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Research Methods 3006 > Exam 4 > Flashcards

Exam 4 Flashcards

1
Q

Field Research

A

Naturalistic observation, Case studies, Archival

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2
Q

Qualities of Field research

A

little or no manipulation, little or no random assignment, less control

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3
Q

Whats the point of field research

A

External validity, easy generalization to real world

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4
Q

When do we use a Quasi-Experiment?

A

When a true experiment is not possible, unethical to move people around (like sick/not), and it is not possible to change peoples genes

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5
Q

Qualities/aspects of a quasi-experimental design

A

causal hypothesis, at least 2 levels of an IV(not always manipulated), specific procedures for testing hyp, some controls for threats to validity(double-blind,automation etc.)

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6
Q

Types of quasi-experimental designs:

A

Non-equivalent control-group design

Interrupted time-series design

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7
Q

Non-equivalent control group design

A

pre-existing control/experimental group, groups can be made similar on important

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8
Q

Interrupted time-series design

A

One group tested repeatedly, Within subjects design

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9
Q

Types of designs for Program Evaluations:

A

randomized control group design, non-equivalent control group design, single group interrupted time series, pretest-posttest design(w/no control group, not recommended)

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10
Q

Why transfer data?

A

Make non-normal distributions, or conceptual reasons for better understanding of the data

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11
Q

Types of transformations

A

sqrt(X), Log2(X), 1/(X)

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12
Q

Data transformation:Skew, how to report?

A

Use the raw data for: Descriptive summary values (Mean, SD, N)
Use Transformed data to: Run the parametric tests(t,F,ANOVA)

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13
Q

Platykurtotic

A

flat (values distributed evenly)

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14
Q

Leptokurtotic

A

Tall (values mostly around the mean, and less extremes)

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15
Q

Types of data

A

Nominal, Ordinal, Interval, Ratio

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16
Q

Nominal

A

Data with an order

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17
Q

Ordinal

A

Ordered, but not necessarily evenly spaced

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18
Q

Interval

A

Equal interval, no absolute 0

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19
Q

What do you use when you do not have an equal interval but want one?

A

Item response theory

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20
Q

Describe item response theory

A

How likely is it that a given person will get a question correct, It put persons responding, and the items they are responding to on the same scale… (so equal interval)

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21
Q

Ratio

A

Ordered, equal intervals, absolute zero

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22
Q

When do you use the Rasch Model?

A

For dichotomous responses (like true false)

23
Q

When do you use the Rasch credit model?

A

For polytomous responses

24
Q

Information received from Item Response Theory:

A

item difficulty (b), Step difficulty (o), and person scores(0)

25
Q

In multiple regression what is this used for:

Y’=a+b1X1+b2X2

A

To predict a DV from multiple IV’s (1 DV, IV1, IV2, IV3…etc.)
(allows one to assess how many (or few) IVs predict a DV in a model)

26
Q

Y’=a+b1X1+b2X2

A 
a  =  regression constant (intercept)
b1 = partial regression coefficient for IV predictor 1
b2 = partial regression coefficient for IV predictor 2
X1 = score on IV predictor 1
X2 = score on IV predictor 2
27
Q

Hierarchical Multiple regression

A

Planned, incremental, multiple regression is done in steps, and planned by YOU

28
Q

Stepwise Multiple regression

A

Unplanned, incremental, computer selects best IV correlated with the DV successively, Examine R2 and its change. (not the best bc you can end up with a worse model than if you made it)

29
Q

Issues with Multiple regression:

A

IV’s may be correlated

30
Q

multicollinearity

A

When the IV’s overlap too much

31
Q

Special correlations

A

Partial regression coefficient, Semi-partial (“Part”) correlation, partial correlation

32
Q

Partial regression Coefficients

A

a regression weight that adjusts for the other regression weights in a multiple regression model, but when both predictors are taken together in the same model, the regression weights change

33
Q

Semi-partial (“Part”) correlation

A

when squared, (sr2) is the unique proportion of Y variance uniquely explained by X1

34
Q

Partial correlation

A

when squared, (pr2) is the proportion of variance in Y not associated with X2 that is associated with X1

35
Q

Multiple regression becomes complex when…

A

you add in IV predictors that are related to each other

36
Q

Factor Analysis

A

used to reduce the several variables into sets of variables

assess how well items or scores align themselves on single or multiple dimensions

37
Q

Two types of Factor Analysis

A

Exploratory, and confirmatory

38
Q

Exploratory factor analysis

A

the goal is to extract a common variance of the variables with their factors

39
Q

What question does EFA answer?

A

how many factors are in this set of variables

40
Q

Factor loading=

A

correlation of variable X with a factor

41
Q

Confirmatory factor analysis (CFA)

A

We know how many factors we want to extract, and we know what relationship the factors should have with the variables

42
Q

Reliability

A

consistency or stability in measurement

43
Q

If a test is not “reliable”…

A

there is too much measurement error

44
Q

X (observed score) =

A

T (true score) + E (Error)

45
Q

Ways to test reliability:

A

Test-retest Reliability, Slipt half, Chronbach’s alpha, Item-total correlation

46
Q

Test-retest reliability

A

measure the same people twice on the same scale, then compute the coefficient between the two occasions

47
Q

Why can test-retest reliability be misleading?

A

scores can shift up, yet maintain the same order, did they improve? or are they stable? ??????

48
Q

Split half (reliability)

A

split the test in half and correlate the two halves

49
Q

Split half strengths

A

can get reliability estimate with only one test

50
Q

Split half weaknesses

A

measuring the same traits throughout the scale?

51
Q

Chronbach’s Alpha

A

Average of all possible ways of splitting a test

52
Q

Problems with Chronbach’s Alpha

A

the more items there are, the more reliable the test is…which means Cronbach’s alpha is measuring…?

53
Q

Item-total correlation

A

take item 1’s score and correlate it with the sum of all others. (If persons score high on this item, and high on the total test, then the relationship should be high.)

Research Methods 3006 (4 decks)

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