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Research Design and Analysis final > Study Guide content > Flashcards

Study Guide content Flashcards

1
Q

what does it mean to be conservative for a test?

A

a p-value of 0.01 to be statically significant is more conservative than 0.05. (how much error they will allow into their study).

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2
Q

Factorial design

A

more than one independent variable

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3
Q

A quasi-experimental design: non equivalent control group

A

Basically just an experimental design but the researcher had picks who is in the control and experimental groups.

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4
Q

A quasi-experimental design: reversal designs

A

ABA method

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5
Q

A quasi-experimental design: interrupted time series

A

Data is being collected at multiple times before and after manipulation is administered. Basically a “longitudinal study” comparing before and after manipulation.

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6
Q

A quasi-experimental design: control series design

A

create two groups with people of similar characteristics and then you make them the control vs experimental group. SO you can make sure that whatever manipulation you did for one group wouldn’t have happened just in the “wild”

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7
Q

A quasi-experimental design: single subject designs

A

comparing before and after intervention on one participant

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8
Q

A quasi-experimental design: multiple baseline designs

A

Introducing the manipulation at different times.

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9
Q

A quasi-experimental design: across subjects, behaviors

A

Apply the treatment or intervention to all subjects/behaviors simultaneously. and then you Monitor changes in all subjects/behaviors after the intervention.

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10
Q

Program evaluation concept:
constructive/destructive

A

Adding things one by one or removing things one by one to see which variable is the issue or solution.

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11
Q

Program evaluation concept:
assessment of interventions

A

-Clearly outline the objectives and goals of the intervention.
- Choose appropriate measuring methods
-track progress.
-Analysis:
-Feedback and Improvement:

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12
Q

what do you use to find the difference between groups?

A

ANOVA or T-test

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13
Q

what do you use to find the relationship between two groups?

A

regression and correlation

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14
Q

degrees of freedom

A

a way you can lie with statistics
-manipulating degrees of freedom
- misinterpreting the results

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15
Q

y-axis

A

by editing the layout of the y-axis you can lie with statistics

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16
Q

sample bias

A

lieing with statistics

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17
Q

problem graphics

A

lying with statistics

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18
Q

research hypothesis

A

an idea to be tested

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19
Q

Null hypothesis

A

assumes that there is no effect or relationship. Researchers are trying to reject the null hypothesis in experiments.

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20
Q

effect size

A

helps us to understand how much difference or relationship is between two variables

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21
Q

power analysis

A

statistical measure to determine how many participants you want in a study.

22
Q

Alpha

A

significance level

23
Q

Type 1 error

A

testing positive when you are negative

24
Q

Type II error

A

testing negative when you are really positive

25
Q

Generalization

A

how well conclusions can generalize to a population.

26
Q

Meta-analysis

A

an analysis of a lot of research papers on the same topic

27
Q

threats to external validity

A

effects that inhibit generalization.
- sample size
- sample bias
- measurement effects
- regression to the mean
- history effects
- instrumental degradation
- ect.

28
Q

what to do with outliers

A

keep them in if they change the outcome too much. Throw them out if it doesn’t really matter.

29
Q

Sensitivity

A

Catching the people WITH the condition

30
Q

Specificity

A

not wrongly identifyingg that DONT have the conditionn.

31
Q

Confidence intervals

A

estimating the likely hood of the sample data to be true about a population.

32
Q

rate analysis

A

incidence and prevalence

33
Q

Incidence

A

a component of rate analysis:
The number of new cases of a condition that develop in a
population during a defined time. (longitudinal study)

34
Q

prevalence

A

a component of rate analysis:
The total number of people in a population with a
condition at a given point in time.(cross sectional)

35
Q

odds ratio

A

odds that an event will occur in one group versus the odds that is will occur in another group.

36
Q

pathological Science

A

when scientific claims are made without scientific studies to back them up.

37
Q

What is Content Validity

A

Does the test cover all of the material

38
Q

What is Criterion Validity

A

How well a test predicts or correlated to an established criterion.

39
Q

What is Construct validity

A

is it measuring what it is supposed to measure.

40
Q

what is concurrent validity

A

Does the test correlate with other tests we have given in the past.

41
Q

what is convergent vailidty

A

same as concurrent ( does the test correlate to other tests we have given in the past)

42
Q

predictive validity

A

does the test predict future performance.

43
Q

Meta-analysis

A

analysis of lots of research papers in one, to draw conclusions.

44
Q

4 steps to Meta Analysis

A

1) get on PubMed and find all the research on your wanted topic.
2) make a common metric for the results (example is effect size)
3)code dimensions of the study
4) draw conclusions on the findings.

45
Q

Longitudinal designs

A

designs over a long period of time with lots of analysis at different points

46
Q

cohort designs

A

follows a group of people over time.

47
Q

what do you do with missing data

A

ignore it is best

48
Q

Quasi experimental design

A

(If you design it and it makes a better argument use it) We choose who is in the independent and dependent groups. You need to put in the discussion why you decided to do that comparison, and why you did not do randomization.

49
Q

Two types of replication

A

exact(illegal with animals) or conceptual(trying to learn something new with the replication)

50
Q

Pathological science

A

result from slopy methods and difficult measurements and media.
(Research conclusions not based on good research).

Research Design and Analysis final (8 decks)

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