychological research
Relationships -- Are they related? Do they correlate or covary?
Making predictions shows how well you understand the information.
§ Ex: Does diagnosis of depression predict performance in college?
Control behavior to make positive lasting changes in people’s lives. Use the predictions, explanations, and descriptions you find to help lead you hear.
§ What factors lead to success at Ohio State?
Sometimes involves application of existing theory and research findingsHow can we use psychology to help people with depression?
What is an Induction/Deduction/Verification Cycle
o Induction: involves looking at the evidence to make a general conclusion. It is more concerned with probabilities and determines the consequences that are most likely to be true. Unlike deductive reasoning, the conclusion drawn from inductive reasoning is not guaranteed to be true, even if the facts are correct. Instead, the conclusion is the one most likely to be true. In science, inductive reasoning is used to build theories with the evidence providing support for the theory that is most likely to be true.
o Deduction: evaluating facts to determine the logical conclusion that can be derived from them. There can only be one logical conclusion from the given facts. If the premises are true and the argument is valid, then the conclusion is said to be sound. This guarantees that a logical conclusion is true.
o Verification: Real world data (conclusions & what inductive reasoning is driven from).
o I/D/V Cycle: Real World DataInduction Theory or Abstract ExplanationDeduction Predictions about real world Verification Real world Data
4 Scientific cycles
o Theory-Data Cycle
o Basic Applied Research Cycle
o Peer Review Cycle
o Journal to Journalism Cycle
Association, causal, frequency
a claim about 2 variables, in which the level of one variable is said to vary systematically with the level of another variable, such that when one variable changes, the other variable changes too.
a claim arguing that a specific change in one variable is responsible for influencing the level of another variable.
What is an example of face validity? Let’s say you are interested in measuring, ‘Propensity towards violence and aggression’. By simply looking at the following items, state which ones qualify to measure the variable of interest:
§ Have you been arrested?
§ Have you been involved in physical fighting?
§ Do you get angry easily?
§ Do you sleep with your socks on?
§ Is it hard to control your anger?
§ Do you enjoy playing sports?
YES, but not vice versa
What are the elements of a true experiment
· Manipulate one or more independent variables to create at least two conditions (often experimental and control).
· Control all other variables so that conditions differ only on IV.
· Measure effects on the dependent variable (DV)
What are the three requirements for establishing a causal relationship
2. Temporal Precedence
3. Internal Validity
What is the different between and Independent variable and a dependent variable
· Treatment Group: the participants in an experiment who are exposed to the level of the independent variable that involves a drug, therapy, or intervention.
· Control Group: a level of an independent variable that is intended to represent “no treatment” or a neutral condition.
· Placebo Group: A control group that is exposed to an inert treatment (e.g., a sugar pill).
What is a random groups design, natural groups design, matched groups design
· Random Groups Design: (or Random Assignment) the use of a random method (e.g. flipping a coin) to assign participants to the independent variable conditions.
· Natural Groups Design: the preexisting groups or groups that are about to be
“naturally formed” ARE the conditions of the IV (e.g., gender, age, personality, history, treatment by other than the researcher).
Matched Groups Design: an experimental design in which participants who are similar on some measured variable are grouped into sets and the members of each matched set are then randomly assigned to different experimental conditions.
What is a repeated measures design?
· An experiment with a within-groups design in which participants respond to a dependent variable more than once, after exposure to each level of the independent variable.
i. Disadvantages: have potential for order effects which threatens internal validity (control order effects by counterbalancing).
Advantages of within-groups design is that it ensures that the participants in the 2 treatment groups will be equivalent, gives researchers more power to notice differences between conditions, and requires fewer participants. They are true experiments, establish internal validity when experimenters control order effects, establish covariance, and ensure temporal precedence, but they have 3 main draw backs.
Disadvantages: High levels of demand characteristics can occur. A within groups design, with or without counterbalancing, would make no sense at all.
How do you get around the disadvantages associated with this type of research design?
What is a clinical trial?
A medical experiment that has all of the elements of a true experiment but is done in the field of medicine
i. Internal validity- we can conclude that our manipulation of the IV caused change in DV
ii. Reliable- we can conclude the outcome is not due to chance
iii. Sensitive- we can detect small effects
iv. External validity- we can generalize beyond the experiment
Elements of a true experiment:
i. Manipulate one or more independent variables to create at least 2 conditions
ii. Control all other variables, conditions differ only on IV
iii. Measure effects of DV
What is a complex design, and when is the most effective time to use it?
Studying 2 or more independent variables at the same time.
What is the difference between a main effect and an interaction?
· A main effect in a factorial design, the overall effect of one independent variable on the dependent variable, averaging over the levels of the other independent variable.
· An interaction in a factorial design, a situation that occurs when the effect of one independent variable differs depending on the level of the other independent variable.
If you are given a factorial, how do you figure out how many independent variables are present versus how many conditions are present?
· A factorial design, a study in which there are two or more independent variables, or factors. Factorial designs are used when a researchers wants to test for interactions. In the most common factorial designs, researchers cross the 2 IV’s; that is they study each and every possible combination of the IV’s.-->2 IV’s vs 4 conditions
The number of numbers is how you figure out the number of IV’s. For example, a 2x3 factorial would have 2 independent variables because there are 2 numbers. (a 2 and a 3). You figure out the number of conditions by multiplying all of the numbers together. (2x3 factorial=6 conditions)
If given a graph, can you determine if an interaction has taken place or not?
Do you understand the purpose of an ANOVA test, can you interpret information produced by an ANOVA test?
· (Analysis of Variance): The F test, or ANOVA. The t test is the appropriate test for evaluating whether 2 groups means are significantly different, but when a study compares two or more groups to each other, the appropriate test is the F-test, obtained from an analysis of variance. The f test helps us decide whether the differences among the groups are statistically significant. The f test is a ratio of 2 values. The numerator contains the value representing the variability between the means, and the denominator contains the value representing the variability within the groups.
ANOVA in an example. (page A40)
1. Stating null hypothesis
2. Computation of the F ratio
3. Calculating the probability of the F value we obtained, or even larger value, if the null hypothesis is true
What are the two main kinds of single case designs?
i. Case Studies:
ii. Single Subject Experimental Designs
What is a case study (types) and why might it be useful?
i. Snapshot case: case study done within a single period of time
ii. Longitudinal case: case is done over time as key variables change naturally
iii. Intervention case: case study done over time, with a planned or unplanned change
1. Rich source of ideas for developing research questions
2 . Can provide tentative evidence in support of a theory
1. Can provide evidence against a theory
2. Useful method for studying a rare event
3. Useful way to try and examine a new intervention
1. Observer bias likely
2. Run risk of confirmation bias
3. Huge possibility of demand characteristics and expectancy results
4. Extremely limited internal validity
5. Limited external validity
What are the three main kinds of single case (N=1) experimental designs -- Stable, Reversal, and multiple baseline—distinguish them from each other.
i. Stable = AB
ii. ABAB = reversal: establish a baseline, apply treatment, discontinue treatment (should revert to baseline), apply treatment. Overall goal is to create replication within the experiment.
iii. Multiple baseline: provide comparison conditions to which a treatment or intervention can be compared
What is meant by “Baseline” in these designs.
i. Records levels of DV before treatment-this is the behavior you want to change for the better. Once baseline is established, we can predict where future behavior, if untreated,, is likely to be, so the level following treatment can be assumed to be the result of the treattment
Why do we want behavior to return to baseline in an Reversal design? Why might it not do so?
i. If behavior returns to baseline after treatment is discontinued, we have evidence for effectiveness of treatment.
ii. Might not return to baseline because:
1. Treatment effect continues even when the treatment is withdrawn
2. Variable confounded with first treatment
3. Ethical issues in removing an effective treatment
What distinguishes a quasi-experimental design from a true experiment?
What are the elements of a quasi-experiment?
i. Includes an intervention or treatment
ii. Includes measures of the DV taken after (and in some cases before) intervention
iii. Lacks random assignment of conditions but may include a “comparison group: that is not a true control group
iv. May lack control over variables that can produce confounds
What are some threats to internal validity that may affect a quasi-experiment? What are history, selection, and attrition in the context of quasi-experiments?
8. Attrition/participant mortality
ii. History- event confounded with treatment
iii. Selection- differences between treatment and comparison due to lack of random assignment
iv. Attrition- subject loss
What is contamination?
Participants talk to each other- treatment group talks to control group
What is instrumentation?
A threat to internal validity that occurs when a measuring instrument changes over time from having been used before.
What are the categorizations of quasi-experiments? (O,X, dotted lines)
i. O= measure of DV
ii. X = treatment
iii. O’s and X’s on two or more lines, separated by dashes = multiple groups with no random assignment
What is a non-equivalent control groups design without pretest– can you give an example?
i. A quasi-experimental study that has at least one treatment roup and one comparison group, but particpants have not been randomly assigned to the 2 groups
What is the interrupted time series design? Give an example. What does it look like in a diagram? What are the most obvious threats to internal validity?
i. A quasi-experiment in which people are measured repeatedly on a dependent variable before, during, and after the “interruption” caused by some event.
ii. An example is the vacation study (burnout on y axis, vacation on x axis)àdo vacations really reduce job burnout? This study measures people repeatedly on a dependent variable (in this case, job burnout) before, during, and after the “interruption” caused by some event (in this case vacation).
iv. Most obvious threats to internal validity
What is “discontinuity” in the context of an interrupted time series design? What does it mean? What does it have in common with an ABAB design?
What is the interrupted time series with non-equivalent control groups design? What does it look like?
See Television/Larceny Study (350). In this study the Iv was studied both as a repeated-measures variable (interrupted time series) and as an independent-groups variable (non-equivalent controls groups). (double check).
1. See page 350 for graph example.
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