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Abnormal psychology > Psy290pt2 > Flashcards

Psy290pt2 Flashcards

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1
Q

What is a confounding variable?

A

It varies along with the independent variable.

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2
Q

What is in a post test design?

A

1) obtain two equivalent groups of participants. 2) manipulate with independent variable 3) measure dependent variable

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3
Q

What are some examples of levels for independent variable? (Think of design)

A

You can have one group of smokers, smoke then the other not. You can also have different times (meditate 5 minute group vs. Meditate 20 minute group). Or 2 different qualitative things (anxiety 1 group writes about it then other meditates)

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4
Q

What is a rule of thumb for # of participants for each group?

A

50 is pretty standard.

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5
Q

What is pretest posttest?

A

Pretest assures that both groups were the same (even if randomly assigned) post test to see difference.

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6
Q

What is a drop out factor in an experiment called?

A

Attrition or mortality. People drop out for various reasons *illness. Family emergency. OR the test itself (further about this on another card)

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7
Q

How might mortality effect a program design (experiment result?) Think about smokers

A

You have design about how to reduce smoking, but all heaviest smokers drop out leaving results from light smokers. Attrition (mortality) is a way to explain results.

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8
Q

What are some disadvantages to a pretest?

A

It may sensitize people to experiment. It can be a long process and and awkward to administer depending on experiment.

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9
Q

What is independent groups design?

A

Its also known as between subjects design. Participants are assigned to a random group and each person participates in one group.

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10
Q

What is repeated measures design?

A

Experiment with two conditions each participants is assigned to both levels of independent variable, each participant is measured after receiving each level of independent variable.

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11
Q

What are the pros and cons of the repeated measures design?

A

Pros: fewer research participants are needed. If there’s not a lot of participants or the experiment is too expensive this is cheap. Also this usually requires some kind of training, so it’s less time with less people. It’s also easier to see the effect of the independent variable
Cons: different conditions musg be present in a particular order. order effect

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12
Q

What are some different order effects?

A

Practice effect, people learning and getting better.
Fatigue effect, deterioration of performance
Carry over effect. The effect of first treatment to carry over to second. It can also mean when 1st effect produces an influence on person when 2nd effect is introduced.

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13
Q

What is counter balancing?

A

Basically you can assign one group high material or low material, they recall the info. Then they are assigned the opposite. There is another group that mirrors it in opposite way. This is to deal with the issues of order effect in repeated measures design.

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14
Q

What is a Latin square?

A

A limited set of orders to ensure that each condition appears in ordinal position and each condition precedes and follows each condition one time.
(Use the rotation example 0 degrees to 60, 180 and 120) tthere are 4 groups, 4 conditions which means 4 different orders 16 options without repeating.

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15
Q

What does time interval between treatments help with?

A

Counter balancing some effects like fatigue or dosage effects. You need to measure different dose sizes and how long they last so you don’t want to do resrarch all at once or every day.

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16
Q

What are advantages to repeated design measures over independent groups?

A

1, reduction of # of participants needed to complete experiment. 2. Greater control over participant differences so easier to detect effects of independent variable.

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17
Q

What is a Solomon Four design?

A

The experimental and control group are studied with and without a pretest

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18
Q

What is a straightforward manipulation?

A

Use instructions and other stimuli to manipulate the independent variable i.e. we randomly assign people to one group vs another and one gets instruction that looks different than the other.

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19
Q

What is staged manipulations?

A

create a psychological state in participants or simulate a real world situation or a “confederate” who appears to be a participant.

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20
Q

What is the strength of manipulation?

A

potential amount of impact of the independent variable on the dependent variable.
Strong internal validity.
strongest possible manipulation may entail a situation that rarely if ever occurs in real world. Should be as strong as possible within the bounds of ethics.

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21
Q

What is the Cost of manipulation?

A

It can be costly to run tightly controlled experiments. doesn’t always mimic real life. balancing internal validity with external validity.

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22
Q

What are self-reports?

A

measures that require participants to describe themselves - rating scales with descriptive anchors (this is for dependent variable)

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23
Q

What is a behavioral measure?

A

direct observations of behaviors. Often observed behaviors must be quantified in terms of rate, reaction time, duration. Behavioral measure is not an actual behavior but behavioral intention/choice

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24
Q

What are physiological measures?

A

recording of responses of the body: ie. galvanic skin response (electrical conductance of skin) EMG, electroencephalography (EEG)

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25
Q

Describe multiple measures for dependent variable measuring techniques

A

Using several methods to qua tiny the same construct in a research study allowing for a more co.orehensive understanding of the phenomenon by capturing different aspects. This can be questionnaires, physiological, observations all trying to address underlying concept

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26
Q

What is the ceiling effect?

A

Capturing the high end of scores
People max out on measure.

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27
Q

what are demand characteristics?

A

Subtle clues or aspects of an experiment that is unintentionally signaling to participants, what the researcher is hoping to find potentially influencing their behavior and responses to conform to those expectations and compromising the validity of the study results

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28
Q

What are filler items?

A

unrelated items on a questionnaire to disguise a dependent variable.

29
Q

what is a placebo group?

A

people who get a placebo instead of the actual drug (ex)

30
Q

Explain Expectancy Effects

A

this is experimenter bias: The impact of the experimenters’s bias on the outcome of a research study.
They may treat participants differently depending on conditions. They may have different ways they interpret behavior that has been recorded.

31
Q

What is a single blind experiment?

A

participant is unaware of whether a placebo or actual drug is being administered

32
Q

What is a double blind experiement?

A

neither participant nor experimenter knows whether the placebo or actual treatment is being given.

33
Q

What is a pilot study?

A

researcher does a trial run with a small # of participants.

34
Q

What is manipulation check?

A

an attempt to directly measure whether IV manipulation has the intended effect on participants

35
Q

what is preregistration?

A

process by which researchers identify and articulate their research questions , hypotheses, and analysis plan for their studies before they collect and analyze data.

36
Q

What is a quasi experimental design

A

the researcher does not have he ability to manipulate the independent variable. We don’t have the same level of control as an experiment (like assigning people groups)

37
Q

What is an issue with a one group posttest only design for quasi experimental design?

A

There is no internal validity. It had no control group and no pretest comparison. Weak designs.

38
Q

What are some potential threats to internal validity in a one group pre-test-posttest design (quasi experimental???)

A

history effect, maturation effect, testing effect, instrument deacay, regression toward the mean

39
Q

What is a history effect?

A

outside event thata could bne responsible for results in a one group pretest posttest design

40
Q

What is a maturation effect?

A

there’s somet naturally occuring qualitiy that is changing within the individual that’s responsible for results (time between sample them 1st time vs 2nd time they get older, a reason they are reporting differently)n a one-group pretest posttest design

41
Q

What is instrument decay?

A

The people who are measuring originally may have different scores over time. It’s not consistent or they may have totally different people measuring.

42
Q

What is testing effect?

A

Participants are able to guess the results or answer according to previous test or what they think people want to hear. n a one-group pretest posttest design

43
Q

what is regression toward the mean for one group pretest posttest design?

A

extreme scores over time will trend toward the average. First measure extreme, second measure more average.

44
Q

what is nonequivalent control group design?

A

Quasi experimental research design, where researchers compare a treatment group to a control group that is not randomly assigned example. How many students have done CP? R, versus how many students have done first?Aid. This can introduce bias. Non equivalent control group is a group that is similar to the treatment group. In many ways, but doesn’t receive intervention

45
Q

What is selection bias?

A

When people can pick the group they want.

46
Q

what is a nonequivalent control group pretest-posttest design?

A

compares an experimental group with a nonequivalent control group and incorporates a pretest/posttest. We get a little control with the pretest (did participants in both groups start in same place or different?) Stil weak

47
Q

What is a propensity score matching?

A

mitigates the disadvantages of nonequivalent group designs. - method of matching participants from nonequivalent group that have similarities across measurements. (great for nonrandom assignment)

48
Q

Explain interrupted time series designs?

A

examine dependent variable over an extended period of time before and after the independent variable is implemented (vulnerable to interpretation problems possible regression to the mean) Quasiexperimental design.

49
Q

What is a control series design?

A

an extension of the interrupted time series design in which there is a comparison or control group (involves finding a similar population that did not receive manipulation being studied)

50
Q

What are the 3 ways we can describe the results of a study of relationships between variables

A

comparing group percentages, correlating scores of individuals on two variables and comparing group means.

51
Q

How can we display difference frequency distributions?

A

hisograms, pie charts, bar graphs, frequency polygons

52
Q

What do pie charts illustrate?

A

percentages, nominal variables,

53
Q

What do bar charts charts illustrate?

A

nominal, ordinal level data, frequency often,

54
Q

what do frequency polygons illustrate?

A

ratio and integral, distribution scores, multiple scores, comparison 2 groups.

55
Q

what do histographs illustrate

A

continuous quality (so ratio), not discrete categories.

56
Q

explain graphing relationships

A

bar is when x axis is nominal. line is when x is continuous

57
Q

what is multiple correlations/regression

A

used to combine a number of predictor variables to increase the accuracy of prediction of a given criterion or outcome variable
Symbolized as R
Y=a+b(1)+b(2)x(2)+…… where Y is the criterion variable, x(1) to x(n) are the predictor variables. a is a constant and b to b(n) are the weights that are multiplied by scores on the predictor variables,

58
Q

what is regression equations?

A

calculations to predict a person’s score on one variable when that persons score is already known. Y= a+bx where Y is the score we wish to predict and x is the score that is known and a is a constant and b is a weighting adjustment factor.

59
Q

what is moderating and mediating variables?

A

uncontrolled 3rd variable may be responsible for the relationship between the 2 variables of interest.
When experimental research is properly designed there is no 3rd variable problem because it’s all extraneous variable s are controlled by keeping the variables constant or using randomization. Multiple regression can be used to statistically control for the effects of 3rd variables.

60
Q

What is Structural Equation modeling?

A

it’s advanced so don’t focus too much on this. It’s to evaluate a proposed set of relationships among variables.
after data have been collected, staat methods can be applied to examine how closely the proposed model actually “fits” obtained data.
Researchers typically present path diagrams to visually represent the models being tested.
These show the theoretical causal paths among variables.

61
Q

What are inferential statistics

A

achieving equivalence of groups is meant to determine that any differences in the dependent variable must be due to the effect of the independent variable. However the difference between any group will almost never be 0. Interential stats allow researchers to make inferences about true difference in population on the basis of the sample data. They give probability that the difference between means reflects random error than than a real difference.

62
Q

what are t tests?

A

they look at the difference between 2 sample means. They can come from independent samples or from linked samples (repeated measures analysis)

t = group difference / within group variabilities.

63
Q

what are f tests?

A

it’s what we use for multiple grouips. Analysis of variance (3 groups or more looking at sample means) or can be looking at repeated measures where sample means represent time pt 1 2 or 3

when a study has only one independent variable within 2 groups. They’re pretty identical to t tests.

64
Q

What is a type I and Type II errors?

A

decision to reect the null hypothesis is based on probabilities rather than certainties./ Decision may not be correct, errors may result from the use of inferential stats.
Using a decision matrix, there are 2 possible decisions and 2 possible truths about population.
Possible decisions: 1 reject null or 2 accept null
Poissible truths: 1 null is true or 2 null is false

65
Q

Type II error what is it?

A

fail to detect a significant result given that the null is false - there’s actually an effect but we can’t detect it. (usually about power, we need more sample size) (they may not know victim is alive, but they’re dead. people may not send out a warning about life threatening weather, but the weather is life threatening, equipment is safe, but it’s not actually)

66
Q

TYPe 1 error what is it?

A

if the null is true, but we reject the null hypothesis. (if someone is innocent but found guilty) (an emergency crew might think a victim is dead when they are alive, they may think equipment is unsafe, but it’s fine)

67
Q

Explain choosing a sample size and power analysis:

A

power of a statistical test determines the best sample size based on probability of correctly rejecting the null hypothesis. Power = 1-p (type 1 error)
effect sizes and desired power:
smaller effect sizes require larger samples to be significant at a 0.05
a higher desired power demands a greater sample size. Researchers usually use power between /70 and .90 to determine sample size.

68
Q
A

Abnormal psychology (2 decks)

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