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EPPP > Stats/Research Design > Flashcards

Stats/Research Design Flashcards

1
Q

What is the difference between true, quasi, and non-experimental studies?

A

Exp: Manipulated IV and random assignment

Quasi: manipulation of an IV without random assignment

Non exp: No intervention/manipulation

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2
Q

Nomothetic vs idiographic

A

Group based research vs single subject

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3
Q

Autocorrelation

A

Problem for single subject design – the effect of measuring the same person repeatedly

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4
Q

Multiple baseline design

A

Treatment is provided sequentially across subjects/situations/behaviors to reduce problems of history (other reasons for change)

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5
Q

Simultaneous/Alternating Treatment design

A

Providing 2+ treatments at different and varied times of day to compare relative effectiveness (e.g., two different reinforcers)

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6
Q

Changing criterion design

A

Goal of changing behavior in increments, and adjusting the target criterion with practice (eg cutting back on smoking)

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7
Q

Time sampling – momentary and whole-interval

A

Recording behaviors with no discrete beginning/end by measuring time for which they are displayed – either y/n (momentary) or for the full duration (whole interval). Eg paying attention for full minute.

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8
Q

Event recording

A

Frequency counting target behaviors

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9
Q

Cluster sampling

A

Randomly selecting pre-existing groups of subjects

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10
Q

Systematic sampling

A

Selecting subjects based on a set ratio from a random start on a list (e.g., every 3rd person)

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11
Q

History (threat to internal validity)

A

Specific incidents that occur outside of the experiment that affect performance

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12
Q

Maturation (threat to internal validity)

A

Time based effects on performance (eg fatigue, aging)

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13
Q

Solomon Four Group Design

A

Addresses the problem of practice effects.

Two groups are measured pre-post, one gets the intervention

Two groups are measured post only, one gets the intervention

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14
Q

Instrumentation (threat to internal validity)

A

Changes in observers/equipment (eg machine wearing out over time)

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15
Q

Attrition/experimental mortality (threat to internal validity)

A

Differential loss of subjects across groups

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16
Q

Diffusion (threat to internal validity)

A

“contamination” of the groups when the control group inadvertently gets some of the treatment.

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17
Q

Threats to internal validity

A

Factors other than IV that may cause change in the DV

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18
Q

Threats to construct validity

A

Things associated with the intervention other than the SPECIFIC FEATURE that caused change (eg rapport rather than cognitive restructuring)

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19
Q

Rosenthal Effect vs Demand characteristics.

A

Rosenthal is Experimenter expectancy bias – cues transmitted by experimenter to subjects (fixed by experimenter blind)

Demand is things in the procedures that affect subject behavior (fixed by subject blind)

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20
Q

John Henry effect/compensatory rivalry

A

Control group participants try harder than experimenter due to a sense of competition

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21
Q

What is the relationship between internal and external validity

A

Inverse relationship.

The more controls exist, the less generalizable it’s likely to be.

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22
Q

What’s the difference between interval and ratio data

A

Interval has no absolute zero score, ratio data does.

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23
Q

What percentiles correspond to each whole-number Z score from -3 to +3

A
  • 3: 0.1st
  • 2: 2.5th
  • 1: 16th,

0 : 50th

+1: 84th

+2: 97.5th

+3: 99.9th

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24
Q

What percentile is an IQ score of 70?

A

2.5

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25
Q

What is the Z score formula?

A

Z = (X - Mean) / SD

26
Q

Explain standard error of the mean

A

The average deviation between sample mean and population mean. It’s calculated as

(SDpop) / √N

27
Q

Beta

A

Probability of making Type II error

(Power = 1 – beta)

28
Q

Homoscedasticity

A

Parametric test assumption that there should be similar variability among groups

29
Q

What is McNemar’s test used for?

A

Group differences with nominal data

when groups are correlated (e.g., diagnosis y/n across siblings)

30
Q

Coefficient of determination

A

Square of correlation coefficient. The amount of variability in Y that’s shared with X.

31
Q

What happens to the correlation coefficient if you have a restricted range?

A

It drops dramatically (underestimates relationship)

32
Q

Canonical correlation

A

Tests relationship between two sets of multiple variables

33
Q

What is the relationship between effect size and standard deviation?

A

Effect size is expressed in units of SD.

Eg effect size of .5 would be response of, on average, half a standard deviation

34
Q

What is the reliability coefficient (range and cut-off)

(RXX)

A

The percentage of true score variability. Range from 0.0 to 1.0, cut off is .8.

35
Q

Content sampling (error)

A

Error resulting from whether or not a test’s items correspond to the test-taker’s knowledge base.

36
Q

Time Sampling (error)

A

When a test is given twice and the scores are different due to time-related factors (Eg forgetting)

37
Q

Test heterogeneity (error)

A

When items on a test tap into more than one domain.

38
Q

How does the number of items affect reliability?

A

Reliability increases with more items

39
Q

How does the homogeneity of items affect reliability?

A

More homogeneous items = increased reliability

40
Q

How does the range of scores affect reliability?

A

A restricted range reduces reliability

41
Q

How does the ability to guess affect reliability?

A

The easier items are to guess, the lower reliability is.

42
Q

Standard error of measurement

A

The standard deviation of the theoretical, normal distribution of scores of one individual on equivalent tests. Aka the average amount of measurement error.

43
Q

What does this formula measure:

SDx √(1-rxx)

A

Standard error of measurement (average amount of error in measuring a latent variable)

44
Q

Explain the relationship between standard error of measurement and confidence interval?

A

CI = true score =/- the standard error of the measurement for 68% CI. Double or triple it for 95 and 99% CI.

45
Q

Content validity

A

How adequately a test samples the target (representative sample of the knowledge/skills)

46
Q

Criterion-Related Validity Coefficient (range and cut-off)

A

Measures how well a score can predict an outcome, ranging from -1 to +1. Validities beyond .2 are acceptable.

47
Q

Standard error of the estimate

A

The average error in estimating a person’s criterion score based on a predictor

48
Q

What’s the difference between standard error of the measurement and standard error of the estimate?

A

Measurement concerns reliability (how accurate is it at testing y)

Estimate concerns predictive validity (how good is it at predicting a later outcome)

49
Q

What is the criterion-related validity coefficient (rxy) and cut off?

A

The correlation between predictor and criterion ranging from -1 to +1, acceptable cutoff is .2.

50
Q

What are Taylor-Russell tables used for?

A

They indicate the amount of improvement in selection when a predictor test is used (incremental validity)

51
Q

Selection ratio

A

The proportion of open positions to applicants. A low ratio means there are many more applicants than positions.

52
Q

Adaptive tests (item response theory)

A

Tests wherein the response to one item determines whether further questions will be asked, resulting in the fewest number of items required.

52
Q

Adaptive tests (item response theory)

A

Tests wherein the response to one item determines whether further questions will be asked, resulting in the fewest number of items required.

53
Q

What happens to criterion-related validity when a test is cross-validated (ie given to another group of people)

A

Criterion related validity decreases because of sample differences.

54
Q

How does restricted range / homogeneous sample affect criterion-related validity?

A

Validity decreases.

55
Q

What is the relationship between validity and reliability

A

Validity is less than or equal to the square root of reliability. Reliability sets ceiling for validity.

Validity ≤ √Reliability

56
Q

Criterion contamination

A

When a rater knows of the subject’s predictor score before assigning criterion rating.

57
Q

Construct validity

A

How well a test measures the target trait. Includes convergent and divergent validity

58
Q

How do you square decimals?

e.g.: square .1, .4, and .7

A

Square the number after the decimal and add a zero if it’s single digit. Should be 2 digits after the decimal.

.12 = .01.

.42 = .16

.72 = 0.49

59
Q

How do you estimate the square root decimals?

e.g. square root of .4, .9

A

Make it 2 digits if needed (add a zero), and find the whole number closest to the square root. Then make sure the answer is in tenths (1 digit after the decimal)

.4 = 0.6 (closest to 40 is 62 = 36)

.9 = .9 (closest to 90 is 92 = 81)

EPPP (8 decks)

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